EUROPEAN COMMISSION

Brussels, 20.9.2021

SWD(2021) 258 final

COMMISSION STAFF WORKING DOCUMENT

Statistical evaluation of irregularities reported for 2020: own resources, agriculture, cohesion and fisheries policies, pre-accession and direct expenditure

Accompanying the document

REPORT FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT AND THE COUNCIL

32nd Annual Report on the protection of the European Union's financial interests - Fight against fraud - 2020

{COM(2021) 578 final} - {SWD(2021) 257 final} - {SWD(2021) 259 final} - {SWD(2021) 262 final} - {SWD(2021) 263 final} - {SWD(2021) 264 final}

Contents

List of abbreviations

1.Introduction

1.1.Scope of the document

1.2.Structure of the document

2.TRADITIONAL OWN RESOURCES

Executive summary

2.1.Introduction

2.2.General analysis – Trend analysis

2.2.1.Reporting years 2016-2020

2.2.1.1.Irregularities reported as fraudulent

2.2.1.2.Irregularities reported as non-fraudulent

2.2.2.OWNRES data vs TOR collection

2.2.2.1.Detection rates in the COVID-19 year of 2020

2.2.3.Recovery

2.2.3.1.Recovery rates

2.3.Specific analysis

2.3.1.Irregularities reported as fraudulent

2.3.1.1.Categories of irregularities

2.3.1.2.Method of detection of fraudulent irregularities

2.3.1.3.Smuggled cigarettes

2.3.1.4.Textiles

2.3.1.5.Irregularities reported as fraudulent by amount

2.3.2.Irregularities reported as non-fraudulent

2.3.2.1.Categories of irregularities

2.3.2.2.Method for detecting non-fraudulent irregularities

2.3.2.3.Shoes are vulnerable to irregularities

2.3.2.4.Irregularities reported as non-fraudulent by amount

2.3.3.Fraudulent and non-fraudulent irregularities and goods related to COVID-19

2.4.Member States’ activities

2.4.1.Classification of irregularities as fraudulent and non-fraudulent and related rates

2.4.2.Recovery rates

2.4.2.1.Irregularities reported as fraudulent

2.4.2.2.Irregularities reported as non-fraudulent

2.4.2.3.Historical recovery rate (HRR)

2.4.3.Commission’s monitoring

2.4.3.1.Examination of the write-off reports

2.4.3.2.Commission’s inspections

2.4.3.3.Particular cases of Member State failure to recover TOR

3.COMMON AGRICULTURAL POLICY

Executive summary

3.1.Introduction

3.2.General analysis

3.2.1.Irregularities reported in the years 2016-2020

3.2.2.Irregularities reported as fraudulent

3.2.3.Irregularities not reported as fraudulent

3.3.Specific analysis

3.3.1.Modus operandi

3.3.1.1.Support to agriculture

3.3.1.2.Rural development

3.3.2.Fraud and Irregularity Detection Rates (FDR and IDR) by CAP components

3.3.3.Market measures – fraudulent and non-fraudulent irregularities

3.3.4.Reasons for carrying out checks

3.3.4.1.Irregularities in relation to rural development

3.3.4.2.Irregularities in relation to market measures

3.3.4.3.Irregularities in relation to direct payments

3.4.Anti-fraud work carried out by the Member States

3.4.1.Duration of irregularities

3.4.2.Detection of irregularities reported as fraudulent by Member State

3.4.2.1.Reported over the period 2016-2020

3.4.2.2.Reported in 2020

3.4.3.Fraud and Irregularity Detection by sector and Member State

3.4.3.1.Rural development

3.4.3.2.Market measures

3.4.3.3.Direct payments to farmers

3.4.4.Follow-up to suspected fraud

3.5.Recovery cases

Main findings

List of abbreviations

1.Introduction

1.1.Scope of the document

This document 1 presents a statistical evaluation of the irregularities and fraud detected by the Member States during 2020, in the context of past years and relevant programming periods (PP). It covers both the revenue and expenditure sides of the EU budget. This analysis is based on the notifications provided by national authorities of cases of irregularities and suspected or established fraud. Their reporting is performed in fulfilment of a legal obligation enshrined in sectoral European legislation. The document accompanies the Annual Report adopted on the basis of article 325(5) of the Treaty on the Functioning of the European Union (TFEU), according to which “The Commission, in cooperation with Member States, shall each year submit to the European Parliament and to the Council a report on the measures taken for the implementation of this article”. Therefore, this document should be regarded as an analysis of the achievements of the Member States, in terms of detection and reporting.

The methodology (including the definition of terms and indicators), the data sources and the data capture systems are explained in detail in the Commission Staff Working Document – Methodology for the Statistical Evaluation of Irregularities accompanying the Annual Report on the Protection of the EU financial interests for the year 2015 2 .

1.2.Structure of the document

The present document is divided in two parts. The first part includes an analysis of the irregularities reported in the area of traditional own resources (revenue), as well as an analysis of the irregularities reported for expenditure for the Common Agricultural Policy.

The second part is composed of three sections dedicated to irregularities reported in the area of expenditure (i) for the cohesion policy, fisheries and other internal policies; (ii) for the pre-accession policy and (iii) under direct management.

The document is completed by 27 country factsheets, which summarise, for each Member State, the main indicators and information on the detection of irregularities and fraud.

Several annexes complement the information and data, providing a global overview of the irregularities reported according to the relevant sector regulations. Annexes 1 to 11 concern Traditional Own Resources, Annexes 12 and 13 complement information on the methodology for the analysis of irregularities concerning expenditure, Annex 14 covers all the expenditure sectors for which Member States and beneficiary countries have a reporting obligation.

2.TRADITIONAL OWN RESOURCES

Executive summary

A year like no other before, 2020 was marked by the COVID-19 pandemic which had important economic and social impact. Although some Member States resisted better than others, all were strongly affected.

In 2020, the import volume of the EU27 decreased by 11.6% compared to the previous year. Nevertheless, the overall detection of fraudulent and non-fraudulent irregularities in traditional own resources (TOR) remained at a level similar to a normal reporting year. Indeed, during the period 2016-2020, around one fifth of the total number of fraudulent and non-fraudulent irregularities and of the related amounts were reported in 2020.

The decrease in import volume and a significant shift toward e-commerce caused by the pandemic have led not only to changes in the number of customs declarations to be cleared but also to a shift in customs workload and work patterns. The reaction of the national authorities to those challenges and the speed with which the customs authorities were able to adapt to new circumstances are only partially comparable, as the rules of lockdowns have been changing greatly over the year among the Member States and within specific regions in some Member States.

The different degree and length of the confinement measures as well as country-specific challenges influenced the possibilities of Member States to adapt to the changing reality.

However, some Member States were able to resist better and were more flexible in adjusting their customs control activities. As a result, in 2020 several Member States reported the highest TOR amount detected in cases of fraudulent and non-fraudulent irregularities during the period 2016-2020.

Nevertheless, the overall TOR amount reported in 2020 for cases of fraudulent and non-fraudulent irregularities decreased by 2% in comparison with 2019 and by 5% in comparison with the five-year average.

National anti-fraud services played a key role in detecting fraud in 2020. Inspections by anti-fraud services was the most successful method of detecting fraud and surpassed post-release controls and release controls in detecting fraudulent duty evasion.

Non-fraudulent irregularities were primarily detected by means of post-release controls. Tax audit gained importance as a detection method in 2020 in monetary terms as significant amounts were discovered during such controls.

Most cases reported in 2020 as fraudulent relate to undervaluation, incorrect classification/misdescription of goods or smuggling. Footwear, textiles, vehicles, electrical machinery and equipment were the types of goods most affected by fraud and irregularities in number of cases and in monetary terms. China remained also in 2020 the most important country of origin of goods affected by fraudulent and non-fraudulent irregularities.

For COVID-19 related goods such as protective garments, a slight increase in the amounts reported as irregular was observed in 2020. However, analysis shows that the impact of irregularities affecting COVID-19 related goods is typically low and remained relatively low in 2020 (6% of the total number of irregularities reported in 2020 and 3% of the related amounts).

In summary, Member States made a significant contribution to the EU’s pandemic response in 2020. Customs authorities adjusted their customs controls strategies; anti-fraud services in several Member States generated new impulses and effectively countered fraud in the context of the COVID-19 crisis. This maintained the overall protection of the EU’s financial interests in 2020 at a level similar to previous years, while ensuring smooth and unhampered trade flows for EU citizens and businesses.

2.1.Introduction

The technical explanations and the statistical approach are explained in the accompanying document 'Methodology regarding the statistical evaluation of reported irregularities for 2015' 3 . In summary, the following statistics are prepared based on the total established and estimated amount of traditional own resources (TOR) as reported in OWNRES 4 . Figures on recovery are based only on established amounts.

To make it easier to compare results with previous years, the analysis for 2020 is based on the figures obtained for the EU of 27 Member States plus the UK 5 .

The following analysis is based on the data available on the cut-off date (15 March 2021). This analysis aims to provide an overview of the cases of fraud and irregularities reported for 2020 together with their financial impact.

2.2.General analysis – Trend analysis

2.2.1.Reporting years 2016-2020

The number of cases reported via OWNRES for 2020 is 4 454. This is roughly 9% lower than the average number of irregular cases reported each year for the 2016-2020 period (4 897).

The total estimated and established amount of TOR involved for 2020 is EUR 490 million. This is roughly 5 % lower than the average estimated and established amount for each year in 2016-2020 (EUR 516 million).

In 2020, five large 6 cases with a combined amount of about EUR 67 million  7 were reported. These five cases had a significant effect on the total estimated and established amount. In 2019, there were only three large cases with a combined amount of about EUR 70 million that affected the total estimated and established amount. Cyprus and Luxembourg did not communicate any case exceeding EUR 10 000.

CHART TOR1: Total number of OWNRES cases and the related estimated and established amount (2016-2020)

Annex 1 of the summary tables shows the situation on the cut-off date (15 March 2021) for the years 2016-2020.

2.2.1.1. Irregularities reported as fraudulent

The number of cases reported as fraudulent registered in OWNRES for 2020 (451) is currently 9% lower than the average number of cases reported each year for 2016-2020 (498).

The total estimated and established amount of TOR involved (EUR 108 million) in 2020 is 6% greater than the average estimated and established amount for each year in 2016-2020 (EUR 102 million).

For 2020, Czechia, Cyprus, Luxembourg, and Malta did not communicate any fraudulent case exceeding EUR 10 000.

CHART TOR2: OWNRES cases reported as fraudulent and the related estimated and established amount (2016-2020)

On the cut-off date (15 March 2021), 10 % of all cases detected in 2020 were classified as fraudulent. This is slightly more than in 2019 (9 %).

Annex 2 of the summary tables shows the situation on the cut-off date for 2016-2020.

2.2.1.2. Irregularities reported as non-fraudulent

At the same time, the number of cases reported as non-fraudulent communicated via OWNRES for 2020 (4 003) was 9% lower than the average number reported each year in 2016-2020 (4 399).

The total estimated and established amount of TOR (EUR 382 million) was 8% lower than the average estimated and established amount for each year in 2016-2020 (EUR 414 million).

Bulgaria, Cyprus and Luxembourg did not report any case of irregularity exceeding EUR 10 000 for 2020.

CHART TOR3: OWNRES cases reported as non-fraudulent and the related estimated and established amount (2016-2020)

Annex 3 of the summary tables shows the situation on the cut-off date for 2016-2020.

2.2.2.OWNRES data vs TOR collection 

In 2020, the total established amount of TOR (gross) was EUR 25 billion. Roughly 99% of this was duly recovered and made available to the Commission via the A-account. According to the OWNRES data, around EUR 490 million has been established or estimated by the Member States in connection with cases reported as irregular (fraudulent/non-fraudulent) where the amount at stake exceeds EUR 10 000.

The total estimated and established amount reported in OWNRES represents 1.97% of the total collected TOR (gross) amount in 2020 8 . This so-called detection rate has increased compared with 2019 when it was 1.79% 9 . A percentage of 1.97 % indicates that, out of every EUR 100 of TOR (gross) established and collected, EUR 1.97 is registered as irregular (fraudulent or non-fraudulent) in OWNRES. There are differences in this percentage among the Member States. In 14 Member States 10 and the UK, the percentage is above the average of 1.97 %. The highest percentage for 2020 can be seen in Hungary, Bulgaria, Lithuania and Croatia with 7.82%, 5.52% 4.16% and 3.61% respectively.

Seven 11 Member States and the UK established and made available most of the TOR amounts. For these seven Member States and the UK, the estimated and established OWNRES amounts was 1.94% of the established TOR for 2020. In comparison with the previous year (1.88%), this represents an increase of 0.06 percentage points. For the Netherlands, estimated and established OWNRES amounts as a percentage of established TOR decreased from 2.87% in 2019 to 0.79% in 2020. For Italy and the UK, it fell by 0.24 percentage points and 0.08 percentage points respectively. For the other five Member States 12 , the estimated and established OWNRES amounts as a percentage of established TOR increased from 1.74% in 2019 to 2.53 in 2020.

TOR MAP1: Showing the percentage of estimated and established amount in OWNRES of established TOR for 2020

2.2.2.1. Detection rates in the COVID-19 year of 2020

A year like no other before, 2020 was marked by the COVID-19 pandemic and a related sharp decrease in import flows. Trade within the EU of 27 13 Member States was hit hard. Imports fell significantly compared with 2019 (down 11.6%) 14 . The decrease in import volume and a significant shift towards e-commerce caused by the pandemic led to changes in the number of customs declarations to be cleared. It also led to a shift in customs workload and work patterns. The reaction of the national authorities to these challenges, and the speed with which the customs authorities were able to adapt to new circumstances, are only partially comparable. This is because the differences in lockdown rules between the Member States - and sometimes due to differences within specific regions of the same Member State.

Based on the overall figures, it seems however that the variation of the total number of cases reported as fraudulent or non-fraudulent and of the related amounts is rather within the usual range of the annual fluctuation 15 and, thus, not especially effected by the pandemic. However, the burden of the pandemic has hit Member States with different intensity.

Chart TOR4 shows the variation in the annual detection rate 16 by Member State in 2016-2020. It underlines that not all Member State customs authorities suffered in the same way from the COVID-19 pandemic. The 2020 detection rates 17 in Belgium, Bulgaria, Germany, Croatia, Hungary, Poland, Slovenia and Sweden were higher than these countries had achieved in previous 4 years. However, the detection rates in Italy, the Netherlands, Austria, Portugal and Slovakia were lower than they had achieved in any of the previous 4 years 18 .

Chart TOR4: Detection rates 2016-2020 by Member State and the UK

2.2.3.Recovery

The fraud and irregularity cases detected in 2020 were for an established amount of EUR 461 million 19 . Nearly EUR 296 million of this was recovered in cases where an irregularity was at stake, and EUR 32 million was recovered in fraudulent cases 20 . In total, EUR 328 million was recovered by all Member States for all cases detected in 2020. In absolute terms, Germany recovered the most in 2020 (EUR 144 million) followed by the UK (EUR 50 million) and Spain (EUR 35 million). The recovered amounts point out to fruitful recovery procedures in 2020 by Member States. Analysis shows that lengthy recovery procedures spread over several years are usually required due to administrative and judicial procedures in complex cases or cases with a large financial impact.

In addition, Member States continued their recovery actions for detected cases from previous years.

2.2.3.1. Recovery rates

Over the past 5 years, the annual recovery rate has varied between 52% and 71% (see CHART TOR5). The recovery rate for cases reported in 2020 is currently 71% 21 . In other words, out of every EUR 10 000 of duties established and reported for 2020 in OWNRES as irregular/fraudulent, approximately EUR 7 100 has already been paid.

CHART TOR5: Annual recovery rates (2016-2020)

The overall recovery rate is a correlation between the detection rate, the established amount, and the current recovery stage of individual cases (large, additional-duty claims are more frequently associated with long-lasting administrative and criminal procedures).

Recovery rates vary among the Member States. In 4 Member States, the entire established amount has already been recovered 22 , and in another 6 Member States, the recovery rates are above 90% (Denmark at 95%, Croatia at 94%, Germany at 93%, Sweden at 92%, Spain at 91% and Lithuania at 91%). Differences in recovery results may arise from factors such as the type of fraud or irregularity, or the type of debtor involved. Because recovery is ongoing, it can be expected that the recovery rate for 2020 will also increase in the future.

On the cut-off date (15 March 2021), the overall recovery rate for 1989-2020 was 64%.

2.3.Specific analysis

2.3.1.Irregularities reported as fraudulent

2.3.1.1. Categories of irregularities

A breakdown by types of fraud reveals that most fraudulent cases in 2020 were for incorrect declarations (incorrect classification, value, country of origin or use of preferential arrangements) and formal shortcomings (e.g. failure to comply with the customs procedures). Smuggling was the second most common fraud mechanism in 2020.

23 24 In 2020, the customs procedure ‘release for free circulation’ remained the procedure most vulnerable to fraud (accounting for 74% of cases and 85% of the estimated and established amount). The category ‘other’ accounted for 12% of all cases reported as fraudulent and 6% of all estimated and established amounts in OWNRES registered as fraudulent for 2020. The customs warehouse procedure was involved in 11% of all cases reported as fraudulent and 4% of all estimated and established amounts in OWNRES cases registered as fraudulent for 2020.

Of all cases reported as fraudulent, about 80% concerned goods such as: tobacco; textiles and footwear; vehicles; electrical machinery and equipment; sugar; and articles of iron, steel and aluminium. In monetary terms, those groups of goods accounted for about 80% of all amounts estimated and established for cases reported as fraudulent. China, Thailand, Belarus, the United States, Bangladesh and Uruguay are the largest - in monetary terms - reported countries of origin of goods affected by fraud.

2.3.1.2. Method of detection of fraudulent irregularities

In 2020 25 , inspections by anti-fraud services was the most successful method of detecting fraudulent cases. These inspections uncovered 50% of the fraudulent cases. The next most successful methods were post-release controls (which uncovered 22% of fraudulent cases) and customs controls carried out at the time of releasing of goods (which uncovered 22% of all fraudulent cases).

CHART TOR6: Method of detection 2020 – Cases reported as fraudulent – by number of cases

In monetary terms, of the EUR 108 million estimated or established in fraudulent cases registered for 2020, around 75% was discovered during an inspection by anti-fraud services, 11% was discovered during a post-release control, and 9% during a control at the time of release of the goods.

CHART TOR7: Method of detection 2020 – Cases reported as fraudulent – by estimated and established amount

In nine Member States, more than 50% of all estimated and established amounts in fraudulent cases were detected by anti-fraud services 26 . Controls at the time of release of goods were the most significant method (in that these controls detected the largest amounts) for detecting fraudulent instances in Denmark, Estonia, Greece, Croatia, Latvia, Slovakia, Finland and the United Kingdom. Post-release controls were the most significant method (in that these controls detected the largest amounts) in Bulgaria, Hungary, the Netherlands and Sweden.

In Spain, 76% of all estimated and established amounts in fraudulent cases were detected by a tax audit. In Austria, 86% of all estimated and established amounts in fraudulent cases were detected during an audit of the accounts. In Poland, all types of controls were used but no single type was predominant in monetary terms.

2.3.1.3. Smuggled cigarettes

In 2020, 124 cases of smuggled cigarettes were registered (CN code 27 24 02 20 90) involving an estimated TOR of around EUR 21 million. In 2019, 132 cases of smuggled cigarettes were registered, totalling around EUR 14 million.

The greatest number of cases was reported by Lithuania (39), Belgium (15), Greece (13) and Latvia (11). The largest amount was reported by Belgium (EUR 10 million). No cases were reported by 15 Member States 28 .

Table TOR1: Cases of smuggled cigarettes in 2020

2.3.1.4. Textiles

In monetary terms, textiles were the goods most vulnerable to fraudulent irregularities in 2020. In total, 67 cases were reported, amounting to EUR 27 million. Undervaluation was the main type of irregularity. France, Bulgaria and Belgium were particularly affected by fraud, and seven other Member States were only marginally affected. Most of the cases were detected by anti-fraud services.

2.3.1.5. Irregularities reported as fraudulent by amount 

In 2020, the estimated and established amount was below EUR 100 000 in 323 cases reported as fraudulent (72% of all fraud cases), whereas it was above EUR 100 000 in 128 cases (28%).

The total estimated and established amount in cases reported as fraudulent, where the amount at stake was above EUR 100 000, amounted to EUR 97 million in 2020 (90% of the total estimated and established amount for cases reported as fraudulent).

Table TOR2: Cases reported as fraudulent by amount category in 2020

2.3.2.Irregularities reported as non-fraudulent

2.3.2.1. Categories of irregularities

A breakdown of irregularities by mechanism type reveals that most cases reported as non-fraudulent relate to undervaluation. Incorrect use of preferential arrangements, incorrect origin/country of dispatching, or incorrect classification are also frequently mentioned.

Not all customs procedures are equally susceptible to irregularities. The vulnerability of a procedure may change over the course of time, as certain economic sectors become a target for fraud or unintentional irregularities occur. The customs procedure ‘release for free circulation’ is the customs procedure mostly affected by irregularities. This is because non-compliance in the customs declaration at the time of release for free circulation may be due to any one of many irregularities, e.g. to the tariff, CN code, (preferential) origin, incorrect value, etc. However, in customs suspension regimes (where the payment of duties is suspended, like in warehousing, transit, inward processing, etc.) the sole irregularity that can occur is the removal of the goods from customs supervision. It is therefore normal, and indeed to be expected, that most fraud and irregularities are reported in connection with the procedure ‘release for free circulation’.

In 2020, most of the estimated and established amounts in OWNRES for cases reported as non-fraudulent related to the customs procedure ‘release for free circulation’ (88%) 29 . In all, 10% of all amounts estimated or established in cases reported as non-fraudulent in 2020 involved inward processing. Other customs procedures were only marginally involved in cases reported as non-fraudulent in 2020.

Of all cases reported as non-fraudulent, about 67% concerned textiles; electrical machinery and equipment; vehicles; plastics; footwear; mechanical machinery and appliances; articles of iron and steel; preparation of foodstuffs; organic chemicals; and chemical products. In monetary terms, those groups of goods accounted for about 80% of all amounts estimated or established for cases reported as non-fraudulent. China, the United States, India, Taiwan Japan, Russia, Turkey and Brazil are the most significant reported countries of origin of goods affected by irregularities.

2.3.2.2. Method for detecting non-fraudulent irregularities

In 2020, most non-fraudulent cases (50%) were revealed during post-release customs controls. Other detection methods for non-fraudulent cases that featured frequently were voluntary admission (20% of detected non-fraudulent cases), release controls (17%), tax audits (7%), and inspections by anti-fraud services (5%). 30

CHART TOR8: Method of detection 2020 – Cases reported as non-fraudulent – by number of cases

On the estimated or established amounts, around 43% of all irregularity cases registered for 2020 were discovered during a post-release control, 29% were discovered during a tax audit, 13% were uncovered due to voluntary admission, 9% were uncovered during a control at the time of releasing the goods, and 6 % were found during an inspection by anti-fraud services.

CHART TOR9: Method of detection 2020 – Cases reported as non-fraudulent – by estimated and established amounts

In 12 Member States and the UK, more than 50% of the monetary amounts detected in all non-fraudulent cases were detected by post-release controls 31 . In Belgium, Portugal and Finland, more than 50% of the monetary amounts detected in non-fraudulent cases were detected by release controls. In Estonia, Ireland, Greece, Italy and Romania, more than 50% of the amounts in non-fraudulent cases were detected by anti-fraud services. In Germany, 63% of all amounts reported in non-fraudulent cases were found during a tax audit.

In 14 Member States 32 and the UK, voluntary admission was referred to as a method of detection for some cases reported as non-fraudulent. Significant amounts were reported by the UK (EUR 25 million) and Germany (EUR 16 million) as having been detected by voluntary admission.

2.3.2.3. Shoes are vulnerable to irregularities 

In 2020, shoes were the category of goods most vulnerable to non-fraudulent irregularities in monetary terms. About 25 % (EUR 96 million) of the total amount that was established in non-fraudulent irregularities concerned shoes. Out of a total of 17 Member States and the UK, Germany reported the most cases of irregularities from shoes (99 cases totalling to EUR 87 million). Incorrect value was the prevailing type of irregularity. Tax audits were the type of check that most frequently led to the discovery that licence fees had not been added to the declared customs value.

2.3.2.4. Irregularities reported as non-fraudulent by amount

In 2020, the estimated and established amount was below EUR 100 000 in 3 483 non-fraudulent cases (87% of all cases of irregularity), whereas it was above EUR 100 000 in 520 cases (13%).

The total estimated and established amount in non-fraudulent cases where the amount at stake was above EUR 100 000 amounted to EUR 293 million (77% of the total estimated and established amount for non-fraudulent cases).

Table TOR3: Cases reported as non-fraudulent by amount category in 2020

2.3.3.Fraudulent and non-fraudulent irregularities and goods related to COVID-19

In 2020, there was a sharp increase in trade in goods related to COVID-19 33 . Imports of protective garments and oxygen equipment grew by 40% in 2020 compared to 2019. Imports of diagnostic testing equipment and sterilisation products increased by almost 20% compared to 2019. Imports of other medical goods, such as medical devices, rose by 5%.

However, analysis of these categories of goods 34 over 2016-2020 shows that there were no significant changes in irregularities reported for 2020 compared to previous years. The impact of irregularities affecting goods needed to address the COVID-19 pandemic is typically low and remained relatively low in 2020 (6% of irregularities reported in 2020 and 3% of the related amounts).

CHART TOR10: Cases related to COVID-19 goods reported as irregular and the related estimated and established amount (2016-2020)

In total, 270 cases amounting to EUR 16.6 million were reported by 17 Member States and the UK. Germany and the UK reported the most cases and the largest related amounts. The predominant types of irregularity were incorrect classification and incorrect value.

A slight increase in the amounts reported as irregular was observed in 2020, in particular for such goods as protective garments (gloves, boot covers, overshoes etc.), monitors and other medical equipment.

CHART TOR11: Cases related to COVID-19 goods reported as irregular and the related estimated and established amount (2016-2020)

2.4.Member States’ activities

2.4.1.Classification of irregularities as fraudulent and non-fraudulent and related rates

For 2020, Member States reported 451 cases as fraudulent out a total of 4 454 cases reported via OWNRES. This indicates a fraud frequency level (FFL) of 10%. The differences between Member States are relatively large. In 2020, 11 Member States categorised between 10-50% of their national cases as fraudulent. However, Czechia, Cyprus, Luxembourg and Malta did not categorise any of their national cases as fraudulent. 35 Eight Member States and the UK categorised less than 10% of their national cases as fraudulent. 36 Four Member States registered more than 50% 37 of their national cases as fraudulent.

In 2020, the total estimated and established amount affected by fraud in the EU was EUR 108 million, and the overall incidence of fraud 38 was 0.43%. For 2020, the highest percentages can be seen in Bulgaria (5.52%), Lithuania (3.44%) and Croatia (2.59%). 39  

The total estimated and established amount affected by cases reported as non-fraudulent was more than EUR 382 million. This indicates an irregularity incidence 40 of 1.54%. The highest percentages for irregularity incidence can be seen in Hungary (7.74%), Germany (3.05%), Finland (2.21%), the UK (2.15 %) and Spain (2.13%). 41

There are large differences between Member States’ classifications. These differences may partly be the result of different Member-State classification practices. This can influence comparisons of the amounts involved in cases reported as fraudulent and as non-fraudulent by Member States. Moreover, larger individual cases detected in a specific year may affect annual rates significantly. The rates can also be significantly influenced by factors such as: the type of traffic; type of trade; the level of compliance by businesses; and the location of the Member State. Bearing in mind these variable factors, the rates of incidence can also be affected by the way a Member State’s customs control strategy is set up to target risky imports and to detect TOR-related fraud and irregularities.

2.4.2.Recovery rates

2.4.2.1. Irregularities reported as fraudulent

In 1989-2020, OWNRES shows that, on average, 20% of the initially established amount was corrected (cancelled). The recovery rate (RR) for all years (1989-2020) is 39% 42 . The RR for cases reported as fraudulent and detected in 2020 was 37 % 43 , which is the lowest annual rate for fraudulent cases reported in the last 5 years. The RR for cases reported as fraudulent is in general much lower than that for cases reported as non-fraudulent.

2.4.2.2. Irregularities reported as non-fraudulent

OWNRES shows that, on the cut-off date, on average 34% (1989-2020) of the initially established amount in relation to cases reported as non-fraudulent had been corrected (cancelled) since 1989. The RR for non-fraudulent cases reported for 2020 is 79% 44 . On the cut-off date, the annual RR for the last 5 years varied between 55% and 79%. The overall RR for all years (1989-2020) for all cases reported as non-fraudulent is 74%. 45  

2.4.2.3. Historical recovery rate (HRR)

The HRR 46 confirms that, in the long term, recovery in cases reported as fraudulent is generally much less successful than in cases reported as non-fraudulent (see Table TOR4). Classification of a case as fraudulent is thus a strong indicator for forecasting short- and long-term recovery results.

Table TOR4: HRR

2.4.3.Commission’s monitoring

2.4.3.1. Examination of the write-off reports

In 2020, 21 new write-off reports were submitted to the Commission by eight Member States. The Commission assessed 153 cases totalling EUR 76 million in 2020. In 74 of these cases, amounting to EUR 46 million 47 , the Commission’s view was that the Member States did not demonstrate satisfactorily that the TOR was lost for reasons not imputable to them, so the Member States were considered financially responsible for the loss. In addition, late payment interest totalling to EUR 35 million is due.

Examination of Member States’ diligence in write-off cases is a very effective mechanism for gauging their activity in recovering money. It encourages national administrations to increase the regularity, efficiency and effectiveness of their recovery activity, since lack of diligence in recovery means individual Member States must foot the bill.

2.4.3.2. Commission’s inspections

In its TOR inspections, the Commission has emphasised Member States’ customs control strategies. The Commission also closely monitors Member-State actions and follow-up on observations made during the inspections.

For 2020, the Commission services performed TOR inspections (either on the ground in Member States or remotely) on: (i) the reliability of the TOR accounting and related statements; (ii) the keeping of the separate (B-) account and (iii) the corrections of the normal (A-) account. Considering the magnitude of the TOR losses at stake, DG BUDG also continued its inspection activities in 2020 on the control strategy for customs value and monitored Member State measures to tackle undervaluation fraud.

Due to the COVID-19 pandemic, the initial planning for TOR inspections had to be constantly adjusted depending on the particular lockdown measures in the Member States. Moreover, to implement the programme at least partially, DG BUDG carried out several inspections remotely. Finally, some inspections planned for 2020 had to be postponed to 2021, and the second annual inspection to some Member States was cancelled.

Nevertheless, the restricted inspections that were carried out made it possible to make some recommendations. There restricted inspections also revealed certain shortcomings, some of which have a potential financial impact. Where the Commission considers that cooperation and progress in tackling outstanding issues are insufficient, it applies corrective measures.

As stated in the 2019 PIF report, such corrective measures were already applied by the Commission against the UK. It calculated the TOR losses from the undervaluation fraud in textile and shoes imported from China via the United Kingdom based on the investigations carried out by OLAF and by DG BUDG as part of its management of own resources. Although those corrective measures are still subject to ongoing Court proceedings 48 , the Commission took further steps in 2020 to quantify the TOR losses that occurred in all Member States and sent them preliminary calculations of potential TOR losses for imports that took place on their territory. In addition, Commission quantified potential TOR losses with regard to the evasion of anti-dumping duties for solar panels and informed the Member States concerned.

Finally, one general conclusion can be drawn from the unprecedented year that was 2020. It became crystal clear that it is now vital to explore all ways to ensure that the Customs Union and Member States’ customs authorities operate at maximal efficiency, remain flexible and resilient in times of crisis and better anticipate problems. This implies, above all, a new emphasis on ensuring greater availability and use of data and data analysis for customs purposes developing an appropriate set of tools to help with foresight and common crisis-management. Further steps are therefore required towards risk assessment at EU level, uniform controls and EU-wide and international coordination/cooperation to detect irregular cases bearing in mind that fraud diversion and spreading of specific fraud mechanisms are not constrained by national borders.

2.4.3.3. Particular cases of Member State failure to recover TOR

If TOR are not established or recovered because of an administrative error by a Member State, the Commission applies the principle of financial liability 49 , making individual Member States responsible for the error. Member States have been held financially liable in 2020 for over EUR 109 million 50 , and new cases are being appropriately followed-up.

3.COMMON AGRICULTURAL POLICY 

Executive summary

Over the period 2016-2020, the level of detection of fraudulent irregularities related to rural development expenditure under the programming period 2014-2020 had a slow start (which might indicate insufficient detection work in the Member States). The level of detection decreased for the programming period 2007-2013, as expected. The level of fraud detected for support to agriculture (including direct aid to farmers and market measures) was stable.

Over the period 2016-2020, the rural development part of the budget was more affected by fraud than support to agriculture, as a proportion of the payments received by the Member States. However, the incidence of fraud for market measures was even higher than for rural development. Direct aid to farmers accounted for most payments, but the incidence of fraud was low, as it is entitlement-based and there are systems in place to support prevention. Similar patterns applied to non-fraudulent irregularities.

Over the past years, the detection of fraud was concentrated in a few Member States and this was not substantiated by a similar level of concentration in related payments. Differences in the quality of prevention or detection work carried out or different approaches taken to criminal investigation may contribute to this.

From 2016-2020, the majority of fraudulent irregularities concerning support to agriculture were related to the use of false documents, such as invoices or lease agreements, or false requests for aid. For example, this includes false information provided about the eligible area and compliance with other conditions for aid. Overdeclaration of products, species or land was also frequently detected. High financial amounts were recorded in several cases, related to the market measure ‘Promotion’ and investigated by OLAF, where conflict of interest was combined with other violations. The creation of artificial conditions for the purpose of receiving financial support is a potential risk. For example, beneficiaries may artificially split agricultural holdings and request aid via several linked companies, to avoid degressive aid rates or limits in terms of area or animals.

In terms of rural development fraud, fraudsters mainly used the practice of falsifying documents. For example, this may involve falsifying invoices, declarations of equipment as new while it is second-hand, bids in procurement procedures, or false information provided on compliance with the conditions for receiving the aid. A significant number of fraudulent irregularities concerned failure to fully implement the action. The creation of artificial conditions is a potential risk also for rural development funding. Concerning non-fraudulent irregularities, the majority were related to the action for which the funding was received, which most often was either not completed, not implemented or delayed.

Over 2016-2020, the highest number of fraudulent irregularities for market measures was found in national support programmes for the wine sector. An analysis has shown that in this domain irregularities are for (i) investment measures; (ii) promotion, especially in non-EU markets; and (iii) restructuring and converting vineyards. The highest total financial amount was found in the fruits and vegetables sector. A recent analysis has shown that fraudulent irregularities have an impact in particular on aid for producer groups for preliminary recognition, especially on investment measures. After the fruits and vegetable sector, the second highest total financial amount involved in fraudulent irregularities concerned the ‘promotion’ sector. An analysis has shown that irregularities concern both EU and non-EU markets.

The capability to detect irregularities and fraud is key to protecting the EU budget. The Commission recommended the Member States to further exploiting the potential of risk analysis and improving the spontaneous reporting of potential irregularities. So far, there has been little improvement on this in the Member States.

After about 10 years from initial reporting, the share of cases of suspected fraud that have not lead to conviction remains very high, while the share of cases in which fraud is established is low. This may signal the need to invest further in reporting suspected fraud and in the investigation/prosecution phase. 

3.1.Introduction

Section 3 presents a statistical evaluation of irregularities and fraud detected by the Member States in 2020 in expenditure under the common agricultural policy (CAP). It provides context to these detections by looking at past years and relevant programming periods (PP).

Over the period 2016-2020, the CAP’s overarching objectives were (i) viable food production; (ii) sustainable management of natural resources and climate action; (iii) balanced territorial development. Over 99% of expenditure was disbursed by Member States under shared management.

For the purpose of this analysis, the CAP is split into two main parts:

oSupport to agriculture (SA), by providing direct aid to farmers (DA) and measures to respond to market disturbances (MM), such as private or public storage and export refunds. The European Agricultural Guarantee Fund (EAGF) finances these actions.

oRural development (RD) programmes run by the Member States. The European Agricultural Fund for Rural Development (EAFRD) finances these programmes.

The European Maritime and Fisheries Fund (EMFF) provides funding and technical support to make the fishery industry more sustainable. However, EMFF is analysed together with the other structural funds, as it belongs to the ESIF (European Structural and Investment Funds) family of funding (see Section 4). 

Table NR1 shows the 2020 budget for the CAP, which represents about 35% of the EU budget.

Graph NR1 overleaf shows the relative weight of different components of the CAP on payments and on the financial amounts involved in all CAP irregularities.

In 2020, rural development represented 25% of CAP payments, but over 60% of the financial amounts involved in CAP irregularities. This is even more pronounced for market measures, which accounted for 5% of payments and 24% of irregularities in terms of financial amounts.

The opposite applies to direct aid, which absorbs most of the CAP payments (70%), but only accounts for 11-13% of the irregularities in terms of the financial amounts involved.

The European Commission is responsible for managing the EAGF and the EAFRD. However, the Commission does not pay the beneficiaries itself. Under the principle of shared management, this task is delegated to the Member States, who make the payments via national or regional paying agencies. Before these paying agencies can claim any expenditure from the EU budget, they must be accredited on the basis of a set of criteria laid down by the Commission.

Before making payments, these paying agencies must also, either directly or via delegated bodies, ensure that the aid applications are eligible. The checks they must carry out are laid down in the CAP sectorial regulations and vary from one sector to another. Specific national authorities are competent for rural development operations.

The Commission reimburses the Member States the expenditure made by the paying agencies. EAGF reimbursements are made on a quarterly basis and EAFRD on a quarterly basis. Though entitlements and measures supported under the EAGF follow a yearly flow, those under the EAFRD are implemented through multiannual programmes, as action financed by other ESI Funds. In general, reimbursements are subject to possible financial corrections by the Commission, under the clearance of accounts procedures. 

This report is structured as follows. Section 3.2 focuses on general trends, broken down by fraudulent and non-fraudulent irregularities. Section 3.3 details more specific analyses (i) on the types of irregularities; (ii) on the detection rates by CAP component; (iii) on the irregularities affecting market measures; (iv) on the reasons for carrying out the checks that led to the detection of irregularities. Section 3.4 digs into the anti-fraud activities carried out and results obtained by the Member States, including analysing the fraud and irregularity detection rates (the ratio between the amounts involved in cases reported as fraudulent (FDR) or not reported as fraudulent (IDR) and the payments made during the same period of time).

3.2.General analysis

3.2.1.Irregularities reported in the years 2016-2020

The analysis in Section 3 refers to the EU-27, unless specified otherwise. UK data is added in the tables, as specified, to give a complete picture. However, the accompanying analysis focuses on the current Member States and EU-27 in aggregate. In the whole report, when reference is made to ‘fraudulent’ or ‘fraud’, this includes both ‘suspected fraud’ and ‘established fraud’. 51 Member States are requested to communicate irregularities involving financial amounts above EUR 10 000. 52  From 2016-2020, several Member States also reported several irregularities under this threshold. However, these cases represented only about 1% and 3% of the number of irregularities reported as non-fraudulent and fraudulent, respectively. To use all information reported by the Member States, they are included in the analysis for this Report. 53

3.2.2.Irregularities reported as fraudulent

Table NR2 provides an overview of the number of irregularities reported as fraudulent by the Member States, broken down by the type of support, from 2016-2020. 54  The number of irregularities found in rural development spending fell sharply in 2017 and started rising again in 2020. The irregularities found under support to agriculture were rather stable.

The irregularities in rural development expenditure reported from 2016-2020 concerned both PP 2007-2013 and PP 2014-2020. Table NR3 shows the sharp fall in 2017 in the number of rural development cases related to PP 2007-2013, which was to be expected, given that the PP closed in 2015. The slow start of detections related to PP 2014-2020 did not compensate for the drop in 2017. Since then, there have not been remarkable shifts in the number of fraudulent irregularities detected. Table NR4 shows the trends in terms of the financial amounts involved.

For PP 2014-2020, the slow start should be closely monitored to ensure it is not due to less of a focus on fraud detection. From 2009-2013, detections related to PP 2000-2006 (closed) and to PP 2007-2013 (at that time, under implementation) were overlapping, similar to what is happening now for detections related to PP 2007-2013 and PP 2014-2020. Table NR3 confirms that, during the first seven years of implementation, the management and control systems for PP 2014-2020 have detected far fewer fraudulent irregularities than those for PP 2007-2013 (in 2009-2013). This also applies to the financial amounts involved (Table NR4).

As shown in Table NR2, several irregularities were classified SA/RD, meaning that they were related to both components of the CAP. Basically, in all of these irregularities, irregularities in rural development expenditure were found in combination with irregularities in direct aid to farmers.

The detection of fraudulent irregularities was concentrated in a few Member States. From 2016-2020, the irregularities notified by the top five Member States in terms of cases reported (Romania, Poland, Italy, Bulgaria France) represented about 75% of all irregularities reported as fraudulent (80% of financial amounts). In 2020, this rose to 84%.

A deeper analysis of concentration was included in the 2018 PIF Report. 55 That analysis found that the concentration of detections went beyond what could be expected given the level of concentration of payments. This could be due to many different factors, including different underlying levels of irregularities and fraud, differences in the quality of the prevention or detection work or different practices at the stage of the procedure when potentially fraudulent irregularities are reported. The concentration of detections was more accentuated for fraudulent rather than for non-fraudulent irregularities. This suggests that different approaches to criminal investigation and prosecution could be an additional and significant factor giving rise to these different levels of detection across the Member States.

Table NR5 shows the trend of financial amounts involved in irregularities reported as fraudulent. 56 For rural development irregularities, similar to the trend in terms of number of detections, the financial amounts involved fell in 2017 and began rising again in 2020. The trend in the financial amounts involved in support to agriculture was heavily influenced by two cases concerning market measures, worth between EUR 20 and 30 million each, which Poland detected in 2017 and 2018. This is the reason for the significant increase found over these two years. Excluding these two irregularities, the irregular financial amounts detected in relation to support to agriculture were rather stable, reaching a record low in 2020.

Over the period 2016-2020, 50% of the irregular financial amounts involved were in support to agriculture irregularities, and 48% were for rural development irregularities. However, over the same period, rural development payments represented just 23% of the CAP budget. Therefore, rural development expenditure was more affected by fraud than support to agriculture expenditure. This is analysed further in Section 3.3.2., through the fraud detection rate, distinguishing between direct aid to farmers and market measures.

An analysis covering the period 2015-2019, included in the 2019 PIF Report 57 , shows that in most fraudulent irregularities, the ‘persons involved’ 58 were legal entities. Most of them were private companies, followed by non-profit organisations, in particular associations. For a significant one third of cases, the ‘persons involved’ were natural persons. Most of the fraudulent irregularities involved a single entity.

3.2.3. Irregularities not reported as fraudulent

The number of rural development irregularities not reported as fraudulent increased constantly until 2015, in line with implementation of the programmes, while the number of irregularities related to support to agriculture remained stable. Since then, rural development non-fraudulent irregularites fell sharply until 2017 and then stabilised. (see Table NR6). 

The irregular financial amounts linked to rural development also peaked in 2015, then started to fall, a trend that accelerated in 2019 (see Table NR7). The irregular financial amounts linked to support to agriculture fluctuated strongly around an annual average of about EUR 70 million. This was mainly due to the fact that cases involving over EUR 10 million each were reported in 2017 (one case in Romania) and 2019 (two cases in Poland), but none were detected in 2016, 2018 and 2020. 

The number of non-fraudulent irregularities in spending on rural development regularly and significantly exceeded the number on support to agriculture, over the entire 2016-2020 period. As a result, the number of irregularities linked to rural development were over double the number affecting support to agriculture. Rural development non-fradulent irregularities also exceeded those in support to agriculture in terms of the financial amounts involved, but only by 46%.

Irregularities in rural development spending were found in both PP 2007-2013 and PP 2014-2020. Table NR8 shows the sharp fall from 2016 to 2019 in the number of rural development cases related to PP 2007-2013, which was to be expected, considering that this PP closed in 2015. The slow start of detections related to PP 2014-2020 did not compensate for this drop. The rebound in 2020 was due to both an increase in irregularities still related to PP 2007-2013 and the sharpest rise in irregularities related to PP 2014-2020 since its start. Table NR9 shows the trend in terms of the financial amounts involved.

For PP 2014-2020, the slow start is in line with the situation at the start of the previous programming period. Over the period 2009-2013, irregularities detected in rural development spending related to PP 2000-2006 (closed) and to PP 2007-2013 (at that time, under implementation) overlapped, similar to what is happening now for detections related to PP 2007-2013 and PP 2014-2020. Table NR8 confirms that, during the first seven years of implementation, the management and control systems for PP 2014-2020 detected a number of irregularities in rural development spending that is similar (-9%) to what the systems for PP 2007-2013 achieved during the seven first years of implementing of that PP (during 2009-2013). In terms of financial amounts, the gap was more significant (-25%), but these fluctuations should not be overemphasised, as they are often due to few cases with high amounts involved.

As shown in Table NR6, several irregularities were classified as SA/RD, meaning that they were related to both components of the CAP. In most of these cases, irregularities in rural development spending were combined with infringements concerning direct aid to farmers.

3.3.Specific analysis

3.3.1.Modus operandi

3.3.1.1. Support to agriculture

Table NR10 provides an overview of the most frequent categories (or combinations of categories) of irregularities linked to cases reported as fraudulent in relation to support to agriculture in 2020 and the financial amounts involved. It also gives the figures for these categories (or combinations of categories) over the period 2016-2020. 59 In the following paragraphs, the adjective ‘pure’ is used to refer to cases where a specific category of irregularity is not combined with other categories.

The irregularities reported in 2020 mainly concerned the documentary proof. Over the whole period 2016-2020, irregularities concerning the request were also prevalent. Further analysis shows that, in most cases, it was due to false documentary proof or false requests. A wide range of documents can be falsified, such as invoices, lease agreements and property documents, and certifications of compliance with the conditionality requirements. Requests for aid could include false information about the eligible area, compliance with other conditions for aid, etc.

Over the period 2016-2020, the Member States detected few fraudulent cases of ‘pure’ ‘(non) action’, but these cases accounted for the second highest financial amount involved. Irregularities in the category ‘pure’ 'product, species and/or land' were more frequently detected, mostly for 'overdeclaration and/or declaration of fictitious product, species and/or land'.

Although there were no such cases in 2020, over the whole period 2016-2020, 28 irregularities were reported in the category ‘pure’ 'ethics and integrity'. All of these irregularities were communicated by Poland and were not reported under the types 'conflict of interest', 'bribery' or 'corruption', but as 'other irregularities concerning ethics and integrity'. Most concerned the creation of artificial conditions for receiving financial support. For example, beneficiaries may artificially split agricultural holdings and request aid through several linked companies, to avoid degressive aid rates or limits in terms of area or animals. Other Member States may have reported this type of infringement under other categories.

High average financial amounts (about EUR 1.8 million) were recorded in several cases of conflict of interest combined with other violations (8 irregularities). In 2019, Czechia reported two irregularities related to corruption, in combination with public procurement infringements (conflict of interest) and failure to implement the action. In five irregularities reported by Bulgaria in 2018, conflict of interest was combined with violations concerning the ‘beneficiary’ (mostly not having the required quality) and ‘(non) action’ (infringements relating to the cofinancing system). In another case detected in Bulgaria, a conflict of interest was combined with violations concerning the ‘beneficiary’ (not having the required quality) and ‘accounts & records’ (revenues not declared). All of these eight irregularities were related to the market measure ‘promotion’ (see Section 3.3.3) and were investigated by OLAF. The investigations uncovered a complex fraudulent scheme, mainly based on price inflation, kickback payments and money laundering. The public procurement procedures were breached through a solid network of companies based in different countries. In some cases, the manipulation was possible also due to the collusion of the beneficiaries.

Table NR11 provides an overview of the most frequent categories (or combinations of categories) of irregularities linked to cases not reported as fraudulent in support to agriculture expenditure in 2020 and the financial amounts involved. It also gives the total for these categories (or combinations of categories) for the period 2016-2020.

Irregularities due only to the 'request' (pure) were by far the most recurrent category. More specifically, during 2016-2020, the most recurrent type of violation by far was 'false or falsified request for aid', followed by 'incorrect or incomplete request for aid' and 'product, species, project and/or activity not eligible for aid'. This rate of irregularities related to falsification would not be expected for non-fraudulent irregularities. Similar findings apply to the category ‘documentary proof’. Violations concerning the category 'documentary proof' were also quite frequent. Most of the times, from 2016-2020, these irregularities concerned missing, incomplete or incorrect documents. However, they also related to the type of violation 'false or falsified documents'. This mostly happened in the past; no such case were reported in 2020.

The highest irregular financial amounts were due to infringements concerning ‘(non) action’. Nearly 30% of the irregular financial amounts reported over the period 2016-2020 for ‘(non) action’ were due to two irregularities totalling about EUR 36 million. In this category, the three most reported types of violations concerned the action itself (not implemented or not completed), and 'refusal to repay not spent or unduly paid amounts'.

Other prevalent categories of irregularities in support to agriculture expenditure not reported as fraudulent were related to 'product, species and/or land', 'beneficiary' or 'ethics and integrity' (not combined with other categories of irregularity). For pure 'product, species and/or land', most violations concerned 'overdeclaration and/or declaration of fictitious product, species and/or land'. In the category pure 'beneficiary', the most reported type of violation was 'operator/beneficiary not having the required quality'. Infringements related to 'ethics and integrity' were less frequent than for the irregularities reported as fraudulent. Apart from one case of conflict of interest 60 , all of these violations were reported as 'other irregularities concerning ethics and integrity'.

3.3.1.2. Rural development

Table NR14 provides an overview of the most frequent categories of irregularities reported as fraudulent in rural development expenditure in 2020 and the corresponding financial amounts. It also gives the total for these categories over the period 2016-2020.

Similar to the findings for support to agriculture, there were mainly cases of ‘pure’ falsification of the documentary proof or, to a lesser extent, of requests for aid. Falsification may concern, for example, invoices, declarations of equipment as new while it is second-hand, bids in the context of procurement, and information on compliance with conditions for receiving the aid. The pure category 'documentary proof' was by far the most reported, with 'false or falsified documents' as the most reported type of violation. The category pure 'request' was another frequent category, with the violation 'false or falsified request of aid' being the most reported.

A significant number of detections and irregular financial amounts were related to pure '(non) action'. Under this category, from 2016-2020, the most reported type of violation was 'action not implemented’.

The category pure ‘ethics and integrity’ ranked high, with 83 irregularities found, but none reported in 2019 or 2020. Only one irregularity was reported as corruption 61 . Similar to support to agriculture cases, Poland communicated most of these violations and they were not reported under the types 'conflict of interest', 'bribery' or 'corruption', but as 'other irregularities concerning ethics and integrity'. Most of these violations concerned the creation of artificial conditions for receiving financial support. Other Member States may have reported this type of infringement under other categories of irregularity, such as the one referring to the beneficiary (for example, using the the type of violation 'operator/beneficiary not having the required quality' or ‘other’).

Table NR13 provides an overview of the most frequent categories of irregularities not reported as fraudulent in rural development expenditure in 2020 and the corresponding financial amounts. It also gives the total for these categories over the period 2016-2020.

The highest number of detections and irregular financial amounts were related to pure '(non) action'. This included ‘action not completed’, ‘action not implemented’, or ‘failure to respect deadlines’ among the most reported types of violation.

Violations concerning 'documentary proof' alone (pure) or the ‘beneficiary’ were also prevalent. They were also often combined with the category ‘(non) action’ and with each other.

Over the period 2016-2020, the number of infringements related to 'documentary proof'' followed that of infringements concerning ‘(non) action'. 'Documents missing and/or not provided' was the most reported type of violation. However, from 2016-2020, 'false and/or falsified documents' were reported in a number of cases (about 50), which would not be expected for non-fraudulent irregularities. The same applies to the category 'request', with a number of cases (about 20) reported in the 'false or falsified request of aid' type. 

The category pure ‘beneficiary’ was the third most frequent from 2016-2020 and the fourth in 2020. 'Operator/beneficiary not having the required quality' was the most reported type of violation.

In 2020, there was a sharp increase in the detection of violations concerning ‘product, species and/or land’, mostly due to 'over declaration and/or declaration of fictitious product, species and/or land'.

There were just a few reported cases of conflict of interest. There was one pure case of conflict of interest and two additional cases of conflict of interest in combination with public procurement infringements. In addition, there were eight other cases of conflict of interest in the public procurement procedure. In 2020, one Member State reported a multi-million irregularity in rural development expenditure related to conflict of interest, corruption, use of false documents and accounts. Reporting as non-fraudulent would not be expected, but the Member State also communicated that penal proceedings were ongoing. Apart from these cases, infringements related to 'ethics and integrity' were reported as 'other irregularities concerning ethics and integrity'.

3.3.2.Fraud and Irregularity Detection Rates (FDR and IDR) by CAP components

Table NR14 shows the FDR and IDR per type of policy measure. 62  

Detection rates for support to agriculture were much lower than for rural development. However, one part of support to agriculture, interventions in agricultural markets (market measures), accounted for the highest FDR and IDR. It could be argued that this comparison is biased by a few cases related to market measures (two fraudulent and three non-fraudulent) involving exceptionally high financial amounts (more than EUR 10 million each). However, even excluding these irregularities from the calculation, the FDR and IDR for market measures were the highest, at 0.32% and 1.23%, respectively.

The detection rates for direct payments to farmers were much lower.

3.3.3.Market measures – fraudulent and non-fraudulent irregularities

As shown in Table NR14, the FDR and IDR of market measures are high. Table NR15 shows the number and financial amounts of irregularities reported as fraudulent in relation to market measures for the period 2016-2020, while Table NR16 shows the same data on irregularities that were not reported as fraudulent.

Fraudulent and non-fraudulent irregularities involving the highest financial amounts are often related to market measures. From 2016-2020, the Member States reported two fraudulent irregularities related to aid to producer groups for preliminary recognition in the ‘fruits and vegetables’ sector, accounting for over EUR 20 million each. This type of aid was also subject to two non-fraudulent irregularities, accounting together for over EUR 36 million. Another non-fraudulent irregularity involving about EUR 19 million affected a food programme for deprived persons.

The highest number of irregularities reported as fraudulent was related to national support programmes for the wine sector. A detailed analysis covering 2015-2019, included in the 2019 PIF, shows that in this domain irregularities affect in particular investment measures and promotion, especially in non-EU markets. This analysis also identified the restructuring and conversion of vineyards. For further details, see ‘Statistical evaluation of irregularities reported for 2019: own resources, agriculture, cohesion and fisheries policies, pre-accession and direct expenditure’, SWD(2020)160 final, Section 3.3.3.

Although it ranked first in terms of number of detections, ‘products of the wine-growing sector’ were clearly below those for other products, in terms of the financial amounts involved. This is the case for ‘fruits and vegetables’ and ‘promotion’ (see Table NR15). The analysis included in the 2019 PIF shows that for ‘fruits and vegetables’, irregularities had an impact in particular on ‘aid for producer groups for preliminary recognition’, especially ‘investment’ measures. Concerning the market measure ‘promotion’, according to the analysis included in the 2019 PIF, irregularities affect both the EU and the non-EU markets, but the financial amounts involved in irregularities related to promotion in non-EU countries are higher. For further details, see SWD(2020)160 final, Section 3.3.3.

For irregularities not reported as fraudulent, the category 'products of the wine-growing sector' was the most frequently reported, but 'fruit and vegetables' was the one with the highest financial amounts. The category 'Food programmes' was impacted by few irregularities, but high financial amounts. As mentioned, one single non-fraudulent irregularity accounted for EUR 19 million.

3.3.4.Reasons for carrying out checks

To boost the capability to detect irregularities, the Commission recommended to the Member States to improve risk analysis and the use of spontaneous reporting. Detection capability is a key feature of the anti-fraud cycle, which contributes to the effectiveness and efficiency of the system for the protection of the EU budget. In the 2017 PIF Report, an analysis was made of the reasons for carrying out checks and led to the recommendation to further exploiting the potential of risk analysis. The report also recommended to facilitating and assessing the spontaneous reporting of potential irregularities and strengthening the protection of whistle blowers that are also a crucial source for investigative journalism. 63

So far, there has been little improvement on the ground (see Tables NR17-NR22). The 2017 PIF Report was adopted at the beginning of September 2018 and it may take time to evolve effectively from reactive to proactive detections based on risk analyses. It should also be considered that non-fraudulent irregularities that are detected and corrected at the national level before including the expenditure in a statement submitted to the Commission for reimbursement do not have to be reported in the Irregularity Management System (which is the source for this Report). Therefore, if risk analyses have a higher impact in terms of ‘early’ detection of these irregularities, it would not be captured by Tables NR17-NR22. By contrast, this exception does not apply to fraudulent irregularities, which should always be reported, even when detected before expenditure is submitted to the Commission.

3.3.4.1. Irregularities in relation to rural development

With reference to rural development, there was no increase in the use of risk analysis or in the number of irregularities detected following tips (e.g. from whistle blowers) or information published by media.

With a focus on checks that led to discovering irregularities reported as fraudulent in rural development, Table NR17 provides information on the number of checks that were carried out due to reasons that can be linked to the recommendations mentioned in Section 3.3.4. For the period 2016-2020, it compares the situation before 2018 with the situation in 2018-2020. Over the past three years, Member States have reported the detection of only few irregularities on the basis of risk analysis or similar (‘comparison of data’)  64 or information published by the media. The share of irregularities detected following tips fell from 8% to 3%.

Table NR18 provides the same information for irregularities not reported as fraudulent in rural development. There was a slight increase in the use of risk analysis and possibly similar methods. There were no significant changes in the irregularities reported as a result of tips and media. With specific reference to risk analysis (in the strict sense), no additional Member States started reporting this type of detections. From 2018-2020, detections based on risk analysis (in the strict sense) were made by only seven Member States (over 60% of such detections in Hungary).

3.3.4.2. Irregularities in relation to market measures

With reference to market measures, Table NR19 indicates no increase in the use of risk analysis and in the number of fraudulent irregularities detected following information published by media. The percentage of irregularities detected following tips increased from 4% to 6%, but this was based on few cases.

The categories 'scrutiny 4045' and scrutiny 485' refer to Regulation No 4045/1989 and Regulation No 485/2008, respectively. These deal with the scrutiny of commercial documents of those entities receiving payments from the Guarantee section of the EAGGF (Reg. No 4045/1989) or from the EAGF (Reg. No 485/2008) 65 . Although Reg. No 485/2008 explicitly brought the concept of risk analysis, Reg. No 4045/1989 already required the Member States to consider risk factors and concentrate on sectors or undertakings where the risk of fraud is high. In 2018-2020, the share of fraudulent irregularities the Member States reported on ' scrutiny 4045/scrutiny 485' fell.

Table NR20 provides the same information for irregularities not reported as fraudulent in market measures. Over the past three years, there was a slight increase in the use of risk analysis and possibly similar methods, in line with the findings for rural development (see Section 3.3.4.1). The share of irregularities detected on the basis of 'scrutiny 4045/scrutiny 485' decreased by over eight percentage points. The share of irregularities detected following tips slightly increased, but on the basis of few cases.

3.3.4.3. Irregularities in relation to direct payments

With a focus on checks that led to discovering irregularities reported as fraudulent in direct aid, Table NR21 shows that, apart from a falling share of the irregularities found as a result of tips, the Member States detected just two irregularities on the basis of risk analysis or similar. 

Table NR22 highlights irregularities not reported as fraudulent in direct aid. Over the past three years, there was a slight increase in the use of risk analysis and possibly similar methods; the share of irregularities rose from 3.5% to 4.5%. In particular, only 0.8% of cases were started following a risk analysis (in the strict sense), but there was an increase in ‘comparison of data’ and ‘probability checks’. It is not clear what kind of activity was reported under these reasons. There was no increase in the use of information published in the media, while the use of tips increased as a reason for the irregularities detected (from 2% to over 3%).

3.4.Anti-fraud work carried out by the Member States

Previous sections have examined the trend and main features and characteristics of the irregularities reported as fraudulent.

This section digs into some aspects linked to the anti-fraud work carried out and results obtained by the Member States in particular. It analyses four aspects:

(1)Duration of irregularities (fraudulent and non-fraudulent). No analysis by Member State is presented in this section.

(2)The number of irregularities reported as fraudulent by each Member State (in 2020 and over the past five years).

(3)the FDR (the ratio between the amounts involved in cases reported as fraudulent and the payments made over the same period) and the IDR (the ratio between the amounts involved in cases not reported as fraudulent and the payments made over same period) over the past five years 66 ;

(4)the follow-up to suspected fraud.

3.4.1.Duration of irregularities

The Member States are requested to indicate the date or period when the irregularity was committed. Of the 15 544 irregularities (fraudulent and non-fraudulent) reported by Member States (and the UK) in 2016-2020 in relation to the CAP, 8 836 (57% of the total) involved irregularities that were protracted over a span of time. For the 1 338 irregularities reported as fraudulent, this rises to about 70%. The remaining part of the dataset refers to irregularities which consisted of a single act identifiable on a precise date (about 42% of the whole dataset and 29% of that including only the fraudulent irregularities) or for which no information was provided 67 (7% of the whole dataset, but only 1% of the irregularities reported as fraudulent). The average duration of the irregularities that were protracted over time was 27 months (two years and three months). For the irregularities reported as fraudulent, the average was three month less: 24 months.  

3.4.2.Detection of irregularities reported as fraudulent by Member State

3.4.2.1. Reported over the period 2016-2020

Table NR23 gives an overview of the irregularities reported as fraudulent by the Member States over the period 2016-2020. It also shows the related amounts, overall payments under the agricultural policy 68 and the FDR.

Belgium, Cyprus and Malta have notified no irregularities as fraudulent. 15 other Member States reported fewer than 30 potentially fraudulent irregularities; six Member States reported between 30 and 60; and three Member States reported over 60.

The FDRs exceeded 0.40% in Bulgaria, Estonia and Romania. Romania was the Member State that accounted for the highest number of irregularities, and Poland reported the highest financial amounts involved.

3.4.2.2. Reported in 2020

Table NR24 gives an overview of the irregularities reported as fraudulent in 2020, broken down by Member State. It also shows the related amounts, overall payments for the common agricultural policy and the FDR. 

Ten Member States reported no irregularities as fraudulent. Most Member States reported fewer than 30 fraudulent irregularities; only Romania reported over 30 fraudulent irregularities.

The highest FDRs were recorded in Estonia (1%) and Romania (about 0.5%). Romania reported the highest number of irregularities and related financial amounts.

3.4.3.Fraud and Irregularity Detection by sector and Member State

3.4.3.1. Rural development

Table NR25 and Map NR1 provide an overview of the irregularities reported as fraudulent by the Member States over the period 2016-2020 for rural development expenditure. It also shows the total payments made for rural development and the FDR. As mentioned, the irregularities refer exclusively to the rural development component.

Estonia, Romania, Denmark, and Bulgaria recorded the highest FDR. The FDR was higher than the EU average also in Lithuania, Portugal and Poland. 22 Member States reported fraudulent cases concerning rural development spending over the period 2016-2020. Romania and Poland reported the highest number of cases, and Romania reported the highest financial amounts involved.

In this map, ‘0.00’ indicates low financial amounts involved in the irregularities, in proportion to the payments received.

If no relevant irregularities were reported, no FDR is calculated and the Member State is grey. See Table NR 25.

UK is not included.

Table NR26 and Map NR2 provide an overview of the irregularities not reported as fraudulent by the Member States over the period 2016-2020 concerning rural development expenditure. Table NR26 also shows the total payments for rural development and the IDR.

Bulgaria (4.2%) and Portugal (3%) recorded the highest IDR. The IDR was higher than the EU average also in Romania, Lithuania, Malta, Estonia, Italy, Slovakia, Hungary and Poland. Romania and Portugal reported the highest number of cases, and Romania, Italy and Portugal reported the highest financial amounts involved.

If no relevant irregularities were reported, no FDR is calculated and the Member State is grey. See Table NR 26. UK is not included.

Tables NR25 and NR26 indicate that the reporting of irregularities was concentrated in a few Member States. The top two Member States in terms of number of detections (Romania and Poland) reported 54% of all fraudulent irregularities related to rural development (59% in terms of the financial amounts involved), while they received about 18% of payments. For non-fraudulent irregularities, the top two Member States (Romania and Portugal) reported 32% of cases and 37% of the financial amounts involved, but received about 15% of payments.

The concentration of detections was analysed in detail in the 2018 PIF Report for the period 2014-2018. 69 The analysis suggests that the concentration of detections went beyond what could be expected from the concentration of payments related to rural development among Member States. This could be due to many different factors, including different underlying levels of irregularities and fraud, differences in the quality of prevention or detection work or different practices concerning the stage of the procedure when potentially fraudulent irregularities were reported. This difference in concentration between detections and payments was less pronounced for non-fraudulent irregularities, which could be taken as an indication of more uniform approaches to management and administrative checks, although data on individual Member States highlighted significant discrepancies. The concentration of detections was instead more accentuated for fraudulent irregularities, suggesting that different approaches to criminal investigation and prosecution could be an additional and significant factor explaining the different levels of detection among Member States.

3.4.3.2. Market measures

Table NR27 and Map NR3 provide an overview of the irregularities reported as fraudulent by the Member States over the period 2016-2020 for market measures expenditure. The table also gives the total payments for market measures and the FDR. 70  

FDR was the highest in Poland and Bulgaria, but significantly higher than the EU average also in Czechia. 15 Member States reported fraudulent cases in this area. France and Poland reported the highest number of cases and Poland and Bulgaria reported the highest financial amounts involved.

If no relevant irregularities were reported, no FDR is calculated and the Member State is grey.

See Table NR 27. UK is not included in the map.

Table NR28 and Map NR4 provide an overview of the irregularities not reported as fraudulent by the Member States over the period 2016-2020 in relation to market measures. It also gives the total payments for expenditure under market measures and the IDR.

The IDR exceeded 17% in Poland, Romania and Malta. It was higher than the EU average also in Hungary, Sweden and Bulgaria. 22 Member States reported non-fraudulent cases concerning market measures. Spain, France and Italy reported the highest number of cases and Poland, Romania, Spain and France reported the highest financial amounts involved.

If no relevant irregularities were reported, no FDR is calculated and the Member State is grey. See Table NR 28.

UK is not included in the map.

Tables NR27 and NR28 indicate that the reporting of irregularities was concentrated in a few Member States. The top two Member States in terms of number of detections (France and Poland) reported about 57% of all fraudulent irregularities (70% of irregular financial amounts) related to market measures, while they received about 25% of payments. For non-fraudulent irregularities, the top two Member States in terms of number of detections (Spain and France) did not overlap with the highest ranking Member States in terms of the financial amounts involved (Poland and Romania). Poland and Romania reported about 60% of the irregular financial amounts and received about 5% of payments.

As mentioned in Section 3.4.3.1, the concentration of detections was analysed in detail in the 2018 PIF Report, covering the period 2014-2018. 71 The analysis suggests that the level of concentration of detections went beyond what could be expected given the concentration of payments related to market measures among Member States, especially for fraudulent irregularities. This suggests the need for more uniform practice in criminal investigation and prosecution to protect the EU budget. 

3.4.3.3. Direct payments to farmers

Table NR29 and Map NR5 provide an overview of the irregularities reported as fraudulent by the Member States over the period 2016-2020 in relation to direct payments to farmers. It also shows the total payments for direct payments and the FDR. 72

Romania recorded the highest FDR, at 0.12%, followed by Italy and Slovakia, at 0.05%. Thirteen Member States have reported fraudulent cases in this area. Romania and Italy reported the highest number of cases and financial amounts involved.

In this map, ‘0.00’ indicates low financial amounts involved in the irregularities, in proportion to the payments

received. If no relevant irregularities were reported, no FDR is calculated and the Member State is grey.

See Table NR 29. UK is not included in the map.

Table NR30 and Map NR6 provide an overview of the irregularities not reported as fraudulent by the Member States over the period 2016-2020 in relation to direct payments. It also shows the total payments for direct aid and the IDR.

The IDR was the highest in Italy (0.44%), double the rate for Romania, which ranked second. 21 Member States have reported non-fraudulent cases in direct aid.

In this map, ‘0.00’ indicates low financial amounts involved in the irregularities, in proportion to the payments received. If no relevant irregularities were reported, no FDR is calculated and the Member State is grey. See Table NR 30. UK is not included in the map.

Tables NR29 and NR30 suggest that the reporting of irregularities was concentrated in a few Member States. The top two Member States in terms of number of detections (Romania and Italy) reported 80% of all fraudulent irregularities (and 78% of irregular financial amounts) related to direct aid, while they received about 14% of payments. With reference to non-fraudulent irregularities, the top two Member States in terms of number of detections (Italy and Romania) reported about 62% of such irregularities (and 77% of irregular financial amounts), while they received about 14% of payments.

The concentration of detections in relation to direct payments to farmers was analysed in detail in the 2018 PIF Report, covering the period 2014-2018. 73 The analysis suggests that the concentration of detections went beyond what could be expected given the level of concentration of payments related to direct aid to farmers among Member States. This may be due to different factors, including no uniform management and control systems and, for the fraudulent irregularities, different approaches to criminal investigation and prosecution to protect the EU financial interests.

3.4.4.Follow-up to suspected fraud

In the 2019 PIF Report, a new analysis was carried out into the follow-up Member States give to suspected fraud. The analysis covers the irregularities reported as suspected fraud from 2007 to 2013 and look at whether these irregularities have been dismissed, are still pending as suspected fraud or have been confirmed as established fraud. Details on the methodology for this analysis can be found in the 2019 PIF Report. 74

Table NR31 includes the update of the dismissal ratio, established fraud ratio and pending ratio. The dismissal ratio gives the percentage of fraudulent irregularites reclassified as non-fraudulent over their lifetime, until end of 2020. 75 The established fraud ratio gives the percentage of fraudulent irregularities classified as established fraud by the end of 2020. 76 The pending ratio gives the percentage of fraudulent irregularities still classified as suspected fraud at the end of 2020.  77 The three percentages sum up to 100%.

Similar to 2019, about 22% of the irregularities reported as fraudulent were dismissed by the end of 2020. Another 64% of these irregularities were still pending and for about 40% of these cases, no change of status is to be expected. This is because about 40% of the irregularities still labelled as suspected fraud at the end of 2020 were closed. This would indicate a significant underestimation of the dismissal ratio, which could be already considered above 45%, and could potentially exceed 85% if most of the pending cases of suspected fraud are dismissed.

The dismissal ratio varied across the Member States. High dismissal ratios, especially when associated with high pending ratios, may be either due to the detection phase or to the investigation/prosecution phase. Low dismissal ratios may be positive, but they may also be the result of many irregularities still pending. After seven years following the end of the period under consideration (2007-2013), the dismissal ratio was zero or very low in many Member States. This indicator must be read in combination with the pending ratio. The pending ratio indicates that the dismissal ratio may increase in the future (depending on the number of cases that are still open) or that the dismissal ratio may be underestimated (depending on the number of cases that are already closed).  

There were few cases of established fraud. This may indicate the need to invest further in the investigation/prosecution phase. At EU-27 level, the established fraud ratio was 14%. It was zero or very low in many Member States. In general, the established fraud ratio is not likely to increase significantly because, although 64% of cases are still classified as suspected fraud (pending ratio), about 40% are already closed and, in any case, between 7 and 14 years have already passed since the irregularity was detected.

3.5.Recovery cases

For an in-depth analysis of recovery and financial corrections in the CAP, see the DG AGRI’s 2020 Annual Activity Report and the 2020 Annual Management and Performance Report for the EU Budget 78 .

Main findings

Fraudulent irregularities

Over the period 2016-2020, the number fraudulent irregularities in support to agriculture expenditure was rather stable. This was the case also for the financial amounts involved, apart from a significant increase in 2017-2018, caused by just two cases related to market measures.

The fraudulent irregularities in rural development expenditure were related to both PP 2007-2013 and PP 2014-2020. The number of irregularities related to PP 2007-2013 fell sharply as from 2017. This is line with the multiannual nature of the PP, which closed in 2015. The drop was not compensated by the increase in detections related to PP 2014-2020. During the first seven years of implementation, the management and control systems for PP 2014-2020 detected much fewer fraudulent irregularities than the systems for PP 2007-2013, during the first seven years of that PP (during 2009-2013). This slow start should be closely monitored to ensure it is not due to a reduced focus on combatting fraud.

During 2016-2020, more fraud was detected in rural development than in support to agriculture expenditure, in proportion to the payments received by the Member States. The weight of the financial amounts involved in fraudulent irregularities on payments (fraud detection rate - FDR) for rural development was three times that for support to agriculture (0.19% versus 0.06%). The FDR was 0.1% for the overall CAP expenditure. Reimbursement-based expenditure, such as rural development, is more prone to errors than entitlement-based expenditure and provides more opportunities for fraudsters. Most support to agriculture payments concern direct aid to farmers, which recorded the lowest FDR, at 0.01%. In this area the integrated administration and control system and the parcel identification system support cross-checks, which enhances prevention. However, the other component of support to agriculture, market measures, accounted for the highest FDR, at 0.68%. Excluding a few irregularities involving exceptional financial amounts, the FDR was still 0.32%, nearly double that for rural development.

The detection of fraudulent irregularities was concentrated in few Member States. The level of concentration goes beyond what could be expected given the level of concentration of corresponding payments. This could be due to many different factors, including different underlying levels of irregularities and fraud, differences in the quality of prevention or detection work or different practices concerning the stage of the procedure when potentially fraudulent irregularities are reported. The concentration of detections was more accentuated for fraudulent rather than for non-fraudulent irregularities. This suggests that different approaches to criminal investigation and prosecution could be an additional and significant factor explaining the different levels of detection among Member States.

In most fraudulent irregularities, the ‘persons involved’ tend to be legal entities. Most are private companies, followed by non-profit organisations, in particular associations. Most fraudulent irregularities involve a single entity.

Non-fraudulent irregularities

Over the period 2016-2020, non-fraudulent irregularities in support to agriculture expenditure continued to be rather stable. The irregular financial amounts linked to this part of the budget fluctuated strongly, mainly due to three cases related to market measures involving over EUR 10 million each reported in 2017 and 2019, and none detected in 2016, 2018 and 2020.

Non-fraudulent irregularities in rural development expenditure concerned both PP 2007-2013 and PP 2014-2020. The number of irregularities related to PP 2007-2013 fell sharply from 2016 to 2019. As for fraudulent irregularities, this was expected since this PP closed in 2015. The increase in detections related to PP 2014-2020 did not compensate for the decrease. This slow start is more in line with the situation at the start of PP 2007-2013 (see fraudulent irregularities in rural development). During the first seven years of implementation, the management and control systems for PP 2014-2020 detected a number of irregularities similar to the level achieved by the systems for PP 2007-2013 over the first seven years of implementation of that PP (i.e. during 2009-2013).

The number of non-fraudulent irregularities in rural development expenditure has regularly and significantly exceeded those in support to agriculture throughout the entire 2016-2020 period, with over double the number of irregularities. The ratio of the financial amounts involved in non-fraudulent irregularities on payments (the irregularity detection rate - IDR) was very different between the two types of support, as it was 0.16% for support to agriculture and 0.86% for rural development (0.33% for the overall CAP expenditure). Most of support to agriculture payments concern direct payments to farmers, which recorded the lowest IDR, at 0.07%. This is consistent with the the findings of the European Court of Auditors, according to which payments made on an entitlement basis (such as direct payments to farmers, which represent most of CAP expenditure) is less prone to error than reimbursement-based expenditure (such as rural development). However, another part of support to agriculture, market measures, accounted for the highest IDR, at 1.64%. Excluding a few irregularities involving exceptional financial amounts, the IDR was 1.23%, still 50% higher than that for rural development.

Types of violation – support to agriculture

Over the period 2016-2020, fraudulent irregularities in support to agriculture mainly concerned the documentary proof. Fraudulent irregularities concerning the request were also prevalent. In most cases, it was due to falsified documentary proof or falsified requests. A wide range of documents can be falsified, such as invoices and lease agreements. Requests for aid may include false information about the eligible area, compliance with other conditions for aid, etc. Irregularities concerning 'over declaration and/or declaration of fictitious product, species and/or land' were also frequently detected.

The Member States detected few fraudulent cases related to the implementation of the action, but these cases accounted for the second highest financial amounts involved. High average financial amounts (about EUR 1.8 million) were recorded in several cases of conflict of interest combined with other violations. These irregularities were related to the market measure ‘promotion’ and were investigated by OLAF, which uncovered a complex fraudulent scheme, mainly based on price inflation, kickback payments and money laundering. The public procurement procedures were also breached via a solid network of companies based in different countries. In some cases, the manipulation was possible also due to the collusion of the beneficiaries.

One Member State reported a significant number of fraudulent cases of beneficiaries creating artificial conditions to receive financial support, under the category ‘ethics and integrity’. For example, beneficiaries may artificially split agricultural holdings and request aid via several linked companies, to avoid degressive aid rates or limits in terms of area or animals. Either the other Member States failed to detect similar irregularities or they reported them under other categories.

Non-fraudulent violations mostly concerned requests for aid. These requests were often falsified, which would not be expected for non-fraudulent irregularities. Similar findings apply to violations concerning documentary proofs, which were also quite frequent. Other prevalent types of irregularities not reported as fraudulent in support to agriculture expenditure concerned the implementation of the action, the 'over declaration and/or declaration of fictitious product, species and/or land' and the operator not having the required quality.

For non-fraudulent irregularities, the highest financial amounts were due to infringements concerning the implementation of the action. In this area, the three most reported types of violations concerned the action itself (not implemented or not completed), and refusal to repay not spent or unduly paid amounts.

Types of violations – rural development

Similar to irregularities in support to agriculture payments, over the period 2016-2020, irregularities in rural development mainly involved cases of falsified documentary proof or, to a lesser extent, falsified requests for aid. This may include falsified invoices, declarations of equipment as new while it is second-hand, bids in the context of procurement and information on compliance with conditions for receiving the aid. A significant number of rural development fraudulent irregularities were related to the action, which was often not implemented.

One Member State reported a high number of rural development fraudulent cases of beneficiaries creating artificial conditions to receive financial support, under the category ‘ethics and integrity’ (see also support to agriculture). Only one irregularity was reported as corruption. Conflicts of interest were reported more often, especially in the context of public procurement, together with other irregularities such as falsified requests for aid or documentary proof.

The highest number of non-fraudulent irregularities in rural development were related to the action, most often not completed, not implemented or delayed. Violations concerning the documentary proof (most often missing) or the beneficiary (most often not having the required quality) were also prevalent. They were also often combined with the violations concerning the action and with each other. Several cases of falsified documents or requests of aid were reported, which would not be expected for non-fraudulent irregularities.

There were just a few reported cases of conflict of interest. In 2020, the detection of non-fraudulent 'over declaration and/or declaration of fictitious product, species and/or land' sharply increased.

Zooming in on market measures

Individual fraudulent and non-fraudulent irregularities involving the highest financial amounts are often related to market measures. From 2016-2020, the few, but high-impact irregularities were related to aid to producer groups for preliminary recognition in the ‘fruits and vegetables’ sector and a food programme for deprived persons.

The highest number of irregularities reported as fraudulent was related to national support programmes for the wine sector. Recent analysis showed that in this domain irregularities affect (i) investment measures; (ii) promotion, especially in non-EU markets; (iii) and the restructuring and conversion of vineyards.

The highest total financial amount was related to market measures concerning fruits and vegetables. In this context, recent analysis showed that fraudulent irregularities have an impact in particular on aid for producer groups for preliminary recognition, especially investment measures. After fruits and vegetable, the second highest total financial amount involved in fraudulent irregularities concerned the measure ‘promotion’. Recent analysis showed that in this sector, irregularities concern both the EU and non-EU markets, with higher financial amounts involved in non-EU markets.

For irregularities not reported as fraudulent, the category 'products of the wine-growing sector' was the most frequently reported, but the highest total financial amount was for 'fruit and vegetables'. The category 'food programmes' was affected by few irregularities, but they accounted for high financial amounts, also due to one non-fraudulent irregularity.

Follow-up on the recommendation to improve detection capabilities

Detection capability is key to the effectiveness and efficiency of the system for the protection of the EU budget. In the context of past PIF reports, the Commission recommended to the Member State to further exploiting the potential of risk analysis. The Commission also recommended improving the spontaneous reporting of potential irregularities and strengthening the protection of whistle blowers, who are also a crucial source for investigative journalism. So far, there has been little improvement on the ground, at least in terms of detections after requests for reimbursement are sent to the Commission.

Anti-fraud work carried out by the Member States

The Member States are requested to indicate the date or period when the irregularity was committed. Most irregularities covered extended spans of time, particularly in cases of fraudulent irregularities, consistent with their intentional nature. The average duration of these protracted irregularities is about two years, both for fraudulent and non-fraudulent cases.

Detection rates are the outcome of the checks carried out by the Member States and they can vary across Member States due to different underlying levels of irregularities and fraud, but also due to differences in the quality of prevention or detection work or different reporting practices. Over the period 2016-2020, the FDR exceeded 0.40% in Bulgaria, Estonia and Romania. However, the picture changes depending on the CAP sector. For rural development, Estonia, Romania, Denmark, and Bulgaria recorded the highest FDRs, while Bulgaria and Portugal scored the highest IDRs. For market measures, the FDR was the highest in Poland and Bulgaria, but also significantly higher than the EU average in Czechia. The IDR was the highest in Poland, Romania and Malta, but it was also more than double the EU average also in Hungary. For direct aid, Italy and Romania recorded both the highest FDRs and the highest IDRs.

Therefore, detection levels were different across the Member States. In all CAP sectors (rural development, market measures and direct aid) the level of detection of irregularities and fraud across the different Member States was uneven. The level of concentration among Member States was analysed in detail in the 2018 PIF Report, covering the period 2014-2018.

For rural development, this analysis suggested that the difference in level of concentration between detections and payments was less pronounced for non-fraudulent irregularities, even though the examination of data on individual Member States highlighted significant discrepancies. The concentration of detections was instead more accentuated for fraudulent irregularities, suggesting that different approaches to criminal investigation and prosecution could be an additional and significant factor explaining the different levels of detection among Member States. Also in the specific case of market measures, this analysis found that the level of concentration of detections went beyond what could be expected given the distribution of corresponding payments, especially for fraudulent irregularities.

According to the same analysis, direct aid was the CAP sector with the highest level of concentration. This may be due to different factors, including not uniform management and control systems and, for the fraudulent irregularities, different approaches to criminal investigation and prosecution. Specific problems may occur at the local level that need to be correctly and promptly addressed by the competent national authorities.

About one fifth of the irregularities reported as fraudulent were dismissed. The dismissal ratio varied across the Member States. High dismissal ratios, especially when associated with a high number of still pending cases, may be due to (i) a detection phase that leads to report to the judicial authority cases that were not fraudulent; (ii) an investigation/prosecution phase that gives low priority or does not have enough resources to properly address the case.  

Analysis suggests that the dismissal ratio is significantly underestimated. About 64% of the irregularities reported as fraudulent were still pending. However, for about 40% of them no changes of status are to be expected, because they are closed cases. There were few cases of established fraud. This may indicate the need to invest further in the investigation/prosecution phase. 

(1) This document does not represent an official position of the Commission.

(2)

SWD(2016)237final

  http://ec.europa.eu/anti-fraud/sites/antifraud/files/methodology_statistical_evaluation_2015_en.pdf

(3) In September 2019, the reporting rules were clarified and updated. 

(4)  OWNRES is the abbreviation for ‘Own Resources’. The OWNRES application is used by Member States to report fraudulent and non-fraudulent cases involving amount of TOR of more than EUR 10 000.

(5)

The UK left the EU on 31 January 2020 and is no longer a member of the EU. However, the UK was still part of the internal market and customs union until 31 December 2020 as agreed in the UK-EU Withdrawal Agreement .

(6) Cases with a TOR amount exceeding EUR 10 million.

(7) BE (1 case – EUR 15 million), Germany (3 cases – EUR 35 million) and FR (1 case – EUR 17 million).

(8)  See Annex 4.

(9)  On the cut-off date for the 2019 PIF report.

(10) Belgium, Bulgaria, Germany, Estonia, Greece, Spain, France, Croatia, Latvia, Lithuania, Hungary, Slovenia, Finland and Sweden.

(11) Belgium, Germany, Spain, France, Italy, the Netherlands and Poland.

(12) Belgium, Germany, Spain, France and Poland.

(13)

The UK left the EU on 31 January 2020 and is no longer a member of the EU. However, the UK was still part of the internal market until 31 December 2020 as agreed in the UK–EU Withdrawal Agreement .

(14)

  Source: EUROSTAT, EU trade in goods strongly impacted by the COVID-19 pandemic in 2020 ,  https://ec.europa.eu/eurostat/product?code=DDN-20210325-1

(15) Taking into account that new reporting rules for fraudulent and non-fraudulent cases detected during post-clearance were introduced in September 2019. A potential effect of this is that post-clearance detections are no longer artificially split based on the CN headings.

(16) Total established and estimated amount in OWNRES as a percentage of total gross TOR collected. Data as on the cut-off date of 15.3.2021.

(17) Larger individual cases detected in a specific year may affect annual rates significantly. The detection rates can also be affected by the way a Member State’s customs control strategy is set up to: (i) target risky imports and (ii) detect TOR-related fraud and irregularities.

(18)

No conclusion can be made for Cyprus, Luxembourg and Malta due to very few cases reported in 2016-2020.

(19) See Annex 5. The estimated amounts are excluded.

(20)  See Annex 10.

(21)  See Annex 5.

(22) Estonia, Malta, Portugal and Slovakia.

(23) See Annexes 6 and 7.

(24) The category ‘Other’ combines, among others, the following procedures or treatments: (i) processing under customs control; (ii) temporary admission; (iii) outward processing and standard exchange system; (iv) exportation; (v) free zone or free warehousing; (vi) re-exportation; (vii) destruction; and (vii) abandonment to the exchequer.

(25) See Annexes 8 and 9.

(26) Belgium, Germany, Ireland, France, Italy, Lithuania, Portugal, Romania and Slovenia.

(27) Combined nomenclature or CN –nomenclature of the common customs tariff.

(28) Bulgaria, Czechia, Denmark, Spain, Italy, Cyprus, Luxembourg, Hungary, Malta, the Netherlands, Austria, Portugal, Slovenia, Slovakia and Sweden.

(29) See Annexes 6 and 7.

(30) See Annexes 8 and 9.

(31) Czechia, Denmark, Croatia, Latvia, Lithuania, Hungary, Malta, the Netherlands, Austria, Poland, Slovakia and Sweden.

(32) Belgium, Czechia, Denmark, Germany, Ireland, Spain, France, Italy, Latvia, the Netherlands, Austria, Slovenia, Finland and Sweden.

(33) Source: EUROSTAT, EU trade in goods strongly impacted by the COVID-19 pandemic in 2020, https://ec.europa.eu/eurostat/product?code=DDN-20210325-1

(34) Not all imports of COVID-19-related goods fall under the scope of Commission Decision (EU) 2020/491 of 3 April 2020.

(35) Cyprus and Luxembourg did not report any irregular case in 2020.

(36) Denmark (6%), Germany (6%), Spain (3%), Hungary (7%), the Netherlands (2%), Austria (6%), Finland (7%), Sweden (1%) and the UK (0%).

(37) Bulgaria (100%), Estonia (75%), Croatia (57%) and Lithuania (62%).

(38)

Total established and estimated amounts related to fraudulent cases as a percentage of the total TOR collected by Member States.

(39) See Annex 4.

(40) Total established and estimated amounts related to non-fraudulent cases as a percentage of the total TOR collected by Member States.

(41) See Annex 4.

(42)  This calculation is based on 19 740 cases, an established amount of EUR 2.87 billion (after already processed corrections) and a recovered amount of EUR 1.13 billion.

(43) See Annex 10.

(44) See Annex 10.

(45) This calculation is based on 96 229 cases, an established amount of EUR 6.61 billion (after already processed corrections) and a recovered amount of EUR 4.89 billion.

(46) The HRR expresses the recovery result in both complex and simple cases. Established and closed cases from 2018 onwards are therefore excluded, because these are predominantly simple cases (complex cases can generally not be closed within 3 years).

(47) See Annex 11.

(48)  Court case C-213/19, Commission vs the UK.

(49) Case C-392/02 of 15/11/2005. These cases are typically identified: (i) on the basis of Articles 119 and 120 (administrative errors which could not reasonably have been detected by the person liable for payment) and 103(1) (time-barring resulting from the inactivity of the customs administration) of the Union Customs Code; or (iii) on the basis of non-observance by the customs administration of articles of the Union Customs Code giving rise to legitimate expectations on the part of an operator.

(50) It includes customs duties (EUR 39 million) and interest (EUR 70 million).

(51) ‘Suspected fraud’ means an irregularity that gives rise to the initiation of administrative or judicial proceedings at national level in order to establish the presence of intentional behaviour, in particular fraud, as referred to in Article 1(1)(a) of the Convention drawn up on the basis of Article K.3 of the Treaty on European Union, on the protection of the European Communities’ financial interests. Regardless of the approach adopted by each Member State, ratification of the 1995 Convention has equipped every country with a basis for prosecuting and possibly imposing penalties for specific conducts. If this happens, i.e. a guilty verdict is issued and is not appealed against, the case can be considered ‘established fraud’. See ‘Handbook on ‘Reporting irregularities in shared management’ (2017).

(52) The reporting of irregularities below this threshold between 2015-2019 was analysed in the framework of the 2019 PIF Report (see Section 3.2.1. of ‘Statistical evaluation of irregularities reported for 2019: own resources, agriculture, cohesion and fisheries policies, pre-accession and direct expenditure’, SWD(2020)160 final (part 1/3)).

(53) Data for this Report was downloaded from the Irregularities Management System (IMS) on 8/3/2021. When entering a case into IMS, the contributor is requested to specify the currency in which the amounts are expressed. If the value of this field is left blank, no transformation is applied. If this field is filled with another currency, the financial amounts involved in the irregularity are transformed on the basis of the exchange rates published by the ECB at the beginning of 2021.

(54)  The category 'unclear' is used where the information is considered insufficient to classify the irregularity in any other category. Annex 12 provides a detailed explanation of the classification of irregularities in SA, RD, SA/RD, ‘unclear’.

(55) Section 3.4.3 of ‘Statistical evaluation of irregularities reported for 2018: own resources, agriculture, cohesion and fisheries policies, pre-accession and direct expenditure’, SWD(2019)365 final.

(56) Fluctuations in the financial amounts involved in irregularities should not be misinterpreted. It must be kept in mind that a significant portion of financial amounts is linked to a relatively low number of cases. In this context, fluctuations are more likely and should not be overemphasised.

(57) See Section 3.3.5. of ‘Statistical evaluation of irregularities reported for 2019: own resources, agriculture, cohesion and fisheries policies, pre-accession and direct expenditure’, SWD(2020)160 final.

(58) A person involved is anyone who had or has a substantial role in the irregularity. This could be the beneficiary, the person who initiated the irregularity (such as the manager, consultant or adviser), the person who committed the irregularity, etc.

(59) For the full description of the categories of irregularities and the related types of violations, please see Annex 13.

(60) There was one additional case of conflict of interest in combination with other categories of violation. Both cases where conflict of interest was involved were related to market measures.

(61) However, another irregularity was reported where conflict of interest was mentioned (as an ‘ethics and integrity’ issue) together with other violations concerning the documentary proof. In addition, nine cases of conflict of interest in public procurement processes were reported (under the category ‘public procurement’ and not ‘ethics and integrity’), always combined with ‘false or falsified request for aid’. In two of these cases, conflict of interest was also combined with ‘documents false and/or falsified’ and, in one case, with ‘action not implemented’.

(62) Some of the irregularities used for these calculations do not refer exclusively to a specific policy measure, because the same case may cover several budget posts referring to different measures. The ‘SA/RD’ cases are only included in the total CAP FDR/IDR. So the SA and RD FDR/IDR are slightly underestimated. By contrast, several cases considered under ‘direct payments’ (DA) had an impact both on DA and RD. There is only one case that impacted both on MM and RD. There are only two cases that impacted both on MM and DA. These 'mixed' cases are included with their full financial amount in DA or MM. So the DA and MM FDR/IDR are slightly overestimated. See ‘Statistical evaluation of irregularities reported for 2019: own resources, agriculture, cohesion and fisheries policies, pre-accession and direct expenditure’, SWD(2020)160 final (Annex 14) for a methodology to assess the impact on FDR and IDR of these ‘mixed’ cases. This methodology applied to the period 2016-2020 suggests that FDR and IDR are not significantly sensitive to these ‘mixed’ cases issues.

(63) Section 9.2 of ‘29th Annual Report on the Protection of the EU’s financial interests – Fight against fraud – 2017’, COM(2018)553 final and ‘Statistical evaluation of irregularities reported for 2017: own resources, agriculture, cohesion and fisheries policies, pre-accession and direct expenditure’, SWD(2018)386 final.

(64) Table NR17 includes reasons that may indicate the use of some forms of risk analysis (comparison of data, probability checks and statistical analysis).

(65) Reg. 485/2008 repealed Reg. 4045/1989.

(66) The Member States have an obligation to report only irregularities for which payment and certification to the Commission was made. As a consequence, the IDR focuses on the 'repression' side of the anti-fraud cycle and does not include the results of prevention. This does not apply to the FDR, as fraudulent cases must be reported regardless.

(67) This includes cases where the start date and the end date were not filled in.

(68) Payments are taken from the Annual Activity Reports (AAR) of the Commission’s Directorate-General for Agriculture and Rural Development from 2016 to 2020. In particular, reference is made to the tables on pages 61-63 of the AAR 2016, pages 74-76 of the AAR 2017, pages 90-92 of the AAR 2018, pages 74-76 of the AAR 2019, pages 52-54 of the AAR 2020.

(69) Section 3.4.3.1 of ‘Statistical evaluation of irregularities reported for 2018: own resources, agriculture, cohesion and fisheries policies, pre-accession and direct expenditure’, SWD(2019)365 final.

(70)

Some of these irregularities do not refer exclusively to market measures, but the reporting authority may have also included budget lines/posts referring to other measures (i.e. direct aid, rural development or other payments related to budget years before 2006). The full financial amounts of these irregularities are included in these tables.

(71) Section 3.4.3.2 of ‘Statistical evaluation of irregularities reported for 2018: own resources, agriculture, cohesion and fisheries policies, pre-accession and direct expenditure’, SWD(2019)365 final.

(72) Some of these irregularities do not refer exclusively to direct aid, but the reporting authority may have also included budget lines/posts referring to other measures (i.e. market measures, rural development or other payments related to budget years before 2006). The full financial amounts of these irregularities are included in these tables.

(73) Section 3.4.3.3 of ‘Statistical evaluation of irregularities reported for 2018: own resources, agriculture, cohesion and fisheries policies, pre-accession and direct expenditure’, SWD(2019)365 final

(74) See Section 3.4.4. of ‘Statistical evaluation of irregularities reported for 2019: own resources, agriculture, cohesion and fisheries policies, pre-accession and direct expenditure’, SWD(2020)160 final (part 1/3)

(75) IRQ2 stands for non-fraudulent irregularities, IRQ3 stands for suspected fraud, IRQ5 stands for established fraud. The following paths are considered for the dismissal ratio: IRQ3IRQ2, IRQ2IRQ3IRQ2, IRQ5IRQ3IRQ2, IRQ3IRQ2IRQ5IRQ3IRQ2, IRQ3IRQ5IRQ3IRQ2, IRQ5IRQ2.

(76) The following paths are considered for the established fraud ratio: IRQ3IRQ5, IRQ2IRQ3IRQ5, IRQ2IRQ5, IRQ5, IRQ5IRQ3IRQ5, IRQ3IRQ2IRQ5.

(77) The following paths are considered for the pending ratio: IRQ3, IRQ2IRQ3, IRQ5IRQ3, IRQ3IRQ2IRQ3, IRQ3IRQ5IRQ3.

(78) COM (2021) 301 final on 8/6/2021. See also the Communication from the Commission to the Parliament, the Council and the Court of Auditors on the Protection of the EU budget – COM(2016)486 on 18/7/2016.

EUROPEAN COMMISSION

Brussels, 20.9.2021

SWD(2021) 258 final

COMMISSION STAFF WORKING DOCUMENT

Statistical evaluation of irregularities reported for 2020: own resources, agriculture, cohesion and fisheries policies, pre-accession and direct expenditure

Accompanying the document

REPORT FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT AND THE COUNCIL

32nd Annual Report on the protection of the European Union's financial interests - Fight against fraud - 2020

{COM(2021) 578 final} - {SWD(2021) 257 final} - {SWD(2021) 259 final} - {SWD(2021) 262 final} - {SWD(2021) 263 final} - {SWD(2021) 264 final}

Table of Contents

List of abbreviations

4.COHESION, FISHERIES AND OTHER INTERNAL POLICIES

Executive summary

4.1.Introduction

4.2.General analysis

4.2.1.Irregularities reported as fraudulent

4.2.1.1.Trend by programming period

4.2.1.2.Trend by Fund

4.2.2.Irregularities not reported as fraudulent

4.2.3.Irregularities reported in relation to the PP 2014-2020: comparison with PP 2007-2013

4.3.Specific analysis

4.3.1.Detection rates by objective

4.3.2.Priorities concerned by the reported irregularities

4.3.2.1.Irregularities reported as fraudulent (fisheries not included)

4.3.2.2.Irregularities not reported as fraudulent (fisheries not included)

4.3.2.3.Irregularities related to investments in health infrastructure

4.4.Reasons for carrying out checks

4.5.Antifraud and control activities by Member States

4.5.1.Duration of irregularities

4.5.2.Detection of irregularities reported as fraudulent by Member State

4.5.3.Fraud detection rate

4.5.4.Irregularity detection rate

4.5.5.Follow-up to suspected fraud (programming period 2007-2013)

4.6.Other internal policies

Main Findings

5.PRE-ACCESSION POLICY

Executive Summary

5.1.Introduction

5.2.Instruments for Pre-accession Assistance

5.2.1.Before 2007: Pre-accession Assistance (PAA)

5.2.2.2007-2013: The Instrument for Pre-accession Assistance (IPA I)

5.2.3.2014 – 2020: The Instrument for Pre-accession Assistance (IPA II)

5.3.General analysis

5.4.Pre-accession Assistance (PAA 2000-2006)

5.4.1.Recent trends

5.4.2.Recent trends by component

5.4.3.Recent trends by beneficiary country

5.4.4.Trends since the start of PAA, by beneficiary country and component

5.5.Instrument for Pre-Accession Assistance (IPA I, 2007-2013)

5.5.1.Recent trends

5.5.2.Recent trends by component

5.5.3.Recent trends by beneficiary country

5.5.4.Trends since the start of IPA I, by beneficiary country and component

5.6.Instrument for Pre-accession Assistance II (IPA II 2014-2020)

5.6.1.Recent trends

5.6.2.Recent trends by component

5.6.3.Recent trends by beneficiary country

5.6.4.Trends since the start of IPA II, by beneficiary country and component

6.Direct Management

6.1.Introduction

6.2.General analysis

6.2.1.Five year analysis 2016-2020

6.3.Specific analysis

6.3.1.Recoveries according policy areas

6.3.2.Recoveries according to legal entity residence

6.3.3.Method of detection

6.3.4.Types of irregularity

6.3.5.Recovery

COUNTRY FACTSHEETS

Belgium - Belgique/België

Bulgaria – България

Czech Republic - Česká republika

Denmark – Danmark

Germany – Deutschland

Estonia – Eesti

Ireland – Éire

Greece – Ελλάδα

Spain – España

France

Croatia – Hrvatska

Italy – Italia

Cyprus – Κύπρος

Latvia – Latvija

Lithuania – Lietuva

Luxembourg

Hungary - Magyarország

Malta

Netherlands - Nederland

Austria – Österreich

Poland – Polska

Portugal

Romania – România

Slovenia – Slovenija

Slovakia – Slovensko

Finland – Suomi-Finland

Sweden – Sverige

Annexes

List of abbreviations

4.COHESION, FISHERIES AND OTHER INTERNAL POLICIES

Executive summary

Between 2016 and 2020, the number of fraudulent and non-fraudulent irregularities related to the 2007-2013 programming period decreased for the Cohesion Fund, the European Regional Development Fund, the European Social Fund and the Fisheries Funds (the European Structural and Investment Funds - ESIF), in line with the implementation cycle. The number of irregularities reported for the 2014-2020 programming period increased. For non-fraudulent irregularities this increase was, however, limited, highlighting an exceptional fall in the number of detected irregularities (and related financial amounts) in comparison to the previous programming period. The gap is significant for all Funds, but in particular for the European Regional Development Fund.

A number of implementation rules changed between the two programming periods. Further analysis would be needed to understand whether this decline is due to better management and prevention, including more effective and proportionate risk-based anti-fraud measures, or due to insufficient enforcement or reporting issues. A wider use of simplified cost options might be contributing to the decline of non‑fraudulent irregularities for the European Social Fund for the 2014-2020 programming period.

For the 2014-2020 programming period, ESIF-funded research and technological development, innovation and entrepreneurship projects were the most affected by fraudulent as well non-fraudulent irregularities, similarly to the previous period. The highest financial amounts related to non-fraudulent irregularities were with infrastructure projects, in particular motorway and road projects.

ESIF projects to improve a country’s health infrastructure are complex, requiring the procurement of services, works, and supplies of medical and ordinary equipment. Fraud and irregularities in this sector were therefore especially related to public procurement for both programming periods. National authorities must keep an eye on the risks that go with urgent spending based on simplified procedures and triggered by the COVID-19 crisis.

Past analysis of data from the 2007-2013 programming period suggested that the concentration of detections in the Member States could not be fully explained by the concentration of payments in these Member States. Other explanations could be different underlying levels of irregularities and fraud, differences in the quality of prevention or detection work or different reporting practices. The Commission recommended that the Member States make better use of risk analysis and improve the spontaneous reporting of potential irregularities. So far, there has been little improvement in the Member States.

It is still too early to assess the indicators related to the detection of fraud and irregularities (fraud detection rate – FDR and irregularities detection rate - IDR) for the 2014-2020 programming period. Experience from the previous period suggests that most irregularities are still to be detected. In Slovakia, the high FDR (15%) is due to three irregularities, accounting for about EUR 850 million. In Romania, the FDR exceeded 1%, while it was still close to zero in most of the other Member States. Slovakia recorded the highest IDR, at 6.5%. In line with the general decrease in non-fraudulent irregularities reported, the IDR was above 1% only in Bulgaria and below 1% in all other Member States.

The proportion of cases of suspected fraud that were reported about ten years ago and that did not lead to conviction is very high, while the cases of established fraud are few. This may point to the need to invest further in the reporting of suspected fraud and in the investigation/prosecution phase.

Concerning shared management Funds to finance other internal policies, the Fund for European Aid to the Most Deprived was the Fund most affected by fraud. More than 90% of the detections of non-fraudulent irregularities were related to the following Funds: Asylum, Migration and Integration Fund, the Fund for European Aid to the Most Deprived and the Youth Employment Initiative. 

4.1.Introduction

Section 4 presents a statistical evaluation of irregularities and fraud detected by the Member States during 2020, with reference to the cohesion and fishery policies. It places these detections in the context of past years and relevant programming periods.

Over half of EU funding is channelled through the five European Structural and Investment Funds (ESIF):

·The European Regional Development Fund (ERDF), which promotes balanced development in the different regions of the EU;

·The European Social Fund (ESF), which supports employment-related projects throughout Europe and invests in Europe’s human capital, i.e. its workers, its young people and all those seeking a job;

·The Cohesion Fund (CF), which funds transport and environment projects in countries where the gross national income (GNI) per inhabitant is less than 90% of the EU average. In 2014-2020, these countries were Bulgaria, Croatia, Cyprus, Czechia, Estonia, Greece, Hungary, Latvia, Lithuania, Malta, Poland, Portugal, Romania, Slovakia and Slovenia;

·The European Agricultural Fund for Rural Development (EAFRD) 1 , which focuses on resolving the particular challenges facing the EU's rural areas;

·The European Maritime and Fisheries fund (EMFF), which helps fishers to adopt sustainable fishing practices and coastal communities to diversify their economies, improving quality of life along European coasts. Due to the operating rules of the EMFF and the European Fisheries Fund (EFF), which are very similar to those of the other Structural Funds, irregularities reported by Member States in relation to fisheries policies are treated in this section, jointly with the Funds for cohesion and economic convergence.

For 2014-2020, EUR 454 billion 2 has been allocated to ESIF for project funding. National co-financing is expected to amount to at least EUR 183 billion, with total investment reaching EUR 637 billion. The purpose of all these funds is to invest in job creation and a sustainable and healthy European economy and environment. They mainly focus on five areas: (i) research and innovation; (ii) digital technologies; (iii) supporting the low-carbon economy; (iv) sustainable management of natural resources; and (v) small businesses.

The European Commission and the EU Member States jointly manage ESIF. Each Member State prepared a partnership agreement, in collaboration with the Commission.

After this introduction, Section 4.2. focuses on general trends for fraudulent irregularities and general trends for non-fraudulent irregularities. It compares detection in the programming period (PP) 2014-2020 with detection in PP 2007-2013, to better assess current trends in detecting irregularities. Section 4.3. analyses more specifically detection rates by objective and the priorities most affected by fraud and irregularities. This includes a deeper analysis of the potential risks related to investments in health infrastructure. Section 4.4. focuses on the reasons for carrying out checks that led to the detection of irregularities. Section 4.5. takes a closer look at the Member States’ anti-fraud activities and the results obtained, analysing fraud and irregularity detection rates (the ratio between the amounts involved in cases reported as fraudulent (FDR) or not reported as fraudulent (IDR) and the relevant payments). Section 4.6. provides figures on other shared management Funds.

4.2.General analysis

The analysis in this section refers to the EU-27, unless specified otherwise. UK data is added in the tables, as specified, to give a complete picture. However, the accompanying analysis is focused on the current Member States and the EU-27 aggregate. In the whole report, when reference is made to ‘fraudulent’ or ‘fraud’, it includes ‘suspected fraud’ and ‘established fraud’. 3

Member States are requested to communicate irregularities with financial amounts above EUR 10 000. During 2016-2020, several Member States also reported a number of irregularities below this threshold 4 . However, these irregularities represented less than 2% of all irregularities reported (EU-27). They are included in the analysis for this report, to make use of all available information.  5

Analysis of the EU cohesion policy is more complex than other budget sectors, as information refers to different programming periods, which are regulated by different rules.

4.2.1.Irregularities reported as fraudulent

4.2.1.1.Trend by programming period

Table CP1 provides an overview by programming period and by Fund of the irregularities reported as fraudulent in the past 5 years (2016-2020) 6 .

Fraudulent irregularities related to PP 2007-2013 peaked in 2015, gradually decreased in the following years and in 2018 they were overtaken by those related to PP 2014-2020. These dynamics are in line with known trends and patterns in the detection and reporting of irregularities and are linked to the PP 2007-2013 implementation cycle 7 .

Reporting related to PP 2014‑2020 basically started in 2017. It is on an increasing trend, despite an unexpected drop in 2019. The current fraud frequency level (FFL) 8 for PP 2014-2020 is high, at 11%. To put this into context, during the whole period between 2007 and 2020, FFL for PP 2007-2013 was just 5%. This higher tendency to detect fraud is influenced by a strong decrease in non-fraudulent irregularities with respect to PP 2007-2013. This is analysed further in the next sections.

Table CP2 provides an overview by programming period and by Fund of the financial amounts involved in cases reported as fraudulent. The financial amounts tend to fluctuate more due to the possibility of individual cases involving high amounts.

For PP 2007-2013, while the number of irregularities peaked in 2015, the financial amounts remained rather stable until 2017. Then the amounts started decreasing in 2018 and dropped in 2019. In 2020, there was a rebound mainly due to two ERDF irregularities reported by Italy and Romania, totalling more than EUR 30 million.

For PP 2014-2020, in 2018, the financial amounts skyrocketed at EUR 650 million. However, this was due to two ERDF irregularities reported by Slovakia, accounting for EUR 590 million. In 2019, the financial amounts decreased, but remained very high. Again, this was due to a CF irregularity of EUR  270 million reported by Slovakia. In the absence of these three irregularities, financial amounts for PP 2014-2020 would have tended to be rather subdued, despite the increasing number of detections. The acceleration in 2020 was supported by five CF cases reported by Romania, totalling EUR 85 million.

Also because of the higher share of EU financing channelled through this Fund, ERDF irregularities were prevalent. Of the irregularities detected between 2016 and 2020 for PP 2007-2013, 73% (84% of financial amounts) concerned ERDF. For PP 2014-2020, 64% (63% of the financial amounts) concerned ERDF.

Those involved were most often legal entities. In most Member States, private companies represent the majority of those involved. The only exception with a large sample is Spain, where most of the reported entities were sub-national governmental bodies.  9

4.2.1.2. Trend by Fund

Tables CP3 and CP4 focus on the distribution by Fund of the irregularities reported as fraudulent:

(1)ERDF was the Funds most affected, because it had the highest number of cases reported as fraudulent, and the related financial amounts were the highest.

The number of irregularities reported as fraudulent jumped in 2015. Since then it has fluctuated around the new, higher level. This was possible because the drop in new cases related to PP 2007-2013 was offset by the rise in detected irregularities related to PP 2014-2020. This did not happen in 2019: the number of cases for PP 2007-2013 and PP 2014-2020 decreased significantly.

Instead of peaking in 2015, the ERDF financial amounts continued to increase in 2016, and in 2018 they litterally skyrocketed. As mentioned, the extreme rise in 2018 was strongly influenced by the two irregularities reported by Slovakia (totalling EUR 590 million) for PP 2014-2020.

(2)After a decrease in 2017, the number of ESF fraudulent irregularities was rather stable. Detections related to PP 2007-2013 have been slowly decreasing while the detections for PP 2014-2020 have been slowly increasing. The financial amounts recorded an extraordinary increase in 2018, due to an irregularity reported by Portugal, accounting for more than EUR 30 million, related to PP 2007-2013;

(3)Since 2010, potential fraud affecting the CF is regularly reported. In 2020, the majority of detections took place in Romania, while in 2018 it was Slovakia reporting most cases. The amounts can fluctuate quite significantly, because of the low number of cases and high amounts involved in the projects financed by the CF. In 2017, the irregular financial amounts increased, due to one case reported by Greece (accounting for more than EUR 14 million). As mentioned, in 2019, the financial amounts skyrocketed because of an irregularity reported by Slovakia, accounting for EUR 270 million. In 2020, the financial amounts remained high because of five irregularities reported by Romania, totalling EUR 85 million.

These trends in financial amounts are also due to different reporting patterns in the Member States. This is examined in the 2019 PIF Report, with reference to the 2015-2019 period 10 . For the CF, Slovakia had a tendency to detect and report fraudulent cases with large financial amounts, supported by the propensity to identify irregularities covering most of the related expenditure. Italy, Portugal and Slovakia showed a similar pattern for the ERDF. For the ESF, Portugal, Poland and Romania had a tendency to detect and report fraudulent cases with large financial amounts, and only for Portugal was this supported by the propensity to identify irregularities covering a significant share of the related expenditure. Italy detected few ESF irregularities, but with exceptionally high amounts involved.

4.2.2.Irregularities not reported as fraudulent

Table CP5 provides an overview by programming period and by Fund of the irregularities not reported as fraudulent in the past five years (2016-2020). Table CP6 shows the financial amounts involved in these irregularities. As mentioned, fluctuations in the financial amounts are broader and more frequent than in the number of detections and they can be linked to individual irregularities or groups of irregularities of huge value.

The decrease in the number of irregularities and financial amounts related to PP 2007-2013 was significant. This is in line with the multiannual nature of structural programmes, which were closed already in 2015. This trend was common to all Funds. The financial amounts experienced a similar drop. However, in 2020 financial amounts increased for all Funds, except for the EFF. Slovakia reported two CF non-fraudulent irregularities, totalling more than EUR 40 million, and Romania and Slovakia reported two ERDF cases, accounting for EUR 30 million.

Basically, detections related to PP 2014-2020 began to be reported in 2016. Since then, detections and irregular financial amounts related to PP 2014-2020 have been increasing for all Funds, but less than expected when compared to the previous programming period. Furthermore, in 2020, there was a decrease in the number of CF and EFF non-fraudulent irregularities and in the financial amounts involved in the CF and the ESF. However, the drop in the financial amounts for the CF was due to the peak reached in 2019. Slovakia reported two irregularities, together accounting for more than EUR 120 million, which contributed to this peak.

As for the fraudulent irregularities, these trends in financial amounts are also due to different reporting patterns in the Member States. This was examined in the 2019 PIF Report, with reference to the 2015-2019 period 11 . For the CF, Slovakia had a tendency to detect and report non-fraudulent irregularities with large financial amounts involved, also because on average the irregularities covered a significant share of the related expenditure. Slovakia, Romania, Italy, Czechia and Poland tended to report large financial amounts for the ERDF. Slovakia and Hungary tended to do the same for the ESF.

4.2.3.Irregularities reported in relation to the PP 2014-2020: comparison with PP 2007-2013

The current programming period started in 2014, about 7 years ago. Reporting of irregularities basically began in 2016 and increased in the following years. To put this trend into perspective, it can be compared with the number and financial amounts of the irregularities that were recorded during the first 7 years of PP 2007‑2013. Tables CP7 and CP8 provide this information 12 . The following graphs provide a more precise comparison, based also on the actual date of reporting 13 . In any case, it must be borne in mind that this comparison is affected by the fact that the irregularities related to PP 2007‑2013 are more 'mature' than irregularities related to PP 2014-2020, which have only just recently been reported. The number of irregularities related to PP 2007‑2013 and the financial amounts involved are the result of several years of investigation (after detection). This brought into the picture additional information to: (i) confirm or refute the hypothesis that an irregularity had been perpetrated 14 ; (ii) classify the irregularity (as fraudulent or non-fraudulent); (iii) to quantify the financial amounts actually involved, etc.

As shown by Graphs CP1 and CP2, the number of irregularities reported as fraudulent was similar for PP 2014-2020 and PP 2007-2013, after a comparable period from the start of the programming periods. There was a slower start of reporting for the current programming period, but, during the fifth year of implementation, there was a strong acceleration that filled the gap. The comparison is more difficult for financial amounts (see Graphs CP3 and CP4). The financial amounts reported for PP 2014-2020 were much higher than for the previous programming period, because there were two noticeable jumps at the beginning of the fifth and seventh years of implementation. The first upswing was due to the two cases Slovakia reported for the ERDF, which totalled about EUR 590 million. The second jump was due to one case Slovakia reported for the CF, accounting for more than EUR 270 million (see Section 4.2.1.1). 

However, PP 2007-2013 experienced similar – but smaller - shifts, because, at the end of the fourth and sixth years of implementation, two cases were reported, each accounting for about EUR 120 million. In addition, at the beginning of the sixth year, an irregularity accounting for about EUR 33 million was reported. Taking these outliers out of the analysis, the financial amounts involved in the fraudulent irregularities reported for PP 2014-2020 were aligned with those reported for PP 2007-2013 during the same period after the start of the programming period.

This was the outcome of different patterns followed by different Funds.

The irregularities reported as fraudulent for the CF and the ERDF significantly increased from PP 2007-2013 to PP 2014-2020 (see Graphs CP5 and CP6). The increase in CF fraudulent irregularities was mainly due to detections in Slovakia and Romania, while detections in Hungary and Romania were the main contributors to the surge concerning the ERDF.

For the ESF and the Fisheries Funds, the detection and reporting of fraudulent irregularities was lower than before (see Graphs CP7 and CP8). ESF-related irregularities were lagging behind by a rather stable number of cases until the end of the sixth year. Then the gap widened due to an increase in irregularities for PP 2007-2013. This gap was mainly due to the decrease recorded in Germany, which was influenced by reporting practices 15 , and Romania. Also, the cumulated financial amounts associated with the ESF-related fraudulent irregularities for PP 2014-2020 were considerably lower than the amounts for PP 2007-2013, due to a strong increase during the seventh year of implementation of PP 2007-2013.

Focusing instead on the non-fraudulent irregularities, the fall in the number of cases and the financial amounts reported after 7 years from the start of the programming period is striking (see Graphs CP9-CP12). This significant difference between these two programming periods warrants further analysis.

The number of irregularities not reported as fraudulent (and the related amounts) can be influenced by the state of implementation of the programming period. An indicator to gauge this state of implementation may be the interim payments that have been made to the Member States, as these payments should reflect the progression of eligible expenditure 16 . Graph CP13, which covers the CF, the ERDF and the ESF, shows this, given that these three Funds account for most of the financial resources. During the first 7 years from the start of PP 2014-2020 (from 2014 to 2020), the Member States have received fewer interim payments than during the first 7 years from the start of PP 2007-2013 (from 2007 to 2013). At the end of 2020, this (cumulative) gap still amounted to about -17% and it had been higher before (see Graph CP13). However, at least part of this gap could simply be due to the fact that interim payments are limited to 90% of eligible expenditure and the remaining 10 % is released after the yearly examination and acceptance of the accounts. As such, this would not reflect delayed implementation 17 . Overall, these findings suggest that the dynamics of the gap in interim payments might explain some of the difference in the number of non-fraudulent irregularities, but certainly not all of it (as the total difference in detection is about -50% - see Table CP8 and Graph CP10). 

A closer look at Graph CP10 reveals that the gap is due to a sudden acceleration in the number of irregularities related to PP 2007-2013, which started during the fifth year of the programming period (2011). This can be seen by comparing the slopes of the curves representing the cumulative number of irregularities related to the two programming periods in Graph 10. During the sixth year, the slope of the PP 2014-2020 curve slightly increased but remained less than the slope of the PP 2007-2013.

In Graphs CP14-CP17, the irregularities not reported as fraudulent are presented by Fund. The widest gap is recorded for the ERDF (-55%). Also for the CF and the ESF, there were significant gaps with respect to PP 2007-2013, even if they were not as wide as for the ERDF (-32% for the CF, -42% for the ESF). For the CF, the financial amounts reported in relation to PP 2014-2020 were not far from those related to PP 2007-2013. For the ESF, the negative gap started to widen towards the end of the fifth year of implementation, both in terms of number and financial amounts. For the Fisheries Funds, the gap in terms of numbers was even higher than that of the ERDF (-59%), but this was based on far fewer cases. The curves of the financial amounts overlap until the end of the sixth year, before diverging due to a sudden upswing of the financial amounts related to PP 2007-2013.

Given that ERDF showed the widest gap between PP 2007-2013 and PP 2014-2020, Graph CP18 shows the comparison, Member State by Member State, in terms of number of irregularities not reported as fraudulent, with specific reference to this Fund. Graph CP19 focuses on the irregular financial amounts.

For the majority of Member States, the numbers of non-fraudulent irregularities related to the two programming periods have been on persistently diverging paths (see Graph CP18). There are a few exceptions, such as Bulgaria, France, Croatia, Lithuania and Slovakia. Further analysis by the Member States’ compentent authorities is warranted to understand the reasons for this drop and to rule out the possibility that this is due to less focus on detecting irregularities. This applies also to the trends for the other Funds.

For all the Funds, the competent national authorities can build on this analysis, to understand the causes of these trends in the different Member States. If they are due to different management and control systems, rules or prevention activities in comparison to the previous programming period, the Member States need to identify what measures brought about these huge changes. If the difference in trends between the two programming periods is due to less enforcement or to reporting issues, the Member States need to act upon these shortcomings in a timely manner.

In general, rules on thematic concentration 18 might have led to more effective spending. Focusing more on the management side, the 2007-2013 national strategic reference frameworks (NSRF) have been replaced by the 2014-2020 partnership agreements. These agreements must present an assessment of the administrative capacities of the authorities involved in implementating the ESI Funds together with – where relevant – a summary of actions to improve these capacities 19 . Last but not least, the legal framework for PP 2014-2020 requires the managing authorities to adopt effective and proportionate anti-fraud measures that take into account the risks identified 20 .

For PP 2014-2020, the possibility to use simplified cost options (SCOs) has been extended, but the impact depends on the extent to which implementing partners used this possibility. For PP 2007-2013, about 7% of the declared ESF expenditure was under SCOs, differing widely from one Member State to another. According to estimates made in 2016 and 2018, for PP 2014-2020, this percentage was expected to rise to 33-35% for the ESF by the end of the programming period. However, the expectation concerning the percentage of the ERDF-CF budget covered by SCOs was much lower, at 4%. Strong differences between Member States were expected 21 . Consequently, for the ESF, the increase in the percentage of expenditure covered by SCOs (from 7% to 33%) together with some implementation delays (still 13% at the end of 2020, as measured through interim payments) may have been factors contributing to the drop in non-fraudulent irregularities (decrease by 42%). However, the situation should be closely monitored, also because (i) any possible effect of delayed implementation will fade; (ii) it is not clear whether the increased use of SCOs will actually materialise; (iii) it is not clear to what extent the increased use of SCOs will concern projects that are more relevant for irregularity reporting 22 ; and (iv) it is not clear when, during the programming period, adopting more SCOs can have a greater impact on patterns of irregularities. In addition, the fact that the number of irregularities dropped even more for the ERDF, where the adoption of SCOs was very low, may point to other factors, which could also apply to the ESF.

As from PP 2014-2020, the Member States prepare accounts and then the Commission examines and accepts them each year (instead of at the closure of the programming period only) 23 . This might have helped to tighten up internal control at Member State level. In this framework, Member States may have an increased tendency to exclude from the annual accounts any expenditures where they have doubts about the legality and regularity. Such expenditures can be included in an application for interim payment relating to subsequent accounting years, while being automatically recovered by the Commission during the current year (without this constituting a financial correction and without it reducing support from the Fund to the relevant operational programme) 24 .

These are just a few possible examples of factors that might potentially influence the number of irregularities, but the actual relevance and impact of these and other changes in the different Member States should be properly evaluated by the national competent authorities.

The irregularity types detected and most reported by the Member States can shed further light on differences between PP 2007-2013 and PP 2014-2020. Changes in the legal framework and implementation context, including anti-fraud systems, may be reflected in the type of irregularities detected in the Member States.

The following tables provide an overview of the irregularities reported as fraudulent (Table CP9) and not reported as fraudulent (Table CP10) by the Member States in relation to PP 2007-2013 and PP 2014-2020. Like above, only the irregularities that had been reported after a comparable amount of time from the start of the programming period 2007-2013 are considered. See Annex 13 for the specific types of violations (IMS codes) that are included in the categories mentioned in Tables CP9 and CP 10.

Both for fraudulent and non-fraudulent irregularities, the number of detections related to non-eligibility and to the implementation of the action strongly declined. The decrease of eligibility violations could be related to the increasing use of SCOs. However, if this were actually the case, the more stringent controls on the implementation of the action that should accompany this change could be expected to lead to the detection of more irregularities of this type. Instead, the infringements of the contract provisions/rules also declined. 

For the irregularities reported as fraudulent (Table CP9), there were significant increases in the number of cases of false documents, infringement of public procurement rules and conflict of interest (under ‘ethics and integrity’). For the irregularities not reported as fraudulent, Table CP10 shows a widespread and deep decrease for all categories of violations. On the action’s implementation, the specific type of infringement that decreased the most was ‘other’ so it provides no further information. Other specific types that were significantly less reported were, for example, related to ‘action not implemented’ and ‘failure to respect deadlines’. Specific types of ‘implementation’ infringements were also reported more, such as ‘infringements with regard to the co-financing system’, ‘control not carried out in accordance with the rules’ and ‘action not completed’.

4.3.Specific analysis

This section covers the following aspects:

·Detection rates by objective (PP 2007-2013);

·Priorities and themes affected (PP 2014-2020);

·Types of irregularity (PP 2014-2020).

4.3.1.Detection rates by objective

The closure for PP 2007-2013 started in March 2017 25 ; this offers an ideal opportunity to present an overview of what occurs during a programming period that has gone through the full implementation cycle. Table CP11 shows the FDR and the IDR per objective.

Detection for different objectives ranged between 0.5% to 3.4%. On average, 5 out of 100 irregularities and 15 out of 100 euro were reported as fraudulent.

The highest FDR and IDR are associated with the ‘Fisheries’ objective. In addition, ‘Fisheries’ recorded the highest fraud frequency level (FFL) and fraud amount level (FAL) 26 . Past analysis has shown that, among the priorities absorbing most resources, the priority ‘Aquaculture, inland fishing, processing and marketing of fishery and aquaculture products’ was the riskiest, with ‘Measures for productive investments in aquaculture’ and ‘Investments in processing and marketing’ as the themes most affected. The priority ‘Technical assistance’ was also particularly vulnerable, but disparity in detection in different Member States was very high. In general, the priority ‘Measures of common interest’ appeared less exposed, but the specific theme ‘Development of new markets and promotional campaigns’ was vulnerable to fraud.

The objective ‘Convergence’ ranked second for all indicators. Looking at the overall detection rate (FDR+IDR), ‘Regional competitiveness and employment’ programmes recorded a relatively low level of detection and relatively low incidence of fraud. ‘European Territorial Cooperation’ programmes’ showed instead a peculiar behaviour: while detection was the lowest by far, the incidence of fraud was high, especially in terms of FAL.

4.3.2.Priorities concerned by the reported irregularities 

4.3.2.1.Irregularities reported as fraudulent (fisheries not included)

The operational programmes financed under the EU cohesion policy are implemented along identified priorities and themes. With the information provided by the Member States, the fraudulent irregularities can be analysed by priority areas.

Table CP12 shows the irregularities reported as fraudulent for PP 2014-2020 by priority area since the beginning of the programming period. The table also compares these irregularities with the situation of PP 2007-2013 when the same amount of time had passed after the start of the programming period. Comparison with the full PP 2007-2013 would be misleading, as projects pertaining to different priorities can have different implementation timelines; this may influence the time when irregularities are more likely to be detected.

From PP 2007-2013, the number of cases where the priority was not specified decreased from 33% to 4%, which was an outstanding improvement in the quality of reporting 27 . However, contrary to the Regulations in force for PP 2014-2020, the Member States continued to encode the irregularities in IMS using the (different) priorities that were valid for PP 2007-2013 28 . In Table CP12, the priorities for PP 2014-2020 are reported in white; while the situation has improved in comparison with 2019, the correct priorities were used in only about 32% of the irregularities.

The priority 'RTD, innovation and entrepreneurship' was even more prevalent for PP 2014-2020 than for PP 2007-2013. Besides the increase in the irregularities encoded with the ‘old’ RTD priority, several irregularities were reported under the ‘new’ priority ‘Development of endogenous potential’, which includes similar projects. The huge financial amounts associated with this ‘new’ priority are due to the two cases Slovakia reported, accounting for EUR 590 million.

The priority ‘Increasing the adaptability of workers and firms, enterprises and entrepreneurs’ ranked second, with an increasing number of cases compared to PP 2007-2013. However, the number of irregularities with the priority ‘Improving access to employment and sustainabily' decreased, including when considered together with the ‘new’ priority ‘Promoting sustainable and quality employment and supporting labour mobility’. It could be argued that the ‘new’ priority ‘Investing in education, training and vocational training for skills and lifelong learning’ could also be relevant to this context. From all this, it can be concluded that fraudulent irregularities related to improving employability increased.

Irregularities increased with ‘Energy’, infrastructure to provide basic services to citizens (such as energy, environment, transport and ICT) and social, health and education infrastructure. This was the case also for the priority related to social inclusion. The high financial amounts involved in the priority ‘Infrastructure to provide basic services to citizens’ were mainly due to one EUR 270 million irregularity Slovakia reported. This irregularity was in the transport sector. The decrease in the number of irregularities and financial amounts in the ‘old’ priority ‘Transport’ does not necessarily means that the impact on this sector decreased, because projects of this type are now covered by the ‘new’ priority related to basic services, where the number of irregularities increased.

4.3.2.2.Irregularities not reported as fraudulent (fisheries not included)

Table CP13 covers the irregularities not reported as fraudulent for PP 2014-2020 by priority area. The table compares this with the situation for PP 2007-2013 when the same amount of time had passed after the start of the programming period.

The comparison between the two programming periods is particularly difficult because several reasons:

·PP 2014-2020 and PP 2007-2013 have different prorities;

·As mentioned in Section 4.3.2.1., contrary to the Regulations in force for PP 2014-2020, the Member States often continued to encode the irregularities in IMS using the priorities that were valid for PP 2007-2013. The correct priorities were used in only about 49% of irregularities (improving from 2019, when this percentage was just about 20%);

·Compared to PP 2007-2013, the number of cases where the priority was not specified for PP 2014-2020 decreased from 37% to 10%, which was an outstanding improvement in the quality of reporting. However, this improvement has an impact on the comparison between single priorities in different programming periods 29 ;

·Overall, the number of irregularities not reported as fraudulent fell, from 9 041 to 4 257.

However, it can be noted that the ‘old’ priority 'RTD, innovation and entrepreneurship' together with the ‘new’ overlapping priority ‘Development of endogenous potential’ were the most affected by irregularities, with the second highest financial amounts involved when considered together. It may be argued that also the priority ‘Productive investment’ belongs to this context. Considering all of these priorities together, there were no significant changes from the previous programming period, despite the huge decline in global numbers.

The highest financial amounts were associated with the ‘new’ priority ‘Infrastructure providing basic services and related investment’, in particular the theme ‘TEN-T motorways and roads — core network’ (all irregularities reported by Slovakia). However, this increase is counterbalanced by a huge decrease in the financial amounts reported under the ‘old’ priority ‘Transport’.

4.3.2.3.Irregularities related to investments in health infrastructure

The focus of this section is on investment in health infrastructures. ‘Health infrastructure’ projects cover the building, renovation and modernisation of healthcare facilities, including the purchase of medical equipment. With the COVID-19 pandemic, EU funding to strengthen national healthcare systems increased and will increase further in the next programming period 2021-2027. 

Past research suggests that fraud and corruption significantly affect expenditure in healthcare. Worldwide, 10–25% of public procurement spending on health (medical devices and pharmaceuticals) is estimated to be lost to corrupt practices. Organised crime is interested in public spending for the health sector. Single bidding in the procurement of medical equipment often takes place, which might also indicate potential corruption or a lack of competition, including collusion between companies 30 .

‑Under PP 2007-2013, one of the priorities was ‘Investment in social infrastructure’, which covered education, health, childcare, housing and other social infrastructure. Under PP 2014-2020, the priority ‘Social, health and education infrastructure and related investment’ broadly covers the same type of expenditure. Figures CP1 and CP2 focus on the irregularities reported as fraudulent and non-fraudulent, respectively. The larger the square, the higher the number of detections; the darker the square, the higher the financial amounts involved. Health infrastrucure actions were affected by 18 fraudulent irregularities, involving about EUR 10.5 million and 577 nonfraudulent irregularities, involving about EUR 108 million. Therefore on average fraudulent irregularities involved about EUR 580,000 and non-fraudulent irregularities about EUR 190 000. 

Maps CP1 and CP2 show the number of detections related to ‘health infrastructure’. In addition, the darker the Member State in the map, the higher the financial amounts involved. Concerning cases reported as fraudulent (Map CP1), the Member States with the highest number of detections and irregular financial amounts were Slovakia, Romania and Czechia. Reporting of non-fraudulent irregularities was more widespread, with Poland leading in terms of numbers and Slovakia in terms of financial amounts.

Health infrastructure actions were strongly affected by violations of public procurement rules. They concerned 22% and 73% of fraudulent and non‑fraudulent irregularities, respectively. Irregularities due to public procurement violations represented an even more significant share in terms of financial amounts: 46% and 76% (fraudulent and non-fraudulent, respectively). Non-eligibility was relevant for fraudulent (33%) and non-fraudulent (16%) irregularities. Infringements of the contract provisions/rules were reported in 14% of the non-fraudulent cases, but in most cases the nature of the violations was not specified.

Based on past experience, it is possible to identify the potential risks to which expenditure in the healthcare sector is exposed. Learning from past collective experience may help better calibrate management and control systems.

However, future scenarios have to consider that the COVID-19 crisis increases known risks of irregularities and fraud. Significant EU spending is likely to cover the sudden need for supplies, services or works during the outbreak or the need to get prepared for new waves of the disease. In general, COVID-19 has led to unforeseeable events and extreme urgency, which may justify procurement through negotiated procedures and, under certain circumstances, even direct award. When emergency can be invoked, it is easier for fraudsters to obtain EU funding. Urgency and less competition facilitate conflict of interest and corruption. In addition, the altered balance between (pressing) demand and offer and the disruption of the supply chains increase the risk of entering into a contractual relationship with unreliable/not sufficiently vetted counterparts. Fake or substandard products may be covered by certificates (attesting the required quality) that are fake, misleading, issued by entities that are not authorised for that.

Projects to improve the health infrastructure are complex, requiring the procurement of services, works, and supplies of medical and ordinary equipment. Building on how irregularities affected projects of this type, a wide range of potential risks can be identified.

Wrongdoings that limit competition in the procurement of supplies/works/services may result in higher prices and/or lower quality/quantity. This may lead to choosing of an inefficient contractor, but may also generate an extra profit for an efficient contractor. This might be intentional and would make room for the payment of the price of corruption/collusion (to the beneficiary, the staff of the contracting authority or other economic operators that cooperated in the formation of the higher price).

The openness of the procedure may be undermined by irregularities related to the ‘how’, ‘what’ or ‘timing’ of the publication of the contract notice, which is meant to inform all potential bidders. Contracting authorities may unduly resort to negotiated procedures without publishing the contract notice, accelerated restricted procedures or even direct awards. This may result from the estimated value of the contract being undervalued or the contracts being artificially split. This keeps the single contract below the threshold value that requires a more open procedure.

The number of potential bidders may be unduly reduced through excessive or discriminatory requirements concerning the potential tenderer. These requirements may touch upon the economic operator’s economic and financial capacity or its knowledge and experience (in particular, previous similar contracts). Contracting authorities may also unduly restrict access to procurement by requesting that national and foreign tenderers provide different documents or that foreing tenderers be established in the country where the contract is to be implemented. Discriminatory requirements may also touch upon cooperation between economic operators, limiting subcontracting and consortium agreements.

Contracting authorities may, in the same contract, unduly group together works, supplies or services that are usually offered by different economic operators (artificial grouping). This excludes specialised economic operators from participating in the procedure, giving an undue advantage to fewer operators able to cover all different parts of the contract. In other cases, the procurement procedure may be rightly grouping similar supplies, but the contracting authority does not allow partial tendering, which unduly reduces competition. Other malpractices concern technical specifications that are too narrow or unnecessarily referring to certain standards or even to a specific brand, trademark, without explicitly allowing for equivalence. Discriminatory technical specifications can concern a wide range of medical equipment, but may also be found in procurement for works. Undue restrictions on the tenderer and on the subject matter of the contract (technical specifications) can reinforce each other.

Unclear or changing terms and conditions may make participation more difficult. This may concern the requirements for participation in the procedure, how they are assessed (the documents to show compliance with these conditions), the subject matter of the contract. It may also include unclear, or lack of, indications in the tender documentation on how foreign potential tenderers are supposed to comply or certify compliance with certain qualification requirements, such as registration in national or local trade or professional registers, authorisations from specific national authorities, such as the Ministry of Health, etc. The more unclear the terms and conditions, the more they may require clarifications during the procedure. This creates a ‘moving target’ setting. It is key that all participants get the same additional information at the same time. Certain clarifications may be so substantial that previous publications of the contract notice would need to be updated and the deadlines for presenting the offers extended. The contracting authority may fail to comply with these obligations.

Non-transparency could be due to insufficient documentation of the evaluation process and be rooted in vague or irregular award criteria. Contracts may be awarded to operators that do not meet the qualification criteria. This may also happen in a context where disproportionate requirements have been set, which probably prevented other operators from partecipating. The contracting authority may also unlawfully change the selection criteria after the tenders are opened. On the other hand, it may be that the exclusion of operators is not justified. The non-respected criteria may also concern the tender rather than the tenderer.

Competition may be defeated by collusion. This may include unlawful cooperation between bidders, such as coordination of price quotations, or between bidders and (staff of the) contracting authority. Suspicious similarities in the offers may suggest cooperation between bidders. There may also be cases where the contracting authority sends the invitation to tender to companies that are owned or managed by the same persons. Tenders may be fraudulently substituted, resulting in higher price of the awarded contract.

Contracts may be changed after the award. This alters the ‘value for money’ balance and casts doubts on the previous steps of the procurement procedure. These changes may concern the performance deadline, the scope, the technical content, the price, the experience of the experts or staff involved, the performance guarantee, advance payments. The contract may be different from the tender specifications already at the first signature or may be changed during implementation. If such changes had already been part of the tender specifications, other operators could have made better offers and could have won. Furthermore, these changes can generate additional profits for the economic operator, because of cheaper or fewer materials, less works for the same price or additional supplies or works for a higher price. Existing contracts may be amended or additional contracts may be unduly awarded to the current contractor, directly or after a negotiated procedure without publication.

Shortcomings in implementation may take various forms. This can have serious consequences for healthcare facilities, such as hospitals, where, for example, correct isolation and ventilation are key for the safety of patients, personnel and potentially the whole community, as the pandemic has shown. These could be shortcomings with the project for which the beneficiary was awarded EU funding and/or be shortcomings with the contract between the beneficiary and the contractors. If these shortcomings are accepted by the beneficiary, this situation is similar to a change of contract. However, a change of contract during implementation does not free the beneficiary from the commitments it undertook when presenting the project. But the contractor could fail to declare these shortcomings to the the beneficiary or could hide them from the beneficiary just as the beneficiary could do the same with the managing and control bodies. Documents that do not match with actual implementation on the ground may be used.

Irregularities may also be related to expenditure that leads to no improvements in the delivery of health services, fewer improvements than expected or improvements that are not durable. Beneficiaries might not comply with the commitment to maintain the supported activities during a certain period of time and at a certain level. The beneficiary might not or might seldom use the medical equipment funded by the project. Achieving project objectives may also be undermined by transfers of ownership or use or because the equipment was used, at least partly, for commercial purposes.

Requests for reimbursements may include costs for ineligible supplies or activities, such as works or the purchase of goods not in the quantity and not with the characteristics agreed with the approval of the project. The project may cover only new medical equipment, while the actual expenditure may be for ineligible second-hand equipment (with an inflated price, as if the equipment were new).

Excessive prices may be paid for medical equipment. This may result from deceptive practices by the beneficiary or other parties involved in the procurement procedure, where the bids may just be made to show the price is reasonable. As mentioned, the supply of second-hand rather than new equipment may be part of the fraudulent scheme. Inflated prices may follow discriminatory technical specification that can be satisfied only by one type of medical equipment.

Double funding may take place because of the overlapping of EU funds and financing from national or local institutions, but also with other projects funded by the EU. The beneficiary or the contractor may even submit an item of expenditure twice for reimbursement within the same project.

4.4.Reasons for carrying out checks

In the antifraud cycle, the capability of detecting fraud and irregularities is a key feature that helps making the system effective and efficient in protecting the EU budget. In the 2017 PIF Report, an analysis of the reasons for carrying out checks was introduced and led to the recommendation to take greater advantage of the potential offered by risk analysis. Furthermore, the report recommended that EU Member States facilitate and assess the spontaneous reporting of potential irregularities and strengthen the protection of whistle-blowers, who are also a crucial source for investigative journalism 31 .

So far, there has been little improvement on the ground (see Tables CP15, CP16). The 2017 PIF Report was adopted at the beginning of September 2018, and effectively shifting from reactive to proactive detections based on risk analysis can take time. In addition, non-fraudulent irregularities that are detected and corrected at the national level before the expenditure is included in a statement submitted to the Commission for reimbursement do not have to be reported in the irregularity management system (IMS) (which is the source for this report). Therefore, if risk analysis has a higher impact in detecting these irregularities ‘earlier’, Tables CP15-CP16 would not capture this. On the other hand, this exception does not apply to fraudulent irregularities, which Member States should always report, even if they detect the irregularities before they submit the expenditure to the Commission.

Table CP15 focuses on fraudulent irregularities detected through a check that started because of reasons that can be linked to the recommendations mentioned above. It compares the situation between 2007 and 2017 (before the recommendation) with the situation in 2018-2020 (after the recommendation). On the one hand, Table CP15 does not show any significant change in the use of risk analysis or in the use of information published by the media 32 . On the other hand, it shows a noticeable increase in the share of fraudulent irregularities detected through tips (from 7% to 21%). Tips from informants, whistle-blowers, etc. helped to detect irregularities especially in Hungary, Czechia, Spain, Poland and Portugal 33 .

As shown by Table CP16, the share of non-fraudulent irregularities detected following risk analysis (in the strict sense) rose from 1% to 5%. However, about 84% of non-fraudulent irregularities detected through risk analysis in 2018-2020 were reported by Poland and Czechia, which were also among the ‘strong performers’ before the recommendation. The situation was more stable with the use of tips or information from the media.

4.5.Antifraud and control activities by Member States 

Previous sections have examined the trend and main characteristics of the reported irregularities. The present section aims to exame some aspects linked to the anti-fraud and control activities and results of Member States. Four elements are taken into account:

·duration of irregularities (fraudulent and non-fraudulent). No analysis by Member State is presented in this section;

·the number of irregularities reported as fraudulent by each Member State;

·the ratio between the amounts involved in cases reported as fraudulent and the payments that occurred in relation to PP 2014-20 (FDR) and the ratio between the amounts involved in cases not reported as fraudulent and the payments that occurred in relation to PP 2014-20 (IDR); 34

·the follow-up given to suspected fraud.

4.5.1.Duration of irregularities 

With reference to the cohesion and fisheries policies, of the 47 042 irregularities (fraudulent and non-fraudulent) reported by Member States (and the UK) in relation to the PP 2007-13 and PP 2014-2020, 23 769 (51% of the total) had been occuring over a period of time. For the 2 458 irregularities reported as fraudulent, this percentage was higher, at 60%. The remaining part of the dataset refers to irregularities that consisted of a single act identifiable on a precise date (about 25% of the whole dataset and 31% of the fraudulent irregularities) or for which Member States have not provided any reliable information. 35 The average duration of the irregularities that occurred over a period of time was 20 months (1 month longer than for fraudulent irregularities).

The average duration of the different phases a case can go through, from perpetration to case closure, was analysed in detail in the framework of the 2018 PIF Report 36 . This analysis has not been replicated for this annual report. However, it is worth recalling some of the findings for PP 2007-2013, which has already gone through the full implementation cycle. Both for fraudulent and non-fraudulent irregularities, on average, it took nearly two and a half years to suspect that an irregularity had been or was being perpetrated. Once the suspicion arose, the Member State detected the irregularity in less than half a year. Then the irregularity was reported to the Commission only 8 months after detection. The only significant difference between fraudulent and non-fraudulent irregularities was in the average time from the reporting to the Commission to the case closure, which was much longer for the irregularities reported as fraudulent compared to the non-fraudulent ones. This delay is consistent with the longer duration of criminal proceedings and is also reflected in the procedures for imposing santions or penalties. They started after a similar time period after detection (8 and 10 months for fraudulent and non-fraudulent irregularities, respectively), but then it took, on average, 1 year to close the procedure in case of a non-fraudulent irregularity and nearly 2 years in case of a fraudulent irregularity. This may be due to overlaps with the criminal procedure.

4.5.2.Detection of irregularities reported as fraudulent by Member State 

Map CP3 shows the number of irregularities each Member State reported as fraudulent for PP 2014-2020. In Map CP3, the darker the Member State, the higher the number of detections.

In previous PIF reports, maps and tables for PP 2007-2013 were also included. For fraudulent irregularities, the map in the 2019 PIF Report 37 was based on 1 877 cases, while the new map would be based on 1 856 cases. In no Member State does the difference exceed 10 irregularities, with the exception of Slovakia (-13) 38 . For non-fraudulent irregularities, the map in the 2019 PIF Report was based on 36 057 cases, while the new map would be based on 36 280 cases. The difference exceeds 3% in only two Member States (Croatia, +11%, Hungary, +6%) 39 . For this reason, as from this report, the maps and the tables focusing on PP 2007-2013 will no longer be included.

Past analysis based on PP 2007-2013 suggested that the concentration of detections is not fully explained by the concentration of payments 40 . The outcome of that analysis could be due to many different factors, including different underlying levels of irregularities and fraud, differences in the quality of prevention or detection work or different practices concerning the stage of the procedure when potentially fraudulent irregularities were reported. This analysis found that the divergence between the distributon of detections and the distribution of payments among Member States was smaller for the cohesion and fisheries policies than for CAP, especially in the case of fraudulent irregularities. This could suggest that when it come to cohesion and fisheries policies Member States take a more similar approach to criminal investigation and prosecution to protect the EU budget or to report suspected fraud than when it comes to agriculture.

4.5.3.Fraud detection rate

The fraud detection rate (FDR) compares the results obtained by Member States in the fight against fraud with the payments they received. Given the multi-annual nature of cohesion programmes, focus is on the whole PP 2014-2020.

Table CP17 shows data on fraud detection in the Member States for PP 2014-2020. For reference purposes, the FDR for PP 2007-2013 is also included in the table. These two FDRs cannot be directly compared. While PP 2007-2013 has already gone through the whole implementation cycle, data for PP 2014-2020 are expected to change as implementation progresses. If the trend of the previous programming period is confirmed, most of the fraudulent irregularities are still to be detected. The increase in the financial amounts involved in irregularities will be at least partly counterbalanced by the increase in the payments made to the Member States. 41  

The huge FDR recorded by Slovakia (15%) is due to three irregularities, accounting for about EUR 850 million. These irregularities also have a strong impact on the EU-27 FDR, which is higher than in PP 2007-2013. In Romania, the FDR exceeded 1%, while it was over 0.1% in Latvia, Denmark, Sweden, Hungary, France, Greece and Poland. In the other Member States, the FDR was still close to zero. Comparison with the values consolidated for PP 2007-2013 suggests that the FDRs for PP 2014-2020 are likely to change significantly in the coming years.

4.5.4.Irregularity detection rate

This section focuses on the irregularity detection rate (IDR), which compares the results obtained by Member States in detecting non-fraudulent irregularities with the related payments.

Slovakia recorded the highest IDR, at 6.5%. In line with the general deep decrease in non-fraudulent irregularities reported, the IDR is above 1% only in Bulgaria. It is between 0.5% and 1% in Austria, Estonia, Romania, Lithuania and Croatia. In all other Member States, IDR is below 0.5%. 

4.5.5.Follow-up to suspected fraud (programming period 2007-2013)

In the 2019 PIF Report, a new analysis of the follow-up Member States give to suspected fraud has been introduced. This analysis considers the irregularities that have been reported as suspected fraud between 2007 and 2013 and looks at whether these irregularities have been dismissed, they are still pending as suspected fraud or they have been confirmed as established fraud. The details of the methodology for this analysis can be found in the 2019 PIF 42 .

Table CP19 includes the update of the dismissal ratio, the established fraud ratio and the pending ratio. The dismissal ratio gives the percentage of fraudulent irregularites that have been reclassified as non-fraudulent during their lifetime, until the end of 2020 43 . The established fraud ratio gives the percentage of fraudulent irregularites that were classified as established fraud by the end of 2020 44 . The pending ratio gives the percentage of fraudulent irregularities that were still classified as suspected fraud at the end of 2020 45 . The sum of these three percentages is 100%.

Similar to 2019, 25% of the irregularities reported as fraudulent were dismissed. Another 60% of these irregularities were still pending, but for about one fourth of them no change in status is expected. This is due to the fact that 25% of the irregularities that were still labelled as suspected fraud at the end of 2020 were already closed. This points to a significant underestimation of the dismissal ratio, which could already be considered about 40%, with the potential of exceeding 80%, if most of the pending cases of suspected fraud are dismissed.

The dismissal ratio varied between Member States. High dismissal ratios, especially when associated with high pending ratios, may be due either to the detection phase or to the investigation/prosecution phase. Low dismissal ratios may be positive, but they may also be the result of many irregularities still pending. After 7 years following the end of the period under consideration, the dismissal ratio was zero or very low in many Member States. This indicator must be read in combination with the pending ratio. The latter points to the possibility that the dismissal ratio increases in the future (depending on the number of pending cases that are still open) or to an underestimation of the dismissal ratio (depending on the number of pending cases that are already closed).  

The cases of established fraud were few. This may point to the need to further invest in the investigation/prosecution phase. For the EU-27 level, the established fraud ratio was about 15%. It ranged from zero or about zero, in nearly half of the Member States, to 45%, in Germany. The established fraud ratio is not likely to increase significantly because, while 60% of the cases are still classified as suspected fraud (pending ratio), about 25% of them are already closed and, in any case, between 7 and 14 years have already passed since the detection of the irregularity.

4.6.Other internal policies

Other Funds are used under shared management to finance other internal policies. Tables CP20 and CP21 provide an overview of all the irregularities and related financial amounts reported by the Member States up to 2020 with reference to the:

·Asylum, Migration and Integration Fund (AMIF): This Fund was set up for the period 2014-2020, with a total envelope of EUR 7.7 billion. It is meant to promote the efficient management of migration flows and the implementation, strengthening and development of a common EU approach to asylum and immigration. The largest proportion of the AMIF (approximately 62%) is channelled through shared management. Member States implement their multiannual national programmes, which the responsible national authorities prepare, implement, monitor and evaluate, in partnership with the relevant stakeholders in the field, including the civil society. All Member States except Denmark participate in the Fund’s implementation. Beneficiaries of the programmes implemented under the AMIF include state and federal authorities, local public bodies, non-governmental organisations, humanitarian organisations, international organisations and public law companies and education and research organisations.

·Fund for European Aid to the Most Deprived (FEAD): Over EUR 3.8 billion are earmarked for this Fund for the period 2014-2020. The FEAD supports Member States in providing material assistance to the most deprived, including food, clothing and other essential items for personal use. Material assistance has to go hand in hand with social inclusion measures, such as guidance and support to help people out of poverty. National authorities may also support non-material assistance to the most deprived people to help them integrate better into society. Following the Commission's approval of national programmes, national authorities decide on the delivery of the assistance through partner organisations (public bodies or often non-governmental organisations).

· European Globalisation Adjustment Fund (EGF): This Fund provides support to people who lose their jobs as a result of major structural changes in world trade patterns due to globalisation or as a result of the global economic and financial crisis. The EGF has a maximum annual budget of EUR 150 million for the period 2014-2020. It can fund up to 60% of the cost of projects designed to help workers made redundant find another job or set up their own business. EGF cases are managed and implemented by national or regional authorities. Each project runs for 2 years.

·Internal Security Fund (ISF): This Fund was set up for the period 2014-2020, with a total envelope of EUR 4.2 billion. The Fund promotes the implementation of the internal security strategy, law enforcement cooperation and the management of the EU's external borders. The 2014-2020 ISF is composed of two instruments, ISF Borders and Visa (B&V) and ISF Police. For the 2014-2020 period:

oEUR 3 billion is available to fund actions under the ISF B&V instrument, of which EUR 2.4 billion are to be channelled through shared management. All Member States except Ireland participate in the implementation. The United Kingdom also does not participate;

oabout EUR 1.2 billion is available to fund actions under the ISF Police instrument, of which EUR 754 million are to be channelled through shared management. All Member States except Denmark participate in the implementation. The United Kingdom also does not participate.

·Youth Employment Initiative (YEI): While supporting the Youth Guarantee, the YEI is aimed at young people who are not in education, employment or training (NEETs), including the long-term unemployed or those not registered as job-seekers. It ensures that in parts of Europe where the challenges are most acute, young people can receive targeted support. The YEI’s total budget is EUR 8.8 billion for the period 2014-2020. Of the total budget of EUR 8.8 billion, EUR 4.4 billion comes from a dedicated youth employment budget line, which is complemented by another EUR 4.4 billion more from ESF national allocations.

The FEAD was the Fund most affected by fraud. Financial amounts involved in these irregularities tend to be high. More than half of the irregularities reported as fraudulent were related to the FEAD and they represented 88% of the irregular financial amounts. The average financial amounts of these cases was nearly EUR 1 million and this was not due just to one case; 6 out of 8 cases ranged between about EUR 850 000 and EUR 1.8 million.

More than 90% of the detections of non-fraudulent irregularities were related to the following Funds: AMIF, the FEAD and the YEI. After a slight decrease in 2019, the number of AMIF irregularities increased in 2020, exceeding also the level reached in 2018. The Commission redoubled efforts in the monitoring process with the responsible authorities to support beneficiaries with relevant guidance and information on the legality and regularity of the expenditure. The reporting of FEAD irregularities has been fluctuating during the period, with higher financial amounts involved than with the AMIF. However, half of the irregular financial amounts were associated with the YEI. 

Main Findings

Fraudulent irregularities

Between 2016 and 2020, fraudulent irregularities for PP 2007-2013 decreased, following known trends and patterns, due to the implementation cycle of this closed programming period. Reporting for PP 2014‑2020 was on an increasing trend.

The financial amounts in both fraudulent and non-fraudulent irregularities are more subject to fluctuations because individual cases may involve high amounts. The amounts are also influenced by different reporting patterns in the Member States. For PP 2007-2013, after financial amounts involved in fraudulent irregularities fell significantly, in 2020 they rebounded. This was mainly due to two large irregularities reported by Italy and Romania. For PP 2014-2020, the financial amounts have been rather subdued, apart from a few huge irregularities reported by Slovakia (two ERDF cases, in 2018 and one CF case, in 2019). The acceleration in 2020 was due to five big cases reported by Romania (CF).

ERDF was the Fund most affected by fraud. The number of irregularities reported as fraudulent jumped in 2015. Since then, the number of fraudulent irregularities has fluctuated around the new, higher level. This was possible because the drop in new cases for PP 2007-2013 was offset by the rise in irregularities detected for PP 2014-2020.

After a decrease in 2017, the number of ESF fraudulent irregularities was rather stable. Detections for PP 2007-2013 have been slowly decreasing while detections for PP 2014-2020 have been slowly increasing. The financial amounts recorded an extraordinary increase in 2018, due to an irregularity Portugal reported.

Since 2010, potential fraud affecting the CF is regularly reported. In 2020, the majority of detections took place in Romania, while in 2018 it was Slovakia reporting most cases.

Non-fraudulent irregularities

Between 2016 and 2020, the number of irregularities and financial amounts for PP 2007-2013 significantly decreased, in line with the multiannual nature of structural programmes, which were already closed in 2015. This trend was common to all Funds. However, in 2020, the financial amounts increased, also because of two large CF irregularities reported by Slovakia and two big ERDF cases reported by Romania and Slovakia.

Since 2016, detections and irregular financial amounts for PP 2014-2020 have been on an increasing trend, but less steep than it could be expected given the experience of the previous programming period. In 2020, some Funds even experienced a decrease, either in terms of numbers or financial amounts. However, the drop in the financial amounts for the CF was due to the peak created in 2019 by two large irregularities reported by Slovakia.

Is reporting for PP 2014-2020 in line with past trends?

Apart from outliers, the number and financial amounts reported as fraudulent for PP 2014-2020 were in line with those detected for PP 2007-2013 after a comparable period from the start of the programming period.

Focusing instead on the non-fraudulent irregularities, the fall in the number and financial amounts reported after 7 years from the start of the programming period is striking and can hardly be explained by delayed implementation. The gap is significant for all Funds, but in particular for the ERDF.

A number of rules changed from PP 2007-2013 to PP 2014-2020. For example, under PP 2014-2020, the managing authorities had to put in place effective and proportionate anti-fraud measures, taking into account the risks identified. The introduction of the annual accounts might have helped to strengthen internal control at Member State level. Wider use of simplified cost options (SCOs) might be contributing to the decline in non‑fraudulent irregularities for ESF, but only for the ESF and also for this Fund the situation should still be closely monitored.

Further analysis by the compentent authorities in the Member States is warranted to understand the causes of these declining trends. The different Member States should properly evaluate the actual relevance and impact of these and other changes in their specific context. If different rules/prevention activities from those of the previous programming period are assessed as relevant, the measures that brought these huge changes should be highlighted. If the decline is due to less enforcement or to reporting issues, Member States should act upon these shortcomings in a timely manner.

Detection rates by objective, after a full implementation cycle

For PP 2007-2013, the FDR was 0.4% and the IDR was 2.4%. On average, 5 out of 100 irregularities and 15 out of 100 euro were reported as fraudulent.

The highest FDR and IDR were associated with the objective ‘Fisheries’. Measures for productive investments in aquaculture and investments in processing and marketing were among the riskiest operations. Technical assistance and the development of new markets and promotional campaigns were also particularly vulnerable.

The objective ‘Convergence’ ranked second, in terms of detection and incidence of fraud. ‘European Territorial Cooperation’ programmes showed a peculiar behaviour: while detection was by far the lowest, the incidence of fraud was high.

The priorities most affected

The operational programmes financed under the EU cohesion policy are implemented along identified priorities. For PP 2014-2020, the quality of reporting by the Member States improved, as the number of cases where the priority was actually specified significantly increased, in comparison with PP 2007-2013. However, Member States often continued to report irregularities with the priorities that were valid for PP 2007-2013, but no longer valid for PP 2014-2020.

During PP 2014-2020, research, technological development, innovation and entrepreneurship projects continued to be the most affected by fraudulent irregularities. Compared with PP 2007-2013, Member States are reporting an increasing number of fraudulent irregularities with measures to improve employability. Also, irregularities with infrastructure to provide basic services to citizens (such as energy, environment, transport and ICT) and social, health and education infrastructure increased. This was the case also for social inclusion projects.

For non-fraudulent irregulaties, the overall drop in the number of cases from PP 2007-2013 to PP 2014-2020 had an obvious impact on single priorities. However, RTD, innovation and entrepreneurship, together with the ‘Development of endogenous potential’ remained the priorities most affected by irregularities. The highest financial amounts were associated with infrastructure projects providing basic services, in particular TEN-T motorways and roads (core network).

Focus on the health sector

Investment in health infrastructure was affected by fraud and irregularities, both during PP 2007-2013 and PP 2014-2020. During these two programming periods, the Member States detected about EUR 10 million in irregular financial amounts that were fraudulent and EUR 108 million in irregular financial amounts that were non-fraudulent. The average amounts involved in the fraud exceeded EUR 500,000 per case, much more than the irregular funding in an average non-fraudulent case. With regard to fraud, the Member States with the highest number of detections and irregular financial amounts were Slovakia, Romania and Czechia. Reporting of non-fraudulent irregularities was more widespread, with Poland leading in terms of numbers and Slovakia in terms of financial amounts. Actions related to health infrastructure are strongly affected by violations of public procurement rules.

Projects to improve a country’s health infrastructure are complex, requiring the procurement of services, works, and supplies of medical and ordinary equipment. Based on how irregularities have affected projects of this type in the past, a wide range of potential risks can be identified. However, future scenarios will have to consider that the COVID-19 crisis increases the risks of irregularities and fraud, basically because of urgent spending through simplified procedures.

Follow-up on the recommendation to improve detection capabilities

In the antifraud cycle, being able to detect fraud and irregularities is a key feature, which helps make the system effective and efficient in protecting of the EU budget. In the 2017 PIF Report, the Commission recommended that Member States better exploit the potential of risk analysis. In addition, the Commission recommended making greater use of spontaneous reporting of potential irregularities and strengthening the protection of whistle-blowers, who are also a crucial source for investigative journalism. So far, there has been little improvement on the ground.

On the detection of fraudulent irregularities, there was no significant change in the use of risk analysis or information published by the media. There was a noticeable growth in the percentage of fraudulent irregularities detected through tips, but 90% of these cases were reported by five Member States.

The share of non-fraudulent irregularities detected through risk analysis rose, but more than 80% of the relevant cases were reported by two Member States, which were among the ‘strong performers’ also before the recommendation. There are no indications that the use of risk analysis is actually spreading. The use of tips and the use of information from the media were stable.

Duration of irregularities

Considering PP 2007-2013 and PP 2014-2020 together, 51% of the irregularities occurred over a period of time (60% of the fraudulent irregularities), with an average duration of 20 months (1 month longer than for fraudulent irregularities).

The average duration of the different phases a case can go through, from perpetration to case closure, has been analysed for PP 2007-2013, which has already gone through the full implementation cycle. On average, it took nearly two and a half years to suspect that an irregularity had been or was being perpetrated. Once the suspicion arose, the Member States detected the irregularity in less than half a year. They then reported the irregularity to the Commission only 8 months after detecting it. The only significant difference between fraudulent and non-fraudulent irregularities was in the average time from reporting them to the Commission to closing the case, which took much longer for the irregularities reported as fraudulent compared to the non-fraudulent ones. This delay is consistent with the longer duration of criminal proceedings.

Anti-fraud activities of Member States

Past analysis based on PP 2007-2013 suggests that the concentration of detections was not fully justified by the concentration of payments. The outcome of that analysis could be due to many different factors, including different underlying levels of irregularities and fraud, differences in the quality of prevention or detection work or different practices concerning the stage of the procedure when potentially fraudulent irregularities were reported.

FDR and IDR for PP 2014-2020 are still ‘immature’ and cannot be directly compared with those for PP 2007-2013. If the trend of the previous programming period is confirmed, most of the irregularities for PP 20014-2020 are still to be detected. The increase in the financial amounts of irregularities will be at least partly counterbalanced by the increase in payments made to the Member States.

For 2014-2020, the huge FDR recorded by Slovakia (15%) is due to three irregularities, accounting for about EUR 850 million. In Romania, the FDR exceeded 1%, while it was over 0.1% in Latvia, Denmark, Sweden, Hungary, France, Greece and Poland. In the other Member States, the FDR was still close to zero. Slovakia recorded the highest IDR, at 6.5%. In line with the general deep decrease in non-fraudulent irregularities reported, the IDR is above 1% only in Bulgaria. It is between 0.5% and 1% in Austria, Estonia, Romania, Lithuania and Croatia. In all other Member States, IDR is below 0.5%.

Analysis suggests that the dismissal ratio is high and underestimated. About 60% of the irregularities reported as fraudulent were still pending. However, for about one fourth of them no change in status is expected, because the cases are closed. The cases of established fraud were few. This may point to the need to invest further in the investigation/prosecution phase. 

Other shared management funds

Concerning shared management Funds to finance other internal policies, the FEAD was the Fund most affected by fraud. Financial amounts involved in these irregularities tend to be high, as the average financial amounts of these cases was nearly EUR 1 million.

More than 90% of the detections of non-fraudulent irregularities were related to the following Funds: AMIF, the FEAD and the YEI. After a slight decrease in 2019, the number of AMIF irregularities increased in 2020, exceeding also the level reached in 2018. The reporting of FEAD irregularities has been fluctuating during the period, with higher financial amounts involved than for the AMIF. Half of the irregular financial amounts were associated with the YEI.

5.PRE-ACCESSION POLICY

Executive Summary

Irregularities reported during the period 2016‑2020 in relation to pre-accession occurred in connection with funds distributed under Pre-accession Assistance (2000-2006, PAA), the Instrument for Pre-accession Assistance I 2007-2013 (IPA I) and the Instrument for Pre-accession Assistance II 2014-2020 (IPA II). About 19% of these irregularities were reported as fraudulent. This percentage (fraud frequency level – FFL) changed over time, increasing in 2019 and peaking in 2020 at 29%. In 2020, more than 70% of cases and related financial amounts were reported by Turkey.  

The most recent non-fraudulent irregularities related to PAA were reported in 2019, while the latest fraudulent irregularities were detected in 2018. This is in line with the implementation cycle of the PAA programmes, which covered the period 2000-2006. Since 2000, 14 beneficiary countries have reported 3 268 irregularities (accounting for EUR 410 million). The three most affected funds were SAPARD (rural development), PHARE (institution building, cohesion and cross border cooperation) and ISPA (large infrastructure). In terms of financial amounts, ISPA was more affected than PHARE, even though ISPA accounted for fewer irregularities. This is in line with the larger size of the projects funded by ISPA. Most of the irregularities related to SAPARD were reported by Romania, followed by Bulgaria and Poland. Most of the irregularities related to PHARE were more evenly split between Romania and Bulgaria. Reporting from Romania accounted for the bulk of irregularities related to the ISPA programme.

About 75% of the irregularities reported during the past 5 years were still related to IPA I, although the number of such irregularities fell markedly in 2020. The fraud frequency level was 19% over the past five years, although in 2019 and 2020 it exceeded 30%. Since 2007, 10 beneficiary countries have reported 824 irregularities (accounting for EUR 74 million). The highest number of irregularities concerned IPARD (the successor of SAPARD for rural development), with nearly 90% of the irregularities detected by Turkey. Only two other countries, Croatia and North Macedonia, reported IPARD cases. A broader range of countries reported irregularities concerning cross border cooperation; this was the second most affected component of IPA I. The majority of these irregularities were reported by Bulgaria. Turkey reported nearly 80% of the irregularities related to human resources development (HRD) programmes, the third most affected component of IPA I.

2017 saw the start of irregularities reporting for IPA II. The number of irregularities reported fell markedly in 2020. During the past 4 years, the fraud frequency level was 18%, similar to the FFL for IPA I. The two main contributors to detection were Turkey and North Macedonia, which together reported more than 80% of irregularities and financial amounts. More than 80% of the 146 irregularities related to IPA II (accounting for EUR 3 million) concerned IPARD. The only other component with more than 10 irregularities was cross border cooperation. Most of these irregularities were detected by Bulgaria, followed by Romania.

5.1.Introduction

Section 5 presents a statistical evaluation of irregularities and fraud detected by the beneficiary countries during 2020 with reference to the pre-accession policy. It places these detections in the context of past years and relevant programming periods.

The EU provides pre-accession assistance to candidate countries and potential candidates for EU membership to support them in meeting the accession criteria and to bring their institutions and standards in line with the EU acquis 46 . The current candidate countries are Albania, Montenegro, North Macedonia, Serbia and Turkey; potential candidates are Bosnia and Herzegovina and Kosovo 47 .

In the whole report, when reference is made to ‘fraudulent’ or ‘fraud’, it includes ‘suspected fraud’ and ‘established fraud’.

5.2.Instruments for Pre-accession Assistance 

5.2.1.Before 2007: Pre-accession Assistance (PAA) 

Before 2007, the EU provided pre-accession assistance to candidate countries through a number of separate instruments. The PHARE programme provided support for institution-building measures and associated investment, as well as funding measures to promote economic and social cohesion and cross border cooperation. The ISPA programme dealt with large-scale environmental and transport infrastructure projects, while the SAPARD programme supported agricultural and rural development. For the programme years 2002‑2006, Turkey received assistance under the specific pre-accession-oriented framework of the Pre‑accession Financial Assistance for Turkey (TIPAA). The CARDS programme was the main financial instrument to promote stability in the Western Balkans and facilitate the region’s closer association with the EU. The countries that joined the EU in 2004 48 received a Transition Facility (TF) in 2004-2006, as did Bulgaria and Romania in 2007-2010. All pre‑2007 programmes and projects have been completed 49 .

5.2.2.2007-2013: The Instrument for Pre-accession Assistance (IPA I)

For the period 2007-2013, the EU supported reforms in the ‘enlargement countries’ (i.e., the candidate countries Albania, Montenegro, North Macedonia, Serbia, and Turkey and potential candidates Bosnia and Herzegovina and Kosovo), providing financial and technical help via the Instrument for Pre-accession Assistance (IPA I) 50 . IPA I funds built up the capacities of these countries throughout the accession process. IPA I had a budget of about EUR 11.5 billion and consisted of five components 51 .

The five components of IPA I were: (i) transition assistance and institution building (TAIB); (ii) cross border cooperation (CBC); (iii) regional development (transport, environment and economic development) (REGD); (iv) human resource development (strengthening human capital and combatting exclusion) (HRD); and (v) rural development (IPARD). Candidate countries were eligible for all five components; potential candidates were eligible only for the first two 52 .

The policy and programming of IPA I consisted of (i) multiannual indicative financial framework on a three-year basis, established by country, component and theme; and (ii) multiannual indicative planning documents per country or per groups of countries (regional and horizontal programmes). The candidate countries also had to submit strategic coherence frameworks and multiannual operational programmes for the third and fourth component. Their principal aim was to prepare beneficiary countries for the future use of cohesion policy instruments by closely imitating its strategic documents, national strategic reference framework and operational programmes, and management modes.

5.2.3.2014 – 2020: The Instrument for Pre-accession Assistance (IPA II) 

For the period 2014-2020, IPA II built on the results achieved under IPA I and set a new framework for providing pre-accession assistance. The primary innovation of IPA II is its strategic focus on specific objectives. The multiannual financial framework for 2014-2020 allocated EUR 11.7 billion for the instrument 53 .

Financial assistance under IPA II pursues four specific objectives: (i) support for political reforms; (ii) support for economic, social and territorial development; (iii) strengthening the beneficiaries’ ability to fulfil (future) obligations stemming from EU membership by supporting progressive alignment with the EU acquis; and (iv) strengthening regional integration and territorial cooperation. The IPA II Regulation limits financial assistance to five policy areas: (i) reforms in preparation for EU membership and related institution-and capacity-building; (ii) socio-economic and regional development; (iii) employment, social policies, education, promotion of gender equality, and human resources development; (iv) agriculture and rural development; and (v) regional and territorial cooperation.

To provide an individual implementation framework for each beneficiary, country strategy papers were drafted, identifying sectors where improvements were necessary to advance membership goals. The priorities outlined in these papers were translated into detailed actions, included in annual or multiannual action programmes that take the form of financing decisions adopted by the European Commission.

The bulk of IPA II assistance is channelled through the country action programmes; these are the main vehicles for addressing country-specific needs in priority sectors as identified in the indicative strategy papers. Additionally, IPA II funded multi-country action programmes to enhance regional cooperation, particularly in the Western Balkans. Financial assistance was also provided via cross border cooperation programmes to encourage territorial cooperation between IPA II beneficiaries and via rural development programmes to encourage the development of rural areas.

In accordance with the Financial Regulation, IPA II-funded activities are managed either directly (meaning that the Commission implements them directly until the relevant national authorities are accredited to manage the funds) or indirectly (meaning that the Commission delegates the management of certain actions to external entities, while still retaining overall final responsibility for the general budget execution). Cross border cooperation programmes with Member States are administered via shared management, meaning that implementation tasks are delegated to the Member States.

5.3.General analysis

This section focuses on the 698 irregularities reported during the period 2016‑2020, in relation to pre-accession funds. These irregularities occurred in connection with funds distributed under the 2000-2006 PAA 54 and under IPA I and IPA II 55 . This is further explored in Sections 5.4, 5.5 and 5.6 56 .

Table PA1 (and the related graph) shows all the fraudulent and non-fraudulent irregularities detected by the beneficiary countries during the past 5 years under pre-accession programmes. About 19% of these irregularities were reported as fraudulent. This percentage (the fraud frequency level – FFL) changed over time, increasing in 2019 and peaking in 2020 at 29%.

For 2020, irregularities were reported by Romania and five other beneficiary countries (see Table PA2). More than 70% of these cases and related financial amounts were reported by Turkey. As mentioned, the global fraud frequency level in 2020 was 29%, ranging from 33% in Serbia to 0 in Albania and Montenegro. When focus is on the financial amounts, the differences were even greater. Here, comparison is based on the share of financial amounts reported as fraudulent (fraud amount level – FAL). North Macedonia recorded the highest FAL, at 94%, while Turkey accounted for the lowest, at 27% (apart from Albania and North Macedonia, which reported no fraudulent cases and Romania, which reported one case but without specifying of the financial amounts involved).

5.4.Pre-accession Assistance (PAA 2000-2006)

5.4.1.Recent trends

The most recent non-fraudulent irregularities related to PAA were reported in 2019, while the latest fraudulent irregularities were detected in 2018. During the past 5 years, the beneficiary countries reported just 21 irregularities, where about EUR 3 million were involved (see Table PA3 and related graph).

5.4.2.Recent trends by component 

The 21 irregularities related to PAA reported during the past 5 years concerned four components. These irregularities were evenly split among ISPA, TIPAA, PHARE and SAPARD. ISPA accounted for the highest number of irregularities (together with TIPAA) and the highest financial amounts (see Table PA4).

5.4.3.Recent trends by beneficiary country

The 21 irregularities related to PAA reported during the past 5 years were evenly split among three countries: Romania, Bulgaria and Turkey. The highest financial amounts were reported by Bulgaria (see Table PA5).

5.4.4.Trends since the start of PAA, by beneficiary country and component

Table PA6 and related graph show the number of irregularities and related financial amounts concerning PAA since 2000, by beneficiary country and component.

Since 2000, 14 beneficiary countries have reported 3 268 irregularities related to six components. The three most affected components were SAPARD, PHARE and ISPA. In terms of financial amounts, ISPA was more affected than PHARE, even though ISPA accounted for fewer irregularities. The PHARE programme provided support for institution building, as well as for promoting economic and social cohesion and cross border cooperation. The ISPA programme dealt with large-scale environmental and transport infrastructure projects. This contributed to the higher financial amounts involved in the irregularities related to ISPA.

Most of the irregularities related to SAPARD (rural development) were reported by Romania, followed by Bulgaria and Poland. Most of the irregularities related to PHARE were more evenly split between Romania and Bulgaria. Reporting from Romania accounted for the bulk of irregularities related to the ISPA programme (see Table PA6 and related graph).

5.5.Instrument for Pre-Accession Assistance (IPA I, 2007-2013)

5.5.1.Recent trends

Most of the irregularities reported during 2016-2020 were still related to IPA I (531 out of 698), although the number of these irregularities fell markedly in 2020. The FFL was 19% during the past 5 years, although in 2019 and in 2020 it exceeded 30%. The number of detections of fraudulent irregularities was particularly high in 2019 (see Table PA7 and related graph).

5.5.2.Recent trends by component 

The 531 irregularities related to IPA I during the past 5 years concerned five components. By far, the highest number of cases and the highest financial amounts concerned IPARD, the successor of SAPARD supporting agriculture and rural development.

5.5.3.Recent trends by beneficiary country

During the past 5 years, irregularities related to IPA I were reported by nine countries. The leading contributor to detection was Turkey, which reported about 70% of irregularities and 90% of the financial amounts.

5.5.4.Trends since the start of IPA I, by beneficiary country and component

Table PA10 and related graph show the number of irregularities and related financial amounts concerning IPA I since 2007, by beneficiary country and component.

Since 2007, 10 beneficiary countries reported 824 irregularities related to five components. The highest number of irregularities concerned IPARD. Nearly 90% of the irregularities related to IPARD were detected by Turkey. Only two other countries, Croatia and North Macedonia, reported IPARD cases. A broader range of countries reported irregularities concerning cross border cooperation programmes (CBC-IPA), the second most affected component of IPA I. The majority of irregularities were reported by Bulgaria. The only non-Member State that reported irregularities relating to CBC was Serbia (apart from one irregularity reported by Turkey). Besides reporting most of the IPARD irregularities, Turkey also reported nearly 80% of the irregularities related to the human resources development (HRD) programmes, the third most affected component of IPA I (see Table PA10 and related graph).

5.6.Instrument for Pre-accession Assistance II (IPA II 2014-2020)

5.6.1.Recent trends

The reporting of irregularities relating to IPA II started in 2017. The number of irregularities reported fell markedly in 2020. During the past 4 years, the fraud frequency level was 18%, similar to the FFL for IPA I (see Table PA11 and related graph).

5.6.2.Recent trends by component 

The 146 irregularities related to IPA II during the past 5 years concerned five components. By far, the highest number of cases and the highest financial amounts concerned IPARD.

5.6.3.Recent trends by beneficiary country

During the past 5 years, irregularities related to IPA II were reported by seven countries. The two main contributors to detection were Turkey and North Macedonia, which together reported more than 80% of irregularities and financial amounts.

5.6.4.Trends since the start of IPA II, by beneficiary country and component

Table PA14 and the related graph show the number of irregularities and related financial amounts concerning IPA II, by beneficiary country and component. As reporting for IPA II started in 2017, data for the past 5 years and data from the start of the programmes (2014) coincide.

Since 2014, 7 beneficiary countries reported 146 irregularities related to five components. More than 80% of the irregularities concerned IPARD. Almost all were detected by Turkey and North Macedonia. The only other component with more than 10 irregularities was cross border cooperation. Most of these irregularities were detected by Bulgaria, followed by Romania.

6.Direct Management

6.1.Introduction

This chapter contains a descriptive analysis of the data on recovery orders issued by Commission services in relation to expenditures managed under ‘direct management’ mode, which is one of the three implementation modes the Commission can use to implement the budget.

According to the Financial Regulation, the Commission implements the budget directly (‘direct management’) as set out in Articles 125 to 153, through its departments, including its staff in the Union delegations under the authority of their respective Head of delegation, in accordance with Article 60(2), or through executive agencies as referred to in Article 69 57 .

For the financial year 2020, a total of EUR 26,579 million 58 has been disbursed under ‘direct management’ mode. Table DM1 presents the actual payments by policy areas. Compared to previous years, actual payments are higher, mostly due to increased spending in ‘Migration and home affairs’.

Table DM1 – Payments made in financial year 2020 by policy area

6.2.General analysis

For the financial year 2020, the Commission services registered 1,326 recovery items 59 in ABAC that were qualified as irregularities for a total financial value EUR 62.37 million. Among these recovery items, 41 have been reported as fraudulent, involving EUR 9.15 million irregular amounts.

However, qualifications attributed to recovery items may change over the years: it may happen that cases of irregularities are turned into suspicions of fraud or the other way round, suspicions of fraud are reclassified as non-fraudulent irregularities upon the closure of the OLAF investigation.

6.2.1.Five year analysis 2016-2020

The following analysis gives an overview of recovery data recorded in the ABAC system in the last five years. Between 2016 and 2020, on average, for one year, there were 55 recovery items qualified as ‘irregularities reported as fraudulent’ 60 . The ratio between the financial amounts related to these irregularities and expenditure during 2016-2020 is very small, it remains close to zero (0.042%). This ratio is quite stable throughout the years. Figures are presented in Table DM2 below.

Table DM2 – Irregularities reported as fraudulent and related amounts, financial years 2016-2020

With regard to ‘irregularities not reported as fraudulent’, between 2016 and 2020, on average, for one year, 1,593 recovery items are registered. The figures for 2020 indicate a noticeable decline, both in the number of cases and in the percentage of irregular amount per payments. Figures are presented in Table DM3 below.

Table DM3 – Irregularities not reported as fraudulent and related amounts, financial years 2016-2020

Between 2016 and 2020, in total, there were 7,967 registered recovery items qualified as ‘irregularities not reported as fraudulent’, with an aggregate recovery amount of EUR 307.66 million. The ratio between these aggregate irregular amounts corresponding to the recovery items and expenditure during 2016-2020 is less than 0.3% (see Total in Table DM3). This ratio has been steadily declining for many years now from the zone of 0,5-0,6% (five years ago).

These figures show the efficiency of the irregularity detection and recovery mechanisms in place.

6.3.Specific analysis

6.3.1.Recoveries according policy areas

Table DM4 provides an overview of irregularity statistics by policy area for 2020.

Table DM4 – Irregularities reported by policy areas and related amounts, 2020

In the financial year 2020, the highest numbers of recovery items qualified as 'irregularities not reported as fraudulent' was recorded in the budget area ‘Research and innovation’ (371). It was the ‘Mobility and transport’ policy field where the highest irregular amounts were registered (EUR 12.29 million).

During the same year, 41 recovery items were registered as ‘irregularities reported as fraudulent’. The three policy areas with the highest number of irregularities reported were ‘Research and innovation’ (12 items), ‘Communications networks, content and technology’ (7 items) and ‘Internal market, industry, entrepreneurship and SMEs’ (6 items). EUR 9.15 million were involved in these irregularities, out of which 35% (EUR 3.2 million) were related to the policy area ‘Foreign Policy Instruments’.

Table DM5 presents the overview of irregularity statistics by policy area for the past five years.

Table DM5 – Irregularities reported by policy areas and related amounts, financial years 2016-2020

During 2016-2020, ‘Communications networks, content and technology’ was the policy field with the highest aggregate recovery amounts (EUR 18.2 million) in relation to ‘irregularities reported as fraudulent’. This policy represented more than 40% of the total amounts. It is followed by policy areas ‘International cooperation and development’ (EUR 5.72 million) and ‘Research and innovation’ (EUR 5.32 million), yet with much smaller amounts.

With regard to ‘irregularities not reported as fraudulent’, during 2016-2020, the highest aggregate recovery amounts were recorded in the policy area of ‘Research and innovation’ (EUR 75.35 million). It is followed by ‘Communications networks, content and technology’ (EUR 45.98 million) and then by ‘Mobility and transport’ (EUR 34.95 million). These three policy areas account for more than half (51%) of the total recovery amounts related to ‘irregularities not reported as fraudulent’ over the past five years.

The ratio between the aggregate recovery amounts related to all recovery items and expenditure during 2016-2020 remains very low, on average 0.329% (0.287%+0.042%).

6.3.2.Recoveries according to legal entity residence

During 2016-2020, with regard to ‘irregularities not reported as fraudulent’, 87% of the total number of recovery items and 85% of the related recovery amounts concerned legal entities that are resident of the European Union. However, the residence of the legal entity and the residence of the beneficiary are not necessarily the same. Nevertheless, in 74% of the ‘irregularities not reported as fraudulent’ and 70% of the related amounts, both the main beneficiary and the legal entity concerned were resident in an EU Member State. For ‘irregularities reported as fraudulent’, these ratios are higher: 90% of the total number of recovery items and 91% of the related recovery amounts concerned a legal entity residing in an EU Member State. In 80% of the ‘irregularities reported as fraudulent’ and 71% of the amounts concerned both the final beneficiary and the legal entity concerned are resident in an EU Member State.

Table DM6 – Recoveries per country of residence of the legal entity, 2016-2020

Table DM6 above summarises the total recoveries made during the past five years according to the country of residence of the legal entity to which the payment was unduly made.

6.3.3.Method of detection

For each recovery item, the Commission service issuing the recovery order has to indicate how the irregularity has been detected. Six different categories are pre-defined for this purpose, two of which fall under the direct responsibility of the European Commission: ‘Ex-ante controls’ and ‘Ex-post controls’. Table DM7 provides a breakdown of the recoveries by source of detection and by qualification.

Table DM7 – Irregularities reported by source of detection and by qualification, 2016-2020

With reference to the ‘irregularities reported as fraudulent’, ‘OLAF’ has been mentioned as the source of detection in relation to 75% of recovery items, corresponding to 93% of total recovery amounts. Meanwhile ‘Ex-post controls’ were the source of detection of another 22% of this type of recovery items, corresponding to another 6% of the recovery amounts.

About 85% of ‘irregularities not reported as fraudulent’ were detected through Commission controls (Ex-ante and Ex-post controls). The share of Ex-ante controls has been steadily declining from 30% (five years ago) to 10% (value of the indicator now).

6.3.4.Types of irregularity

The Commission services also have to specify, in the recovery context, the type of irregularity in relation to each recovery item. Several types can be attributed to one recovery item. For ‘irregularities reported as fraudulent’, ‘Amount ineligible’ was the most frequent type during the past five years. In relation to ‘irregularities not reported as fraudulent’, ‘Amount ineligible’ remains the most frequent irregularity type, followed by ‘Under-performance/Non-performance’ and then by ‘Documents missing’.

Table DM8 provides the full picture regarding the frequency of each type during the past five years. The figures are stable and have been following the same pattern for many years.

Table DM8 – Types of irregularity, 2016-2020

6.3.5.Recovery

Once a recovery order is issued, the beneficiary is requested to pay back the amount unduly received or the amount is offset from remaining payments for the same beneficiary.

For the recovery orders issued between 2016 and 2020, 56% of the total irregular amounts have already been recovered. The recovery rate for ‘irregularities reported as fraudulent’ (26%) remains well below the one calculated for ‘irregularities not reported as fraudulent’ (60%).

COUNTRY FACTSHEETS

Belgium - Belgique/België

Bulgaria – България

Czech Republic - Česká republika

Denmark – Danmark

Germany – Deutschland

Estonia – Eesti

Ireland – Éire

Greece – Ελλάδα

Spain – España

France

Croatia – Hrvatska

Italy – Italia

Cyprus – Κύπρος

Latvia – Latvija

Lithuania – Lietuva

Luxembourg

Hungary - Magyarország

Malta

Netherlands - Nederland

Austria – Österreich

Poland – Polska

Portugal

Romania – România

Slovenia – Slovenija

Slovakia – Slovensko

Finland – Suomi-Finland

Sweden – Sverige

Annexes

ANNEX 12

Classification of cases in relation to common agricultural policy expenditure

This Annex describes the methodology adopted for classifying irregularities concerning the common agricultural policy (CAP) in the components ‘rural development’ (RD) and ‘support to agriculture’ (SA). The methodology also covers the classification of the SA irregularities in the two sub-components ‘market measures’ (MM) and ‘direct aid to farmers’ (DA).

For each irregularity related to the common agricultural policy, the competent national authorities should provide the following information in the irregularities management system (IMS):

This methodology is based on the information included in the fields ‘Fund’, ‘Budget line’ and ‘Budget post’. Budget line and budget post are IMS terminology. In the current EU budget, reference is made to chapters (corresponding to the first part of the IMS budget post above) and articles (corresponding to the IMS budget post).

Cases are classified as:

·RD, where they concern only expenditure on IMS budget lines/posts that contain the codes '0504', 'B01-4' or 'B01-50 61 . In addition, it has been considered that there are irregularities where the field 'Fund' refers to the EARDF (European Agriculture Rural Development Fund), even if the budget line/post is not specified.

62 This choice has been made because, since 2004, in the EU budget, expenditure on rural development has been grouped under the budget chapter 0504. Under this, the budget articles B050405 (as from 2007) and B050460 (as from 2014) refer to European Agricultural Fund for Rural Development (EAFRD) funding.

Between 2000 and 2003, rural development was instead financed under budget chapter B01-40 (EAGGF Guarantee Section). The appropriations included in this chapter were intended to cover expenditure on two types of rural development measures: (1) accompanying measures introduced in 1992 supplemented by the less-favoured-areas scheme; and (2) modernisation and diversification schemes.

Before 2000, the EU budget had no explicit reference to rural development, but budget chapter B01-50 (EAGGF Guarantee Section) covered expenditure on accompanying measures, similar to chapter B01-40 in 2000-2003.

·SA, where the IMS budget line/post does not contain RD budget codes 63 . In addition, it has been considered that there are irregularities where the field 'Fund' refers to the European Agriculture Guarantee Fund (EAGF) and the budget line/post is not specified. For these cases, it is not clear whether this expenditure financed rural development (from the EAGGF – Guarantee Section) or SA. To find the best possible classification for these cases, the following assumption has been made. In 2007, the EARDF was created to finance all measures concerning rural development. Consequently, if the budget years associated to an irregularity are from 2007 onwards, it seems to be unlikely that this irregularity is related to rural development, so it is considered SA. If also the budget year is not mentioned, but the programming period mentioned in the relevant field is 2007-2013 or 2014-2020, the irregularity is considered SA. The other irregularities are classified as in the category ‘Blank’ (see below).

SA includes expenditure relating to intervention in agricultural markets and direct payments to farmers.

·'SA/RD', where they concern both types of expenditure (RD and SA budget codes) 64 . In addition, it has been considered that there are irregularities where the field 'Fund' refers to 'EAGF/EARDF', but the budget line/post is not specified. For these cases, it is not clear whether this expenditure financed only rural development (before from the EAGGF – Guarantee Section and then from EARDF) or both rural development (EARDF) and SA (EAGF). To find the best possible classification for these cases, the following assumption has been made. In 2007, the EARDF was created to finance all measures concerning rural development. Consequently, if the budget years associate to an irregularity are from 2007 onwards only, it seems likely that there is also an SA component in the expenditure related to the irregularity (because EAGF is more likely to point to an SA item of expenditure) so the irregularity is considered ‘SA/RD’. If also the budget year is not mentioned, but the programming period is 2007-2013 or 2014-2020, the irregularity is also considered ‘SA/RD’. Other irregularities are classified as ‘Blank’.

·'Blank', where information has not been considered enough to assign the case to RD, SA or SA/RD 65 .

Some parts of the analysis in Section 3 'Common agricultural policy' separately focus on 'interventions in agricultural markets' (or 'market measures') and 'direct payments' (or ‘direct aid’).

In fact, since 2006, the EU budget provides for support to agriculture to be structured along two main budget chapters: 66

·Budget chapter 0502 'interventions in agricultural markets';

·Budget chapter 0503 'direct aids'.

For the purpose of the analysis in Section 3 'Common agricultural policy', cases are classified as:

·'Market measures', where they concern expenditure on IMS budget lines/posts that contain the code '502', as from the 2006 EU budget (NB, the same case may also concern other areas, including rural development or direct payments);

·'Direct payments', where they concern expenditure on IMS budget lines/posts which contain the code '503', as from the 2006 EU Budget (NB, the same case may also concern other areas, including RD or market measures).

Cases concerning only expenditure in 2005 (budget year) or before are not considered 'market measures' or 'direct payments'. Before 2006, the EU budget had a different structure:

·In 2004 and 2005, the budget chapters 0502 and 0503 referred respectively to 'Plant products' and 'Animal products';

·Before 2004, budget subsection B01 covered the Guarantee Section of the EAGG fund and was split, among others 67 , in:

oB01-1 'Plant products';

oB01-2 'Animal products'.

ANNEX 13

Categories of irregularities and related types

This Annex shows the types of violations in the IMS and how they are grouped in categories. These categories are used in used in Tables NR10-NR13 (Section 3).

In Section 4 (Tables CP9, CP10, CP14), other categories are used, as follows:

·Infringements concerning the request: T11/00, T11/01, T11/99

·Eligibility / Legitimacy of expenditure/measure: T11/02

·Multiple financing: T11/03, T11/04

·Violations/breaches by the operator: T12

·Incorrect, absent, falsified accounts: T13

·Incorrect, missing, false or falsified supporting documents: T14

·Product, species and/or land: T15

·Infringement of contract provisions/rules: T16/00, T16/01, T16/02, T16/03, T16/04, T16/05, T16/06, T16/07, T16/09, T16/10, T16/99

·Movement: T17

·Bankruptcy: T18

·Ethics and integrity: T19

·Infringement of public procurement rules: T40, T41, T16/08

·State aid: T50