EUROPEAN COMMISSION

Brussels, 3.9.2018

SWD(2018) 386 final

COMMISSION STAFF WORKING DOCUMENT

Statistical evaluation of irregularities reported for 2017: 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

29th Annual Report on the Protection of the European Union's financial interests - Fight against fraud - 2017

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{SWD(2018) 382 final}
{SWD(2018) 383 final}
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Statistical evaluation of irregularities reported for 2017 Own Resources, Natural Resources, Cohesion Policy, Pre-accession and Direct Expenditure

Contents

1. Introduction    

1.1. Scope of the document    

1.2. Structure of the document    

2. Traditional Own Resources    

2.1. Introduction    

2.2. General analysis – Trend analysis    

2.2.1. Reporting Years 2013-2017    

2.2.1.1. Irregularities reported as fraudulent    

2.2.1.2. Irregularities not reported as fraudulent    

2.2.2. OWNRES data vs TOR collection    

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. Modus operandi    

2.3.1.2. Method of detection of fraudulent cases    

2.3.1.3. Smuggled cigarettes    

2.3.1.4. Cases reported as fraudulent by amount    

2.3.2. Irregularities not reported as fraudulent    

2.3.2.1. Modus operandi    

2.3.2.2. Method of detection of non-fraudulent cases    

2.3.2.3. Solar panels vulnerable to irregularities – mutual assistance    

2.3.2.4. Cases not reported as fraudulent by amount    

2.4. Member States’ activities    

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

2.4.2. Recovery rates    

2.4.2.1. Cases reported as fraudulent    

2.4.2.2. Cases not reported as 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 (CAP)    

3.1.    Introduction    

3.2.    General analysis    

3.2.1.    Irregularities reported 2013-2017    

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 (SA)    

3.3.1.2.    Rural development (RD)    

3.3.2.    Fraud and Irregularity Detection Rates by CAP components    

3.3.3.    Market measures – fraudulent and non-fraudulent irregularities    

3.3.4. Reasons for performing control    

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 activities of 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 in 2017    

3.4.2.2.    Reported during the period 2013-17    

3.4.3.    Fraud and Irregularity Detection Rates by Member State    

3.4.3.1.    Market measures    

3.4.3.2.    Rural development    

3.4.4.    Ratio of established fraud / Dismissal ratio    

3.5.    Recovery cases    

1. Introduction

1.1. Scope of the document

The present document 1 is based on the analysis of the notifications provided by national authorities of cases of irregularities and suspected or established fraud. The 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”.

For this reason, this document should be regarded as an analysis of the achievements of Member States.

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 is dedicated to the analysis of irregularities reported in the area of the Traditional Own Resources (Revenue).

The second part, concerning the expenditure part of the budget, is composed of three sections, dedicated, respectively, to shared, decentralised and centralised management modes.

The section dedicated to shared management, covers agriculture, cohesion policy and fisheries and other internal policies. Decentralised management refers to the pre-accession policy, while the centralised management section mainly deals with internal and external policies for which the Commission directly manages the implementation.

The document is completed by 28 country factsheets, which summarise, for each Member State, the main indicators and information that have been recorded throughout the analyses.

16 Annexes complement the information and data of this document, providing a global overview of the irregularities reported according to the relevant sector regulations. Annexes 1 to 10 concern Traditional Own Resources, Annexes 11 to 15 complement information on the methodology for the analysis of irregularities concerning expenditure, Annex 16 covers all the expenditure sectors for which Member States and beneficiary countries have a reporting obligation.

Part I - REVENUE

2. Traditional Own Resources

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'.

The following analysis is based on the data available on the cut-off date (15 March 2018) and aims to provide an overview of the reported cases of fraud and irregularities reported for 2017 together with their financial impact.

2.2. General analysis – Trend analysis

2.2.1. Reporting Years 2013-2017

The number of cases reported via OWNRES for 2017 (4 636) is about 11% lower than the average number of of irregular cases reported for the 2013-2017 period (5 222).

The total estimated and established amount of TOR involved (EUR 502 million) is about 6 % higher than the average estimated and established amount for years 2013-2017 (EUR 475 million).

In 2017, 3 big 3 cases for a total amount of about EUR 41 million 4 were reported compared to 2016, when 5 big cases with a total amount of about EUR 115 million affected the total estimated and established amount. Luxemburg did not communicate any case exceeding an amount of EUR 10 000.

CHART TOR1: Total number of OWNRES cases and the related estimated and established amount (2013-2017)

Annex 1 of the summary tables shows the situation on the cut-off date (15 March 2018) for the years 2013-2017.

2.2.1.1. Irregularities reported as fraudulent

The number of cases reported as fraudulent registered in OWNRES for 2017 (441) is currently 33% lower than the average number of cases reported for the 2013-2017 period (658).

The total estimated and established amount of TOR involved (EUR 76 million) represents a decrease of 28% of the average estimated and established amount for the years 2013-2017 (EUR 106 million).

For 2017, Luxemburg, Czech Republic and Slovakia did not communicate any fraudulent case exceeding an amount of EUR 10 000.

CHART TOR2: OWNRES cases reported as fraudulent and the related estimated and established amount (2013-2017)

On the cut-off date (15 March 2018), 9.5 % of all cases detected in 2017 were classified as fraudulent. The percentage decreased slightly in comparison to 2016 (11 %).

Annex 2 of the summary tables shows the situation on the cut-off date for years 2013-2017.

2.2.1.2. Irregularities not reported as fraudulent

At the same time, the number of cases not reported as fraudulent communicated via OWNRES for 2017 (4 195) was 8% lower than the average number reported for 2013-2017 (4 564).

The total estimated and established amount of TOR (EUR 425 million) was 15 % higher than the average estimated and established amount for the years 2013-2017 (EUR 369 million).

Luxemburg and Malta did not report any case of irregularity exceeding an amount of EUR 10 000 for 2017.

CHART TOR3: OWNRES cases not reported as fraudulent and the related estimated and established amount (2013-2017)

Annex 3 of the summary tables shows the situation on the cut-off date for years 2013-2017.

2.2.2. OWNRES data vs TOR collection

In 2017, the total established amount of TOR (gross) was EUR 25.6 billion and more than 98% was duly recovered and made available to the Commission via the A-account. According to the OWNRES data, around EUR 502 million has been established or estimated by the Member States in connection with cases reported as fraudulent/non fraudulent where the amount at stake exceeds EUR 10 000.

The total estimated and established amount reported in OWNRES represent 1.96 % of the total collected TOR (gross) amount in 2017 5 . This proportion has decreased compared with 2016 when it was 2.14 % 6 . A percentage of 1.96 % indicates that of every EUR 100 of TOR (gross) established, an amount of EUR 1.96 is registered as irregular (fraudulent or non-fraudulent) in OWNRES.

TOR Map1 shows the estimated and established amount reported in OWNRES as a percentage of the collected TOR (gross) amount, by Member State. Further details can be found in Annex 4. There are differences among the Member States. In 11 Member States 7 , the percentage is above the average of 1.96 %. The highest percentage for 2017 can be seen in Greece, Spain and Hungary with 7.17 %, 4.31 % and 3.35 %.

For the seven 8 Member States which established and made available most of the TOR amounts, the average percentage of the estimated and established OWNRES amounts to established TOR for 2017 was equal to 2.02 %. In comparison with the previous year (2.13%), this represents a decrease of 0.11%. For Belgium, the proportion of estimated and established OWNRES amounts to established TOR increased in 2017 (1.14%) compared to the previous year (0.62%), while for Germany it has increased from 1.39% to 1.80%. For the other five Member States, the average proportion of estimated and established OWNRES amounts to established TOR declined in 2017 (2.28%) compared to the previous year (2.66%).

2.2.3. Recovery

The fraud and irregularity cases detected in 2017 correspond to an established amount of EUR 483 million 9 . Nearly EUR 212 million 10 of this was recovered in cases where an irregularity was at stake and EUR 15 million 11 in fraudulent cases. In total EUR 227 million was recovered by all Member States for all cases which were detected in 2017. In absolute figures, Germany recovered the highest amount in 2017 (EUR 76 million) followed by the UK (EUR 55 million). This is a starting point for the recovery. 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 huge financial impact.

In addition, Member States continued their recovery actions related to the detected cases of previous years.

2.2.3.1. Recovery rates

Over the past five years the annual recovery rate has varied between 44 % and 80 % (see Chart TOR4). The recovery rate for cases reported in 2017 is currently 47 % 12 . In other words, out of every amount over EUR 10 000 of duties established and reported for 2017 in OWNRES as irregular/fraudulent, approximately EUR 4 700 has already been paid.

CHART TOR4: Annual recovery rates (2013-2017)

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

Recovery rates vary among the Member States. The highest recovery rates for 2017 are in Slovenia (100%), Slovakia (98%), Ireland (97%), Finland (88 %), Hungary (87 %), Austria (83%) and Germany (82%). Differences in recovery results may arise from factors such as the type of fraud or irregularity, or the type of debtor involved. It can be expected that the recovery rate for 2017 will also go up in the future.

On the cut-off date (15 March 2018), the overall recovery rate for all years 1989-2017 was 62%.

2.3. Specific analysis

2.3.1. Irregularities reported as fraudulent

2.3.1.1. Modus operandi

A breakdown by types of fraud reveals that incorrect origin or country of dispatching, smuggling of goods, incorrect value or incorrect classification/misdescription are frequently mentioned in 2017 for cases reported as fraudulent.

In 2017, the customs procedure ‘release for free circulation' remained the procedure most vulnerable to fraud (71 % of the number of cases and 67 % of the estimated and established amount). A total of 19 % of all cases reported as fraudulent and 11% of all estimated and established amounts in OWNRES cases registered as fraudulent for 2017 fall under the category "Other" 13 . A total of 7 % of all cases reported as fraudulent and 20 % of all estimated and established amounts in OWNRES cases registered as fraudulent for 2017 involve the transit procedure.

Of all cases reported as fraudulent about 74 % concern such goods as tobacco, electrical machinery and equipment, preparation of foodstuffs, vehicles, textiles and articles of iron and steel. In monetary terms those groups of goods represent about 78 % of all amounts estimated and established for cases reported as fraudulent. China, United States, Ukraine, Switzerland, Turkey and Singapore are the most important - in monetary terms - countries of origin of goods affected by fraud.

2.3.1.2. Method of detection of fraudulent cases

In 2017 14 , inspections by anti-fraud services (43 %) was the most successful method of detecting fraudulent cases followed by customs controls carried out at the time of clearance of goods (23 %) and post-clearance controls (28 %).

CHART TOR5: Method of detection 2017 – Cases reported as fraudulent – by number of cases

In monetary terms, of the EUR 76 million estimated or established in fraudulent cases registered for 2017, around 52 % were discovered during an inspection by anti-fraud services, 31% during a post-clearance control, 14 % during a control at the time of clearance of goods.

CHART TOR6: Method of detection 2017 – Cases reported as fraudulent – by estimated and established amount

In 11 Member States more than 50 % of all estimated and established amount in fraudulent cases were detected by anti-fraud services 15 . As regards amounts, controls at the time of clearance of goods were the most important method for detecting fraudulent instances in Estonia, Croatia, Latvia, Malta, Portugal, Finland and the United Kingdom whereas post-clearance controls were in Denmark, Hungary, The Netherlands, Austria, Poland and Sweden.

In Belgium, Ireland, Romania and Slovenia the 100% of all estimated and established amounts in fraudulent cases were detected by an inspection by services or bodies other than customs.

2.3.1.3. Smuggled cigarettes

In 2017, there were 173 cases of smuggled cigarettes registered (CN code 16 24 02 20 90) involving estimated TOR of around EUR 25 million. In 2016 the number of cases of smuggled cigarettes was 147, totalling around EUR 25 million.

The highest number of cases was reported by Lithuania (32), Greece (25) and Spain (23). The highest amount was reported by Belgium (EUR 8.3 million). No cases were reported by 8 Member States 17 .

 Table TOR1: Cases of smuggled cigarettes in 2017

2.3.1.4. Cases reported as fraudulent by amount

In 2017, the estimated and established amount was below EUR 50 000 in 303 cases reported as fraudulent (69 % of all fraud cases), whereas it was above EUR 50 000 in 138 cases (31%).

The total estimated and established amount in cases reported as fraudulent, where the amount at stake was above EUR 50 000, amounted to EUR 54 million (70 % of the total estimated and established amount for cases reported as fraudulent).

Table TOR2: Cases reported as fraudulent by amount category in 2017

2.3.2. Irregularities not reported as fraudulent

2.3.2.1. Modus operandi

A breakdown of irregularities by type of fraud shows that most cases of irregularity related to incorrect declarations (incorrect classification, customs value or country of origin or dispatch) and formal shortcomings (removal of goods from customs supervision, incorrect use of preferential arrangements or failure to fulfil obligations or commitments).

Not all customs procedures are equally susceptible to irregularities; their vulnerability may change in the course of time as certain economic sectors are briefly targeted. The customs procedure ‘release for free circulation’ is the customs procedure mostly affected by irregularities since at the time of release for free circulation the non-compliance in the customs declaration may relate to a large number of irregularities, e.g. to the tariff, CN code, (preferential) origin, incorrect value, etc. On the other hand, in customs suspension regimes (like warehousing, transit, inward processing, etc. - where the payment of duties is suspended) the sole irregularity that might occur is the subtraction of the goods from customs supervision. Thus, it is normal, and indeed to be expected, that most fraud and irregularities be reported in connection with the procedure ‘release for free circulation’.

In 2017 most of the estimated and established amounts in OWNRES in the EU-28 (83 %) for cases reported as non-fraudulent related to the customs procedure ‘release for free circulation’. 18 4% of all amounts estimated or established in cases not reported as fraudulent in 2017 involved customs warehousing, 11 % of all amounts estimated or established related to inward processing. Other customs procedures are only marginally affected in 2017.

Of all cases reported as non-fraudulent about 49 % concern electrical and mechanical machinery, vehicles, mechanical appliances, plastics, articles of iron and steel, glass and glassware and textiles. In monetary terms those groups of goods represent about 53 % of all amounts estimated or established for cases reported as non-fraudulent. China, United States, Argentina, Sri-Lanka, Thailand, Japan are - in monetary terms – the most important countries of origin of goods affected by irregularities.

2.3.2.2. Method of detection of non-fraudulent cases

In 2017, most non-fraudulent cases (55 %) were revealed during post-clearance customs controls. Other methods of detection for non-fraudulent cases that featured frequently were voluntary admission (19 %), clearance controls (11 %), tax audits (8 %), followed by anti-fraud services (5 %) 19 .

CHART TOR7: Method of detection 2017 – Cases not reported as fraudulent – by number of cases

Considering the estimated or established amounts, around 52 % of all irregularity cases registered for 2017 were discovered during a post-clearance control, 14 % were related to voluntary admission, 15 % to an inspection by anti-fraud services, whereas 10 % related to a tax audit and 8 % were found during a control at the time of clearance of goods.

CHART TOR8: Method of detection 2017 – Cases not reported as fraudulent – by established amounts

In 13 Member States, more than 50 % of all non-fraudulent cases — in amounts — were detected by post-release controls 20 . In Greece, Spain, France, Portugal and Romania more than 50 % of the amounts relating to non-fraudulent cases were detected by anti-fraud services. Significant amounts were reported as non-fraudulent following voluntary admission by the United Kingdom (EUR 28 million) and Germany (EUR 22 million). In 14 Member States voluntary admission was keyed in as a method of detection of cases reported as non-fraudulent.

2.3.2.3. Solar panels vulnerable to irregularities – mutual assistance

In 2017, solar panels 21 originating in China were especially vulnerable to non-fraudulent irregularities in monetary terms. About 12 % (EUR 49 million) of the total amount that was established in non-fraudulent irregularities concerned this type of goods. Incorrect classification/misdescription and incorrect country of origin or dispatching country were the main pattern of the infringement reported. The United Kingdom, the Netherlands and Germany were particularly affected by this type of goods and infringement. Other 10 Member States reported also cases related to solar panels to a smaller extent 22 . Most of the cases reported were detected following Mutual Assistance notices issued by OLAF. This underlines the importance of investigations conducted by OLAF in this particular field.

2.3.2.4. Cases not reported as fraudulent by amount

In 2017, the established amount was below EUR 50 000 in 3 159 non-fraudulent cases (76 % of all irregularity cases), whereas it was above EUR 50 000 in 1 036 cases (24 %).

The total estimated and established amount in non-fraudulent cases where the amount at stake was above EUR 50 000 amounted to EUR 366 million (86 % of the total estimated and established amount for non-fraudulent cases).

Table TOR3: Cases not reported as fraudulent by amount category in 2017

2.4. Member States’ activities

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

For 2017, Member States reported 441 cases as fraudulent out a total of 4 636 cases reported via OWNRES, which indicates a Fraud Frequency Level (FFL) of 10 %. The differences between Member States are relatively large. In 2017, nine Member States categorised between 10-50 % of all cases reported as fraudulent. However, Czech Republic and Slovakia did not categorise any cases reported as fraudulent 23 . Seven Member States categorised less than 10 % of cases as fraudulent 24 . Nine Member States registered more than 50 % 25 of cases as fraudulent.

In 2017, the total estimated and established amount affected by fraud in the EU was EUR 76 million and the overall incidence of fraud 26 was 0.30 %. For 2017, the highest percentages can be seen in Greece (7.03 %), Malta (2.49 %) and Austria (2.05 %) 27 .

The total estimated and established amount affected by cases not reported as fraudulent was more than EUR 425 million which indicates an irregularity incidence 28 of 1.66 %. The highest percentages can be seen in Spain (4.11 %), Hungary (3.17 %) and Czech Republic (2.58 %) 29 .

There are large differences between Member States’ classifications, which may partly depend on their classification practices. This can influence the comparison of the amounts involved in cases reported as fraudulent and as non-fraudulent by Member States. Moreover, individual bigger cases detected in a specific year may affect annual rates significantly. Factors such as the type of traffic, type of trade, the level of compliance of the economic operators, the location of a Member State can influence the rates significantly. 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. Cases reported as fraudulent

Over the 1989-2017 period, OWNRES shows that, on average, 22 % of the initially established amount was corrected (cancelled). The recovery rate (RR) for all years (1989-2017) is 37 % 30 . The RR for cases reported as fraudulent and detected in 2017 was 26 % 31 which is below the average rate of 36% for fraudulent cases for the 2013-2017 period 32 . In general, the RR in cases reported as fraudulent is clearly much lower than that for cases not reported as fraudulent.

2.4.2.2. Cases not reported as fraudulent

OWNRES shows that on the cut-off date, on average 37 % (1989-2017) of the initially established amount in relation to cases not reported as fraudulent has been corrected (cancelled) since 1989. The RR for non-fraudulent cases reported for 2017 is 50% 33 . On the cut-off date, the annual RR for the last five years has varied between 47% and 85%. The overall RR for all years (1989-2017) for all cases not reported as fraudulent is 71 % 34 .

2.4.2.3. Historical recovery rate (HRR)

The HRR confirms that in the long term recovery in cases reported as fraudulent is generally much less successful than in cases not reported as 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: Historical recovery rate (HRR

2.4.3. Commission’s monitoring

2.4.3.1. Examination of the write-off reports

In 2017, 12 Member States submitted 50 new write-off reports to the Commission. In 2017, the Commission assessed 169 cases totalling EUR 74 million. In 34 of these cases amounting to EUR 11 million 35 , 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 they were considered financially responsible for the loss.

Examination of Member States’ diligence in write-off cases constitutes a very effective mechanism for gauging their activity in the field of recovery. It encourages national administrations to step up the regularity, efficiency and effectiveness of their recovery activity, since any lack of diligence leading to failure to recover results in individual Member States having to foot the bill.

2.4.3.2. Commission’s inspections

In its TOR inspections, the Commission has put a special emphasis on Member States’ customs control strategies and closely monitors their actions and follow-up in relation to the observations made during the inspections. Member States generally show their willingness to adapt their control strategies and to progressively implement systems that provide for efficient and effective risk analysis to protect the EU’s financial interests. However, budgetary constraints and the increase of tasks related to security have led to cuts in the number of customs officials in charge of duty collection control in many Member States. This may undermine the control efficiency and thus pose risks to the protection of the EU financial interest.

In 2017, the general subject of inspection was the keeping of the separate account and the corrections of the normal account, with a specific emphasis on the written-off amounts between EUR 50.000 and EUR 100.000. "Management of the normal and separate accounts in smaller offices" 36 ,"Management of tariff suspensions and quotas" 37 , "External EU transit and the TIR procedures" 38 and "Control strategy of large business units" 39 were the main inspection themes of the on-the-spot customs inspections by the Commission services in Member States.

One general conclusion drawn by the Commission from its inspections in Member States in recent years is that their control strategies are increasingly shifting from customs controls at the time of clearance of goods to post-clearance customs controls. The customs controls before or at the time of clearance of goods remain however indispensable for addressing undervaluation and the detection of new types or patterns of fraud or irregularities. Therefore, the customs controls strategy should be frequently reviewed taking into account recent detections or new risks.

Considering the fraud diversion and spreading of specific fraud mechanism, EU-wide and international cooperation in detection of irregular cases is more and more required.

2.4.3.3. Particular cases of Member State failure to recover TOR

If TOR are not established because of an administrative error by a Member State, the Commission applies the principle of financial liability 40 . Member States have been held financially liable in 2017 for over EUR 29 million 41 , and new cases are being given appropriate follow-up.

PART II - EXPENDITURE

Sustainable growth: natural resources

The emphasis of the EU policy in this field is on increasing farms' profitability, diversifying the rural economy and protecting the natural environment. There is a direct management component but the majority of expenditure is disbursed by Member States under shared management funds.

For the purpose of this analysis, the Common Agricultural Policy (CAP) is split in two main parts:

oDirect support to agriculture (SA), through direct payments to farmers and measures to respond to market disturbances, such as private or public storage and export refunds, which are financed by the European Agricultural Guarantee Fund;

oRural development programmes of the Member States (RD), which are mainly financed through the European Agricultural Fund for Rural Development.

The European Maritime and Fisheries Fund (EMFF) provides funding and technical support for initiatives that can make the fishery industry more sustainable. The EMFF is the successor of the European Fisheries Fund (EFF), for which the full resources have been committed by the end of 2014. Table NR1 shows also the financial resources available for this policy area. However, in light of their belonging to the European Structural and Investment Funds (ESIF) family, EFF and EMFF will be treated together with the other structural funds. EAFRD and the EMFF are among the five ESIF which complement each other and seek to promote a growth and job based recovery in Europe.

3.Common Agricultural Policy (CAP)

3.1.Introduction

For the last 50 years the Common Agricultural Policy (CAP) has been the European Union's (EU) most important common policy. This explains why traditionally it has taken a large part of the EU's budget, although the percentage has steadily declined over recent years.

The CAP is financed by two funds, EAGF and EAFRD, which form part of the EU's general budget.

Under the basic rules for the financial management of the CAP, the European Commission is responsible for the management of the EAGF and the EAFRD. However, the European Commission itself does not make payments to beneficiaries. According to the principle of shared management, this task is delegated to the Member States, who themselves work through 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 European Commission.

The paying agencies are, however, not only responsible for making payments to the beneficiaries. Prior to doing so, they must, either themselves or through delegated bodies, satisfy themselves of the eligibility of the aid applications. The exact checks to be carried out are laid down in the different sectorial regulations of the CAP and vary from one sector to another.

The expenditure made by the paying agencies is then reimbursed by the European Commission to the Member States, in the case of the EAGF on a monthly basis and in the case of EAFRD on a quarterly basis. Those reimbursements are, however, subject to possible financial corrections which the European Commission may make under the clearance of accounts procedures.

Apart from a difference in scope and objectives, the two funds also function differently. While entitlements and measures supported under the EAGF follow a yearly flow, those under the EAFRD are implemented through multi-annual programmes, very much like the interventions financed through the other ESI funds.

Table NR2 shows the financial resources available for the CAP.

3.2.General analysis

3.2.1.Irregularities reported 2013-2017

Table NR3 shows the number of irregularities (fraudulent and non-fraudulent) reported by the Member States for the period 2013-17 in relation to 'rural development' (RD) and direct 'support to agriculture' (SA). Cases are classified as:

·RD, where they concern only expenditure for rural development;

·SA, where they do not concern rural development expenditure. SA includes expenditure in relation to intervention in agricultural markets and direct payments to farmers;

·'SA/RD', where they concern both types of expenditure (rural development and direct support to agriculture) or there is no enough information to assign the case to RD or SA.

Annex 11 provides a detailed explanation about the classification of cases. When inputting a case, the contributor is requested to specify the currency in which the amounts are expressed. Where the value of this field is 'EUR' or the field has been left blank, no transformation is applied. Where this field has been 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 2018.

The number of irregularities decreased by 10% in 2017 (in comparison with 2016) and this brought the overall increase during the period 2013-2017 down to 5%. However, while the irregularities affecting SA have been relatively stable over time, those related to RD have noticeably increased until 2015 and then declined at a similar pace during 2016-2017, as showed by the chart associated to Table NR3 (in 2017, -21.4% in comparison with 2016 and -36.2% in comparison with 2015).

This difference in stability is reflected in the average year-on-year (yoy) absolute variation, which for SA was just 8%, while for RD it reached 25%.

It should be considered that the two types of support are provided following two different modes. SA follows an annual implementation, while RD finances programmes in a multiannual context, which resembles that of the ESI Funds. In fact, the trends of irregularities detected and reported in relation to RD and ESI Funds are similar and are influenced by the implementation modes.

The irregularities notified by a minority of Member States (Italy, Romania, Portugal, Spain, Hungary, Poland and France) nearly represented 75% of the total number of reported irregularities in 2017.

Table NR4 provides information about the financial amounts involved in the cases considered in Table NR3. In 2017, the financial amounts 42 have increased by 10% in comparison with 2016. After a decreasing trend during 2013-2016, in 2017 the SA financial amounts bounced back, pushed by strong increases both in numbers and average financial amount (see also below for an explanation). On the contrary, in 2017 the RD financial amounts continued on the decreasing path that had started after the 2015 peak, due to declining numbers and a stable average financial amount. As a result, in 2017 the financial amounts involved in irregularities are nearly equally shared between RD and SA. However, one has to bear in mind that, in 2017, RD represented about 20% of the total resources devoted to the CAP, while the financial value of the irregularities reported in relation to RD accounted for 50% of the total amount of all irregularities related to CAP expenditure in 2017. 

In fact, the weight of the financial amounts involved in irregularities on payments 43 is very different between the two types of support, as it is 0.1% for SA and 1.3% for RD (0.5% on the overall 2017 CAP expenditure).

Considering the overall period 2013-2017, the average financial amount involved in SA cases is higher than in RD cases (+50%). This is mainly due to irregularities concerning market measures, where cases with exceptional financial amounts happened to be reported. 44 In fact, in 2016 such exceptional cases did not emerge and the average financial amounts of RD and SA cases were broadly aligned. In general, when SA is considered net of cases concerning market measures, the average financial amount is lower than for RD cases. Also in 2016 the average financial amount of cases concerning market measures was 41% higher than that for RD cases.

The trend of the financial amounts must be assessed while bearing in mind that it can be strongly influenced by single observations of significant value. The continuous growth of the financial value of irregularities related to RD until 2015 is, however, in line with the general trend of irregularities showed in Table NR3.

During 2013-2017, cases which involved financial amounts over 1 million represented less than 1% in terms of numbers, but 33% in terms of amounts. 45 60% of these 'over 1 mln' cases concerned RD, while 29% concerned market measures. In such a context, where such a significant portion of the financial amounts is linked to a relatively low number of cases, fluctuations are more likely and should not be misinterpreted.

This contributes to explain the steep increase in 2017 of the financial amounts related to SA irregularities. During 2013-2015 and 2017, each year there were one or two cases concerning market measures which involved exceptional financial amounts (globally adding on average more than EUR 40 mln per year). 46 From this point of view, 2016 was an unusual year, because there were no such exceptional cases. The return to the previous pattern in 2017 contributed to the noticeable upward jump in the financial amounts involved in irregularities concerning SA, which includes market measures.

Section 3.3.4 will deal later with the reasons why controls that led to discover irregularities were performed. That analysis will bring to a number of findings about the frequency and potential of different detection methods. Here a different perspective is taken. When focusing on the 'over 1 mln' cases, it can be noticed that some of these reasons for performing the control were more present than in the overall set of cases. Reference is made to 'Information published by the media', 'Tip from informant, whistle-blower, etc.' and 'Irregularity detected by EU body'. 47 Even if this is based on a relatively low number of cases, it may be see as corroborating the hypothesis that these targeted controls have the potential to lead to better results.

3.2.2.Irregularities reported as fraudulent

For the period 2013-17, Table NR5 provides an overview of the number of irregularities reported as fraudulent by Member States in relation to the type of support concerned. This shows a significant decrease in comparison to 2016 (-31.5%), which is due to a drop in the number of relevant RD irregularities (-51.1%) that could not be compensated by the increase recorded for the SA type of support.

After three consecutive years during which the number of irregularities reported as fraudulent in relation to RD had largely exceeded the number of those reported for SA, in 2017 the SA share matched the RD one. As a result, over the period 2013-2017, the number of RD irregularities reported as fraudulent is still higher than the number of SA ones, but the share of the total was just 56%.

In 2017, the irregularities notified by the first three Member States (Poland, Romania and Italy) represented about 65% of the total number of irregularities reported as fraudulent. This concentration was higher than in 2016 (about 63%) and in 2013 (about 58%).

The first ten countries taken together reported 246 cases as fraudulent, which represented about 89% of the total (in 2016 the first ten countries accounted for about 92% and in 2013 about 93% of the total irregularities reported as fraudulent).

Estonia, Germany, Ireland, Italy, Luxembourg, the Netherlands, Slovakia and Slovenia accounted for an increasing number of cases reported as fraudulent.

Table NR6 provides information about the financial amounts involved in the cases considered in Table NR5. In 2017, the overall financial amounts were stable, but this was the result of different patterns in RD and SA. After the peak recorded in 2016 for financial amounts related to RD, the largest share in 2017 was represented again by the SA, which was pushed by increases both in the number of SA cases (+9%) and their average financial amount (+227%). 48 Financial amounts involved in SA cases were predominant also if one takes into account the whole 2013-17 period (58% of the total amount). However, the share of the RD on the total (40%) was well above the share of the resources allocated to RD on the total of the CAP resources over the same period.

Considering the overall period 2013-2017, the average financial amount involved in SA cases was higher than that for RD cases (+104%). This is mainly due to irregularities concerning market measures, where potential frauds with exceptional financial amounts happened to be reported. 49 In fact, in 2016 such exceptional cases did not emerge and the average financial amount of SA fell below that of RD cases. Also net of these exceptional cases, the average financial amount of potential frauds in market measures is still higher than that of RD cases over the period 2013-2017 (+135%). On the contrary, when SA is considered net of cases concerning market measures, the average financial amount is far lower than for RD cases over the period 2013-2017 and is decreasing in 2017.

During 2013-2017, 103 cases concerned both RD and SA. In most of these cases, violations concerning RD were combined with violations concerning direct payments.

The trend of the financial amounts must be assessed while bearing in mind that it can be strongly influenced by single observations of significant value. For instance, the 'distance' observed in 2013 between the two types of support, finds explanation in very few cases involving high amounts linked to the SA.

3.2.3.Irregularities not reported as fraudulent

Regarding irregularities not reported as fraudulent, the number of those reported in relation to RD has been constantly increasing until 2015, while that related to SA remained stable or recorded minor variations (see Table NR7). Consistently, also the irregular financial amounts linked to RD have been constantly increasing until 2015 (as highlighted in Table NR8). In 2017, the irregular financial amounts linked to SA recorded an unusual increase (+55%), beyond what could be expected due to the related increase in the number of such irregularities (+17%).

In terms of number of irregularities (Table NR7), RD has regularly and significantly exceeded SA across the whole 2013-2017 period, with the result that the number of irregularities linked to RD have been more than double those affecting SA.

In terms of financial amounts (Table NR8), after the peak in 2015, irregularities related to RD gradually decreased, while irregularities related to SA recorded in 2017 a steep raise, after a flat trend. 50 As a result, the gap between RD and SA financial amounts experienced a peak in 2015 and nearly closed in 2017.

In 2017, the average financial amounts increased for both RD cases (+15%) and SA cases (+32%). This supported the increase of financial amounts despite the decrease in the number of cases. Considering the overall period 2013-2017, the average financial amount involved in SA cases is higher than in RD cases (+23.5%). This is mainly due to irregularities concerning market measures, where cases with exceptional financial amounts happened to be reported. 51 However, also net of these exceptional cases, the average financial amount of non fraudulent irregularities in market measures is still higher than that of RD cases over the period 2013-2017 (+75%) and is increasing in 2017. On the contrary, when SA is considered net of cases concerning market measures, the average financial amount is lower than for RD cases over the period 2013-2017 and is decreasing in 2017.

3.3.Specific analysis

3.3.1.Modus operandi

3.3.1.1.Support to agriculture (SA)

Table NR9 provides an overview of the most frequent categories (or combinations of categories) of irregularities linked to cases reported as fraudulent in relation to SA in 2017 and the financial amounts involved. It also presents how these most recurrent categories (or combinations of categories) featured from 2013 to 2017 (included). 52

The most recurrent modi operandi are related to 'documentary proof' or to the 'request' (not combined with other categories of irregularity). Each category is articulated in different types of violations (see Annex 12). With reference to these two categories, the most recurrent types concerned 'false or falsified documents' or 'false or falsified request for aid', both in 2017 and in the overall period 2013-2017.

Irregularities concerning 'Product, species and/or land' (not combined with other categories of irregularity) were also quite recurrent. More specifically, most of these infringements concerned the types 'overdeclaration and/or declaration of ficticious product, species and/or land' (both in 2017 and in the overall period 2013-2017) and 'quantities outside permitted limits, quotas, thresholds' (considering the overall period 2013-2017).

In 2017, 10 irregularities were reported as pertaining to the category 'Ethics and integrity' (not combined with other categories of irregularity). In the previous years, other 41 cases of the sort had been reported. All of these violations were communicated by Poland and were not reported under the types 'conflict of interest', 'bribery' or 'corruption', but as 'other irregularities concernig 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.

Table NR10 provides an overview of the most frequent categories (or combinations of categories) of irregularities linked to cases not reported as fraudulent in relation to SA in 2017 and the financial amounts involved. It also presents how these most recurrent categories (or combinations of categories) featured from 2013 to 2017 (included).

When looking at these irregularities, violations concerning the 'request' are the most recurrent category (by far, in 2017). More specifically, while during the period 2013-2017 most of these infringements were almost equally split between the types 'incorrect or incomplete request for aid' and 'false or falsified request for aid', in 2017 the latter type of violation was clearly predominant. Violations concerning the other category 'documentary proof' were also quite frequent and often related to the type of violation 'false or falsified documents' (202 cases in 2013-2017). 53  

Another prevalent category of irregularity not reported as fraudulent is related to '(non)action'. In this area, the three most reported types pertained to the action itself ('not implemented or completed'), and 'refusal to repay not spent or unduly paid amounts'.

In relative terms, infringements related to 'Ethics and integrity' were less frequent than for the irregularities reported as fraudulent. Apart from one case of conflict of interest, all of these violations were reported as 'other irregularities concernig ethics and integrity'.

3.3.1.2.Rural development (RD)

Table NR11 provides an overview of the most frequent categories of irregularities reported as fraudulent in RD in 2017 and the related financial amounts. It also presents how these most recurrent categories have featured from 2013 to 2017 (included).

In 2017 and in 2013-2017, the category 'documentary proof' ranked first, with 'false or falsified documents' as the most reported type of violation. Also with reference to the 'request', which is another frequent category, the false-related type of irregularity ('false or falsified request of aid') is the most reported.

Within the CAP, 'RD cases reported as fraudulent' is the domain where the category Ethics and integrity ranks higher, with 22 irregularities in 2017 and 137 in 2013-2017. Similarly to SA cases, most of these violations 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 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.

Table NR12 provides an overview of the most frequent categories of irregularities not reported as fraudulent in RD in 2017 and the related financial amounts. It also presents how these most recurrent categories have featured from 2013 to 2017 (included).

When looking at these irregularities, the most frequently detected category is related to 'non-action' (including 'action not completed', 'action not implemented' or 'failure to respect deadlines' among the most reported types of violation). This category ranked very high also in relation to irregularities reported as fraudulent (see Table NR11).

'(Non-)action' was followed by 'documentary proof' representing 11% of the non-fraudulent cases in 2017 (including 'Documents missing and/or not provided' as the most reported type of violation). During 2013-2017, a number of 'documentary proof' cases (45) concerned the 'false and/or falsified documents' type of violation. The same applies to the category 'request', where a number of cases (17) were related to the 'false or falsified request of aid' type of violation.  54

In relative terms, the category Beneficiary is more frequent among RD cases not reported as fraudulent than in other CAP areas (about 10% of cases in 2017). Within this category, 'Operator/beneficiary not having the required quality' is the most reported type of violation.

3.3.2.Fraud and Irregularity Detection Rates by CAP components

Via its two funds (EAGF and EAFRD) the CAP supports agriculture and rural development across Europe. The

EAGF itself has two components with different aims: measures regulating or supporting agricultural markets (insoforth, referred to as 'intervention in agricultural markets' or 'market measures') and direct payments to farmers. Annex 11 provides a detailed explanation about the classification in these two categories of the cases reported by the Member States.

Table NR13 shows the Fraud Detection Rate (FDR) and the Irregularity Detection Rate (IDR) per type of policy measure.

The same case may cover several budget posts referring to different types of expenditure. In Annex 13, a detailed explanation of this issue and how it has been handled in estimating these FDR/IDR can be found.

As mentioned in section 3.2.2, the financial amounts involved in irregularities reported as fraudulent concerning market measures are heavily influenced by few (4) exceptional cases. 55 Net of these cases, the FDR for market measures would be 0.31% rather than 1.17%. Similarly, excluding the few (3) 'exceptional' non fraudulent irregularities, the IDR would be 1.08% rather than 1.39%.

3.3.3.Market measures – fraudulent and non-fraudulent irregularities

As showed in Table NR13, market measures feature high FDR and IDR. Table NR14 shows the frequency and financial amounts of irregularities reported as fraudulent in relation to market measures for the period 2013-2017, while Table NR15 shows the same data with reference to irregularities not reported as fraudulent.

The category 'products of the wine-growing sector' is the most recurrent, but 'fruit and vegetables' is the one with the highest financial amounts, in particular due to the exceptional average amount of cases reported as fraudulent. Another category with an exceptional average financial amount is 'Pigmeat, eggs and poultry, bee-keeping and other animal products'.

3.3.4. Reasons for performing control

3.3.4.1 Irregularities in relation to rural development

In the context of the antifraud cycle, the detection capability is a key feature, which contributes to the effectiveness and efficiency of the system for the protection of the EU budget.

Table NR16 provides an overview of the reasons why controls were performed with reference to rural development during 2013-2017, with a focus on controls that led to discover irregularities reported as fraudulent. 56 The description of the 'reason for performing control' has been shortened to simplify the Table and associated Graphs, but the full description can be consulted in Annex 14.

The straight lines in the graphs associated to Table NR16 represent the border between 'reasons' that led to identify irregularities with an average amount above or below the global average (that takes into account all potential frauds affecting RD). The vertical distance between a point representing a specific reason and the straight line is an indicator of how higher or lower was the yield of these controls started for that specific reason, in comparison with the hypothetical situation where these controls involved financial amounts in line with the global average 57 .

Map NR1 provides an overview by Member State of the number of irregularities reported as fraudulent with reference to rural development during 2013-2017. The most active Member States in detecting and reporting potentially fraudulent irregularities in RD were Poland, Romania and Hungary, which represented more than 60% of these irregularities.

The most frequent reasons for starting a control were 'Routine', 'Administrative enquire' and 'Judicial enquiry'. The average financial amounts involved in these three reasons are broadly in line with the global average, with a better performance of 'Routine' and 'Judicial enquiry'.

'Judicial enquiry' was mentioned as reason mostly in Romania (86% of cases), while 'Administrative enquire' was relatively more widespread, with Hungary as the main Member State (56% of cases). The majority of cases where the control was started because of 'Routine' were reported by Poland (55% of cases).

Poland was also the Member State with the highest number of irregularities detected because of a 'Tip' (followed by the Czech Republic and Slovakia). This reason for starting a control showed above-the-average financial amount involved.

'Risk analysis' was reported only a few times as reason for starting a control, while it showed a good average financial amount. These cases were basically reported only by Lithuania and Bulgaria.

Table NR17 provides an overview of the reasons why controls were performed with reference to rural development during 2013-2017, with a focus on controls that led to discover irregularities not reported as fraudulent.

Map NR2 provides an overview by Member State of the number of irregularities not reported as fraudulent with reference to rural development during 2013-2017. Besides ranking as the most active Member States in detecting potential frauds in RD, Romania, Poland and Hungary were among the most active also for irregularities not reported as fraudulent. For non fraudulent irregularities, also Portugal, Spain and Italy must be mentioned among the Member States with the highest frequency, while they did not report a significant amount of potential frauds. The comparison is striking, in particular for Portugal and Spain, where the ratio (fraud)/(non fraud) was 0.012 and 0.03, respectively.

'Administrative enquiry' and 'Routine' were by far the most frequent reasons for starting a control. The average financial amounts were broadly in line with the global average. 'Administrative enquiry' was mostly reported by Romania and Hungary, while 'Routine' by Portugal and Poland.

Controls that started because of a 'Judicial enquiry' were relatively rare, but they were the ones with the second highest average financial amount. These cases are concentrated in Romania and Italy. The highest average financial amount is for the few cases triggered by an irregularity detected and reported by an EU body.

Another reason that is less frequently reported – but shows a good 'productivity' – is 'risk analysis'. Most cases were concentrated in Hungary, Spain, Germany and Lithuania (in the latter Member State, risk analysis led also to detect a relatively high number of potential frauds – see above).

Also 'Tip' and 'Media' showed good average financial amounts, but these reasons are not often at the basis of controls, especially 'Media'. Lithuania was the Member State where more cases were started because of information provided by the media. Cases that started because of a 'Tip' were more widespread, with Poland ranking high (similarly to what could be found in relation to irregularities reported as fraud). Nevertheless, the highest ranking is for the United Kingdom, where 'Tip' had instead a negligible role in detecting irregularities reported as fraudulent.

3.3.4.2 Irregularities in relation to market measures

Table NR18 provides an overview of the reasons why controls were performed with reference to market measures during 2013-2017, with a focus on controls that led to discover irregularities reported as fraudulent. 58 The description of the 'reason for performing control' has been shortened to simplify the Table and associated Graphs 59 , but the full description can be consulted in Annex 14.

Map NR3 provides an overview by Member State of the number of irregularities reported as fraudulent with reference to market measures during 2013-2017.

The most active Member States in detecting potential fraud in relation to market measures were France, Poland and Hungary, which reported 74% of these cases.

The most recurrent reason for starting these controls was the scrutiny provided for by Regulation 485/2008.

This Regulation provides that the Member States shall carry out systematic scrutiny of the commercial documents of undertakings. Member States shall select the undertaking on the basis of risk analysis. The Regulation provides for a high number of controls 60 , but the ones that led to discover irregularities were concentrated in just two Member States (France and Hungary) and resulted in a below-the-average financial amount 61 . It is possible that some cases were reported in other categories, such as 'Routine' or administrative enquiry'. 'Risk analysys' is explicitly mentioned in 14 cases.

'Tip' was rarely the reason for controls that led to detect potential fraud, but these cases were very 'productive'. Most of these cases were in Poland and Spain. With 10 out of 162 cases (6.2%), this is the field (irregularities reported as fraudulent in relation to market measures) where this reason was relatively more frequent (within the CAP context). In general, it can be noticed that the reason 'tip' is more recurrent in relation to fraudulent cases than in cases not reported as fraudulent (within CAP). 62

'Judicial enquiry' was mentioned only in two cases, with an exceptional average financial amount.

Table NR19 provides an overview of the reasons why controls were performed with reference to market measures during 2013-2017, with a focus on controls that led to discover irregularities not reported as fraudulent.

There are three reasons that cover most of the cases: 'Routine', 'Administrative enquiry' and 'Scrutiny 4045'. 'Administrative enquiry' stands out in terms of average financial amount.  63  

The reason 'Scrutiny 4045' should be interpreted taking into consideration also the cases where 'Scrutiny 485' is mentioned: both Regulation 4045/1989 and Regulation 485/2008 deal with the scrutiny of commercial documents of those entities receiving payments from the Guarantee section of the EAGGF (Reg. 4045/1989) or from the EAGF (Reg. 485/2008) 64 . While Reg. 485/2008 explicitly introduced the concept of risk analysis (see above), Reg. 4045 already required consideration for risk factors and concentration on sectors or undertakings where the risk of fraud is high. The average financial amount involved in irregularities discovered on the basis on 'scrutiny 485' was significantly higher than the average financial amount related to the previous 'scrutiny 4045'. It is possible that some cases were reported in other categories, such as 'Routine' or 'administrative enquiry'. 'Risk analysys' is explicitly mentioned in 25 cases.

Map NR4 provides an overview by Member State of the number of irregularities not reported as fraudulent with reference to market measures during 2013-2017. The most active Member States in detecting non fraudulent irregularities in relation to market measures were Spain, France and Italy, which reported 63% of these cases.

3.3.4.3 Irregularities in relation to direct payments

Table NR20 provides an overview of the reasons why controls were performed with reference to direct payments to farmers during 2013-2017, with a focus on controls that led to discover irregularities reported as fraudulent. 65 The description of the 'reason for performing control' has been shortened to simplify the Table and associated Graphs, but the full description can be consulted in Annex 14.

'Judicial enquiry' and 'routine' were the most recurrent reasons for starting controls that then led to irregularities reported as fraudulent. The average financial amount involved in irregularities discovered because of 'judicial enquiry' was lower that the global average, while the contrary was recorded in relation to 'routine'.

In the direct payments field, Regulation 3508/1992 applies. This Regulation requires the Member State to set up an integrated administration and control system. 'Scrutiny 3508' appears in a limited number of cases. It is possible that some cases were reported in other categories, such as 'Routine' or 'administrative enquiry'. 'Risk analysys' was explicitly mentioned in 54 cases.

Map NR5 provides an overview by Member State of the number of irregularities reported as fraudulent with reference to direct payments during 2013-2017. The most active Member States in detecting irregularities reported as fraudulent in relation to direct payments were Romania, Italy and Poland, which reported 67% of these cases.

Table NR21 provides an overview of the reasons why controls were performed with reference to direct payments to farmers during 2013-2017, with a focus on controls that led to discover irregularities not reported as fraudulent.

'Administrative enquiry' and 'routine' were the most recurrent reasons for starting controls that then led to irregularities not reported as fraudulent. The average financial amount involved in irregularities discovered because of 'administrative enquiry' was in line with the global average, while 'routine' was above such average.

'Scrutiny 3508' appears in a significant number of cases, with a low average financial amount. It is possible that some cases were reported in other categories, such as 'Routine' or 'administrative enquiry'. 'Risk analysis' was explicitly mentioned in 218 cases, with an average financial amount lower than the global average.

Map NR6 provides an overview by Member State of the number of irregularities not reported as fraudulent with reference to direct payments during 2013-2017. The most active Member States in detecting non fraudulent irregularities in relation to direct payments were Italy and Romania, which reported 53% of these cases.

3.4.Anti-fraud activities of Member States

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

The present section digs into some aspects linked to the anti-fraud activities and results of Member States. Four elements are analysed:

(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 2017 and over the last five years);

(3)the fraud detection rate (FDR - the ratio between the amounts involved in cases reported as fraudulent and the payments occurred in the same period) and the irregularity detection rate (IDR - the ratio between the amounts involved in cases not reported as fraudulent and the payments occurred in ther same period) over the last five years 66 ;

(4)the ratio of cases of established fraud on the total number of irregularities reported as fraudulent.

3.4.1.Duration of irregularities

Of the 18,281 irregularities (fraudulent and non-fraudulent) reported by Member States in 2013-2017 in relation to CAP, 10,580 (58% of the total) involved infringements that have been protracted during a span of time. For the 2,081 irregularities reported as fraudulent, this percentage is higher at about 61%. The remaining part of the dataset refers to irregularities which consisted of a single act identifiable on a precise date (about 34% of the whole dataset and 37% of that including exclusively the fraudulent irregularities) or for which no reliable information has been provided 67 (8% of the whole dataset, but only 2% of the irregularities reported as fraudulent).

The average duration of the irregularities which have been protracted over time was 26 months (i.e. 2 years and 2 months). For the irregularities reported as fraudulent, this average was 4 months more: 30 months.

3.4.2.Detection of irregularities reported as fraudulent by Member State

3.4.2.1.Reported in 2017

Table NR22 offers an overview of the irregularities reported as fraudulent by Member States in 2017. It also shows the related amounts, overall payments for the agricultural policy and the FDR.

Belgium, Cyprus, Finland, Malta, Sweden and the United Kingdom have notified no irregularities as fraudulent; other nineteen (19) Member States reported less than 30 potentially fraudulent irregularities; one (1) country reported between 30 and 60; two (2) Member States more than 60.

Poland, Romania and Italy are the three countries which have reported the highest numbers, while Poland, Romania and Bulgaria reported the highest amounts. Estonia and Poland's FDRs approached 1%, more than double the third highest FDR, which is Bulgaria's.

3.4.2.2.Reported during the period 2013-17

Table NR23 offers an overview of the irregularities reported as fraudulent by Member States between 2013 and 2017. It also shows the related amounts, overall payments for the agricultural policy and the FDR.

Only Finland notified no irregularities as fraudulent; the majority of Member States (22, excluding Finland) reported less than 100 potentially fraudulent irregularities; one (1) Member State reported between 100 and 200; two (2) Member States notified between 201 and 300 and other two (2) more than 300.

Romania, Poland, Italy and Hungary are the Member States which have reported the highest numbers, while Poland, Romania, the Netherlands and Italy reported the highest amounts. Netherland and Estonia's FDRs are around 1%, more than double the third highest FDR, which is Poland's.

3.4.3.Fraud and Irregularity Detection Rates by Member State

3.4.3.1.Market measures

Table NR24 focuses on market measures and shows the Member States which have reported potentially fraudulent irregularities in the period 2013-2017. Detections are measured against the expenditure over the same period to calculate the FDR.

15 Member States have reported potentially fraudulent cases in this area. France, Poland and Hungary reported the highest numbers. The highest financial amounts were communicated by Poland, the Netherlands, France and Italy. The Netherland and Poland show the highest FDRs, while the FDRs of Hungary, Slovenia and France range between about 2% and 1%.

Individual cases involving significantly high amounts can produce a distortive effect on the overall analysis. This was particularly the case for the Netherlands, which show the highest FDR despite the low number of detections. The main case reported by the Netherlands refers to events dating back almost ten years.

Table NR25 shows the IDR per Member State, which therefore, refers to irregularities reported as non fraudulent.

22 Member States have reported non fraudulent cases with reference to market measures. Spain, France and Italy reported the highest numbers. The highest financial amounts were communicated by France, Romania and Spain. Malta, Romania and Denmark show the highest FDRs, while the FDRs of the Netherlands, Sweden, Hungary and Cyprus are above 2%.

A part of these irregularities (reported as fraudulent or not) are not exclusively referred to market measures, but the reporting authority may have also included budget posts referring to other measures, including direct payments or rural development. These irregularities have been included in their full value in Tables NR24 and NR25 (see also Annex 13).

3.4.3.2.Rural development

25 Member States have reported potentially fraudulent cases in relation to RD during the period 2013-2017, as showed in Table NR26. Detections are measured against the expenditure over the same period to calculate the FDR.

Poland, Romania and Hungary reported the highest mumbers. The highest financial amounts were communicated by Romania, Poland, Bulgaria and Hungary. Estonia show the highest FDR, above 2%, while the FDR of Bulgaria approaches 1%.

These irregularities are exclusively referred to rural development. A number of additional cases concern both rural develoment and support to agriculture, including market measures or direct payments (see Table NR5 and Annex 13).

 Table NR27 shows the IDR per Member State, which therefore, refers to irregularities reported as non-fraudulent. Romania, Portugal, Poland, Spain, Hungary and Italy reported the highest numbers. The highest financial amounts were communicated by Romania, Spain and Portugal. Lithuania show the highest FDR, above 3%, while the FDR of Romania, the Netherlands, Portugal, Hungary and Slovakia range between 3% and 2%.

These irregularities are exclusively referred to rural development. A number of additional cases concern both rural develoment and support to agriculture, including market measures or direct payments (see Table NR7 and Annex 13).

3.4.4.Ratio of established fraud / Dismissal ratio

Since the PIF Report 2014, the analysis has also tried to focus on the rate of irregularities reported as fraudulent by Member States for which a final decision was taken, establishing that fraud really occurred. By comparing updated data with those published in 2014, it is also possible to identify how many cases have been dismissed (initially reported as fraudulent and then "declassified" or cancelled).

Table NR28, therefore, updates the table already published in the last three Reports indicating that the 'ratio of established fraud' has slightly increased in comparison to last year (from 11% to 12%). Likewise, the 'dismissal ratio' increased from 14% to 17%.

3.5.Recovery cases

For an in-depth analysis of recovery and financial corrections in the CAP, see section 2.1.1.3 of the Annual Activity Report of DG AGRI and the 2017 Annual Management and Performance Report for the EU Budget 68 .

(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)

   Cases with an amount of TOR exceeding EUR 10 million.

(4)

     NL (2 cases – EUR 30.5 million) and the UK (1 case – EUR 10.4 million).

(5)

See Annex 4.

(6)

On the cut-off date for last year report.

(7)

Greece, Czech Republic, Spain, Malta, Lithuania, Hungary, the Netherlands, Austria, Portugal, Croatia and the UK.

(8)

Germany, UK, the Netherlands, Belgium, Italy, France and Spain.

(9)

The estimated amounts are excluded.

(10)

See Annex 9.

(11)

See Annex 9.

(12)

See Annex 5.

(13)

The category "Other" combines, among others, the following procedures or treatments: Processing under customs control, temporary admission, outward processing and standard exchange system, exportation, free zone or free warehousing, re-exportation, destruction and abandonment to the Exchequer.

(14)

 See Annexes 7 and 8.

(15)

Belgium, Bulgaria, Germany, Ireland, Greece, Spain, Italy, Cyprus, Lithuania, Romania and Slovenia.

(16)

Combined nomenclature or CN –nomenclature of the Common Customs Tariff.

(17)

Czech Republic, Denmark, Italy, Cyprus, Luxembourg, the Netherlands, Slovenia and Slovakia.

(18)

See Annex 6.

(19)

See Annex 7 and 8.

(20)

Czech Republic, Denmark, Germany, Estonia, Croatia, Cyprus, Lithuania, Hungary, the Netherlands, Austria, Poland, Sweden and the UK.

(21)

 CN codes 85 01 31 00, 85 01 64 00 and 85 41 40 90.

(22)

France, Austria, Italy, Belgium, Sweden, Czech Republic, Denmark, Estonia, Greece and Spain.

(23)

Luxembourg did not report any irregular case in 2017.

(24)

Denmark (2%), Germany (3 %), Ireland (3%), the Netherlands (2 %), Portugal (6%), Sweden (2 %) and the UK (1 %).

(25)

Bulgaria (95 %), Estonia (80%), Greece (76 %), Croatia (53%), Cyprus (80 %), Latvia (60%), Lithuania (67%), Malta (100 %) and Poland (53 %).

(26)

 The percentage that the total established and estimated amounts related to fraudulent cases represent on the total TOR collected by Member States.

(27)

See Annex 4.

(28)

The percentage that the total established and estimated amounts related to non-fraudulent cases represent on the total TOR collected by Member States.

(29)

See Annex 4.

(30)

This calculation is based on 18 474 cases, an established amount of EUR 2.13 billion (after already processed corrections) and a recovered amount of EUR 0.78 billion.

(31)

See Annex 9.

(32)

On the cut-off date, for years 2013-2017, the annual RR for fraud cases varied between 26 % and 63 %.

(33)

See Annex 9.

(34)

This calculation is based on 82 606 cases, an established amount of EUR 5.3 billion (after already processed corrections) and a recovered amount of EUR 3.77 billion.

(35)

See Annex 10

(36)

Germany and France.

(37)

Lithuania and Luxembourg.

(38)

Belgium, Bulgaria, Czech Republic, Germany, Estonia, Ireland, Greece, Spain, France, Italy, Latvia, Hungary, the Netherlands, Poland, Portugal, Slovenia, Slovakia, Finland, Sweden and the United Kingdom.

(39)

The United Kingdom.

(40)

Case C-392/02 of 15/11/2005. These cases are typically identified on the basis of Articles 220(2)(b) (administrative errors which could not reasonably have been detected by the person liable for payment) and 221(3) (time-barring resulting from Customs’ inactivity) of the Customs Code, Articles 869 and 889 of the Provisions for application of the Code, or on the basis of non-observance by the customs administration of Articles of the Customs Code giving rise to legitimate expectations on the part of an operator.

(41)

It includes customs duties (EUR 9.8 million) and interest (EUR 19.1 million).

(42)

In this report, whenever financial amounts are mentioned with reference to reported cases, they refer to the financial amount of the irregularity and not of the overall related expenditure.

(43)

For example, for RD this is calculated as (financial amounts of irregularities in RD)/(payments related to all RD projects during the same period of reference).

(44)

In this context, a financial amount is considered 'exceptional' where it exceeds EUR 10 million.

(45)

Furthermore, it can be noticed that there were just 24 cases over 3 million accounting for 21% of the financial amounts.

(46)

In this context, a financial amount is considered 'exceptional' where it exceeds EUR 10 million.

(47)

(1) 'Irregularity detected by EU body' is reported in 4.1% of the 'over 1 mln' cases (in RD), against 1.3% of all RD cases; (2) 'Information published by the media': 1.4% in the 'over 1 mln' subset (in RD), against 0.4% in the all RD set; (3) 'Tip from informant, whistle-blower, etc.': 3.3% in the 'over 1 mln' subset, against 1.6% in the all set (difference is even bigger when focusing on market measures: 5.7% against 0.7%). Only cases where the amount of the reported irregularity is greater than zero have been considered.

(48)

See above, for an explanation of the role of exceptional cases in the 2017 steep increase in financial amounts involved in SA cases. RD cases instead decreased both in terms of numbers (-51%) and average financial amount (-14%).

(49)

In this context, a financial amount is considered 'exceptional' where it exceeds EUR 10 million.

(50)

See above, for an explanation of the role of exceptional cases in the 2017 steep increase in financial amounts involved in SA cases.

(51)

In this context, a financial amount is considered 'exceptional' where it exceeds EUR 10 million.

(52)

For the full description of the categories of irregularities and the related types of violations, please see Annex 12.

(53)

Italy reported most of these non fraudulent cases where the type of violation refers to 'false or falsified request for aid' or 'false or falsified documents'.

(54)

Italy reported many of these non fraudulent cases where the type of violation refers to 'false or falsified request for aid' or 'false or falsified documents'.

(55)

In this context, a financial amount is considered 'exceptional' where it exceeds EUR 10 million.

(56)

For the analysis of the reasons for performing controls, only cases where the amount of the reported irregularity is greater than zero have been considered. Within the same case, reference can be made to more than one reason for performing the control. This case has been counted in each 'reason' mentioned in the notification by the Member State. As a consequence, the sum of irregularities in Table NR16 (and similar Tables in this section) is higher than the actual number of relevant cases. This is why the row of totals is not included in the Table. Whenever reference is made to a 'global average', this must be understood as the average financial amount of the relevant cases (potential frauds affecting RD, for comments related to Table NR16, or non fraudulent irregularities affecting RD, for comments related to Table NR17). It is calculated on the basis of data in Table NR16 (or NR17) so it implies some double counting.

(57)

This comparison takes into consideration both the number of positive controls started for a specific reason and the difference between average financial amount associated to that specific reason and the global average.

(58)

For the analysis of the reasons for performing controls, only cases where the amount of the reported irregularity is greater than zero have been considered. Within the same case, reference can be made to more than one reason for performing the control. This case has been counted in each 'reason' mentioned in the notification by the Member State. As a consequence, the sum of irregularities in Table NR18 (and similar Tables in this section) is higher than the actual number of relevant cases. This is why the row of totals is not included in the Table. Whenever reference is made to a 'global average', this must be understood as the average financial amount of the relevant cases (potential frauds affecting market measures, for comments related to Table NR18, or non fraudulent irregularities affecting market measures, for comments related to Table NR19). It is calculated on the basis of data in Table NR18 (or NR19) so it implies some double counting.

(59)

In the graph associated to Table NR18, the upper straight line takes into consideration all cases, while the lower straight line is the result of not considering the 'judicial enquiry' outlier.

(60)

This scrutiny applies, for each period, to a number of undertakings which may not be less than half the undertakings whose receipts or payments, or the sum thereof, under the system of financing by the EAGF, amounted to more than EUR 150,000 for the previous financial year.

(61)

Nevertheless, concerning the average financial amount of the detected potential frauds, it should be considered that it is about EUR 476,000, based on the highest number of cases (69 – which should make the average more 'solid' than other 'reasons' where the average is based on less cases).

(62)

In relation to irregularities reported as fraudulent: 'rural development' = 5.8% and 'direct payments' = 4.5%. In relation to irregularities not reported as fraudulent: 'rural development = 1.1%; 'market measures' = 0; 'direct payments' = 1.4%

(63)

In the graph associated to Table NR19, the upper straight line takes into consideration all cases, while the lower trend line is the result of not considering the 'administrative enquiry' outlier.

(64)

Reg. 485/2008 repealed Reg. 4045/1989.

(65)

For the analysis of the reasons for performing controls, only cases where the amount of the reported irregularity is greater than zero have been considered. Within the same case, reference can be made to more than one reason for performing the control. This case has been counted in each 'reason' mentioned in the notification by the Member State. As a consequence, the sum of irregularities in Table NR20 (and similar Tables in this section) is higher than the actual number of relevant cases. This is why the row of totals is not included in the Table. Whenever reference is made to a 'global average', this must be understood as the average financial amount of the relevant cases (potential frauds affecting direct payments, for comments related to Table NR20, or non fraudulent irregularities affecting direct payments, for comments related to Table NR21). It is calculated on the basis of data in Table NR20 (or NR21) so it implies some double counting.

(66)

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

(67)

This includes cases where start date and end date were not filled in (1,532 cases, of which 49 cases reported as fraudulent) and one irregularity dated 1905.

(68)

COM (2018)457 on 6/6/2018. 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, 3.9.2018

SWD(2018) 386 final

COMMISSION STAFF WORKING DOCUMENT

Statistical evaluation of irregularities reported for 2017: 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

29th Annual Report on the Protection of the European Union's financial interests - Fight against fraud - 2017

{COM(2018) 553 final}
{SWD(2018) 381 final}
{SWD(2018) 382 final}
{SWD(2018) 383 final}
{SWD(2018) 384 final}
{SWD(2018) 385 final}

Contents

4.    The European Structural and Investment Funds (ESIF)    

4.1.    General analysis    

4.1.1.    Irregularities reported as fraudulent    

4.1.2.    Irregularities not reported as fraudulent    

4.1.3. Irregularities reported in relation to the Programming Period 2014-2020    

4.2.    Specific Analysis – Irregularities reported in relation to the Programming Period 2007-13    

4.2.1.    Objectives concerned by the reported irregularities    

4.2.2.    Priorities concerned by the reported irregularities    

4.3 Reasons for performing control    

4.3.1 Irregularities reported as fraudulent    

4.3.2 Irregularities not reported as fraudulent    

4.4.    Antifraud and control activities by Member States – programming period 2007-2013    

4.4.1.    Duration of irregularities    

4.4.2.    Detection of irregularities reported as fraudulent by Member State in relation to the programming period 2007-13    

4.4.3.    Fraud detection rate    

4.4.4.    Irregularity Detection Rate    

4.4.5.    Ratio of established fraud (programming period 2007-13)    

4.5 Other shared management Funds    

5.    Pre-Accession Policy (Pre-Accession Assistance and Instrument for Pre-Accession I and II)    

5.1.    The Pre-accession Assistance (PAA), 2000-06    

5.2.    The Instrument for Pre-accession 2007-13 – IPA I    

5.3.    The Instrument for Pre-accession 2014-20 – IPA II    

5.4.    General analysis    

5.4.1.    Pre-accession assistance (PAA)    

5.4.2.    Instrument for Pre-Accession (IPA I)    

5.5.    Specific analysis – Financial year 2017    

5.5.1.    Pre-Accession Assistance (PAA)    

5.5.2.    Instrument for Pre-Accession (IPA)    

6. Direct Management    

6.1. Introduction    

6.2. General analysis    

6.2.1. Five year analysis 2013-2017    

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    

United Kingdom    

ANNEXES    

4.The European Structural and Investment Funds (ESIF)

Over half of EU funding is channelled through the 5 European structural and investment funds (ESIF). They are jointly managed by the European Commission and the EU countries.

The purpose of all these funds is to invest in job creation and a sustainable and healthy European economy and environment.

The ESIF mainly focus on 5 areas:

–research and innovation;

–digital technologies;

–supporting the low-carbon economy;

–sustainable management of natural resources;

–small businesses.

The European structural and investment funds are:

–European regional development fund (ERDF) – promotes balanced development in the different regions of the EU;

–European social fund (ESF) - supports employment-related projects throughout Europe and invests in Europe’s human capital – its workers, its young people and all those seeking a job;

–Cohesion fund (CF) – 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 are Bulgaria, Croatia, Cyprus, the Czech Republic, Estonia, Greece, Hungary, Latvia, Lithuania, Malta, Poland, Portugal, Romania, Slovakia and Slovenia;

–European agricultural fund for rural development (EAFRD) 1 – focuses on resolving the particular challenges facing EU's rural areas;

–European maritime and fisheries fund (EMFF) – helps fishermen to adopt sustainable fishing practices and coastal communities to diversify their economies, improving quality of life along European coasts.

Due to the rules of functioning of the EMFF and (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 chapter jointly with the funds for cohesion and economic convergence.

All these funds are managed by the EU countries themselves, by means of partnership agreements. Each country prepares an agreement, in collaboration with the European Commission, setting out how the funds will be used during the current funding period 2014-2020. Partnership agreements lead to a series of investment programmes channelling the funding to the different regions and projects in the policy areas concerned.

For 2014-2020, EUR 454 billion 2 in ESIF funding has been allocated to promote job creation and growth. National co-financing is expected to amount to at least EUR 183 billion, with total investment reaching EUR 637 billion.

These resources will contribute to:

·Strengthening Research and Innovation;

·Supporting the digital single market;

·Supporting the growth of Europe’s small and medium-sized enterprises (SMEs);

·Supporting the energy union and the low-carbon economy;

·Investing in environmental protection and resource efficiency;

·Climate change and risk prevention;

·Supporting sustainable transport;

·Promoting sustainable and quality employment;

·Promoting social inclusion;

·Investing in education and training;

·Support youth employment;

·Strengthening institutional capacity and efficient public administration.

However, this section of the report will focus on previous programming periods 3 , as only a very limited part of the reported irregularities refer to the period 2014-2020.

4.1.General analysis

In comparison with the other budget sectors, the analysis of the cohesion policy poses a higher level of complexity, as information refers to different programming periods, which are regulated by different rules. 4

Table CP1 offers an overview of the number of irregularities (both fraudulent and non-fraudulent) reported from 2013 to 2017, by programming period (PP) and fund.

Table CP1 does not suggest any major diversion from known trends and patterns in detection and reporting of irregularities, with the exception of year 2015. In this year, the number of reported irregularities doubled, before decreasing in the following years. In relation to this 2015 peak, the following can be pointed out:

1)The increase was mainly related to the PP 2007-13.

a.It was for the greatest part linked to the reporting of irregularities by one Member State (Spain), which covered almost half of the total number of irregularities reported in 2015.

a.This Spanish anomalous increase was due to delayed reporting of irregularities detected throughout the programming period. If they were excluded, the number of reported irregularities would still be higher than in 2014. However, this increase would be more in line with the programming cycle of the funds.

b. When support is based on multi-annual programmes, it can be expected that the number of irregularities increases around the end of the eligibility period and decreases afterwards, when routine controls are less intense. In general, it should be kept in mind that increases in the number of reported irregularities can be influenced by detection capacity building by the Member State.

2)A minor, yet still striking increase in reporting was observed in relation to the previous PP 2000-06. The number of irregularities almost doubled from 2014 to 2015. In this respect, the explanation is belated reporting by another Member State (Ireland).

Table CP2 offers an overview by PP and fund of the financial amounts involved in irregularities detected and reported to the European Commission over the last five years. While the number of reported irregularities peaked in 2015 and gradually, but significantly decreased in the following years, the involved financial amounts were stable in 2016, before declining at a slower pace. This trend implied a raise of the average financial amounts, both in 2016 (+17%) and 2017 (+40.5%).

This was mainly due to:

·the high amounts involved in the irregularities affecting the Cohesion Fund, which finances infrastructure projects of very high value and in relation to which, sometimes, individual cases of irregularities involving very high amounts can be detected. The financial amounts related to PP 2007-2013 significantly increased in 2016 (+36%) while the financial amounts in 2017 were pushed further by irregularities related to PP 2014-2020;

·the steep upward trend in the average amount of the irregularities pertaining to the ERDF in the programming period 2007-2013 (+16% in 2016 and +53% in 2017) which represent the large majority of all irregularities. Furthermore, in 2017 irregularities related to PP 2014-2020 started to be significantly reported.

The trend of the financial amounts must be assessed while bearing in mind that it can be strongly influenced by single observations of significant value. During 2013-2017, cases which involved over EUR 5 million represented less than 1% in terms of numbers, but 38% in terms of amounts. 5 71% of these cases concerned the ERDF, while 22% concerned the Cohesion Fund. The average financial amount of cases related to the Cohesion fund was 33% higher than that of ERDF cases. In such a context, where such a significant portion of the financial amounts is linked to a relatively low number of cases, fluctuations are more likely and should not be misinterpreted.

While focusing on PP 2007-2013, section 4.3 will deal with the reasons why controls that led to discover irregularities were performed. That analysis will bring to a number of findings about the frequency and potential of information from media, EU bodies, tips and risk analysis. Here a different perspective is taken. Reference is made to the irregularities reported during the period 2013-2017, including all programming periods. Within this context, when focusing on the 'over 5 mln' cases, it can be noticed that these reasons for performing the control were more present than in the overall set of cases, in particular with regard to information from EU bodies. 6 Even if this is based on a relatively low number of cases, this corroborates the hypothesis that these targeted controls based on information from media, EU bodies, tips or risk analysis have the potential to lead to better results.

4.1.1.Irregularities reported as fraudulent

4.1.1.1.Trend by programming period

Table CP3 provides an overview by PP and fund of the irregularities reported as fraudulent in the last five years (2013-2017).

Irregularities reported as fraudulent in 2017 have increased by 10% since 2013, while they have decreased by 18% in comparison with the 2015 peak.

During the last five years, while the fraudulent irregularities linked to the PP 2000-06 have been decreasing to reach nearly 0 in 2017, those linked to the PP 2007-13 have peaked in 2015 and gradually decreased in the following years. These trends are linked to the implementation cycle of PP 2007-2013 and the closure of PP 2000-2006. Apart from very few cases in 2015 and 2016, reporting related to PP 2014-2020 started in 2017 (more than 10% of all cases reported in 2017 as fraudulent)

Table CP4 provides an overview by PP and Fund of the financial amounts involved in cases reported as fraudulent. As already indicated on several occasions, the trend of the financial amounts is more subject to fluctuations due to the possibility of individual cases involving high amounts. While the number of irregularities peaked in 2015, the involved financial amounts resumed strong growth in 2017. This was mainly due to irregularities pertaining the programming period 2007-2013, with noticeable increases for the Cohesion fund (+349%) and the ERDF (+34%), and the programming period 2014-2020, where significant reporting started for the Cohesion Fund. These increases were mainly due to higher financial amounts reported by Slovakia (Cohesion Fund and ERDF), Romania (ERDF) and Portugal (ERDF).

Focusing on PP 2007-2013, the financial amounts involved in irregularities reported as fraudulent for the ERDF were predominant (73% in 2013-2017), also due to the high share of EU financing that is channel through this fund..

4.1.1.2.Trend by Fund

The analysis of the same data presented in Tables CP3 and CP4 but focussed on the distribution of the irregularities reported as fraudulent by Fund (Tables CP5 and CP6), highlights the following situations:

(1)2015 witnessed a peak in the number of irregularities: this was the end year of eligiblity for Cohesion programmes (PP 2007-2013), when irregularities reported can be expected to increase. The number of irregularities reported by the MS in relation to PP 2007-2013 jumped, both with reference to the ERDF (+105%) and the ESF (+46%). The related financial amounts moved in the same direction (+166% for the ERDF and +268% for the ESF). In 2016, figures concerning the ESF reverted down to previous levels.

(2)2017 showed an increase in financial amounts despite a decrease in the number of irregularities. This was the year of closure of Cohesion programmes, when the number of irregularities can be expected to decrease, while the amounts involved are not strictly correlated to the number of irregularities. This increase was due to a growth in the financial amounts involved in CF irregularities (+611%) and, to a lesser extent, in ERDF irregularities (+38%);

(3)The highest number of cases and absolute financial amounts (not relative to payments) relate to the ERDF. The number of cases increased significantly from 2013 to 2017, due to an upward shift in 2015, followed by stable reporting in 2016 and a slight decline in 2017. The financial amounts increased until 2017 (with the exception of 2016). The average financial amount significantly increased in 2017 (+55%);

(4)Potential frauds affecting the Cohesion fund are now reported regularly (since 2010), and from 2016 to 2017 doubled, in terms of number, and became seven times higher, in terms of financial amounts. Fluctuations of the amounts, however, can be particularly significant in respect of these cases, because of fewer cases and high amounts involved in the projects financed by the Cohesion Fund.

(5)Both in terms of numbers and, even more, of financial amounts, cases related to the ESF peaked in 2015 and their share on the total during 2013-2017 exceeded 15%, in terms of financial amounts (similar to CF);

4.1.2.Irregularities not reported as fraudulent

Table CP7 provides an overview by PP and fund of the irregularities not reported as fraudulent in the last five years (2013-2017).

The reasons behind the high increase in 2015 have already been explained under section 4.1.

After 2015, the decrease in the number of irregularities was fast for the ERDF (as from 2016) and the ESF (as from 2017) and more gradual for the CF. 7 The financial amounts followed a different pattern and increased further in 2016, before falling in 2017, but not as much as the number of irregularities.

The average financial amounts for PP 2007-2013 have been increasing since 2016: CF (+49% in 2016), ERDF (+19% in 2016, +45% in 2017), ESF (+32% in 2016, +23% in 2017). For PP 2000-2006, the financial amounts reported in relation to the ERDF dropped in 2016. In general, irregularities for this PP are fading towards zero. Considering the fact that irregularities reported as fraudulent usually imply higher financial amounts, one may suppose that some of the cases notified as non-fraudulent might be reclassified later as potentially fraudulent.

In 2016, the reporting of irregularities referring to PP 2014-2020 started and increased in 2017, as implementation is progressing. Number and financial amounts are still low, but they can be expected to grow during next years, in line with the implementation cycle. Anti-fraud capacity building by Member States and new anti-fraud provisions may contribute to this increase. The average financial amounts are still lower than for PP 2007-2013 but, in this comparison with previous PP, the ESF sticks out, with very low averages of about EUR 8,300 and 14,800 in 2016 and 2017, respectively. 8  

Table CP8 shows the financial amounts involved in the irregularities not reported as fraudulent. Once more, as already mentioned several times in relation to the financial amounts, fluctuations can happen more often, as they can be linked to individual irregularities or groups of irregularities of significant value, which produce distortive effects from one year to the next.

4.1.3. Irregularities reported in relation to the Programming Period 2014-2020

Table CP9 provides an overview of all the irregularities and related financial amounts that have been reported up to 2017 with reference to PP 2014-2020.

Apart from a few cases in 2015, reporting of these irregularities started in 2016 and increased in 2017. This is consistent with the implementation cycle of the ongoing programming period. There is not enough data yet to present a meaningful analysis focusing on PP 2014-2020.

4.2.Specific Analysis – Irregularities reported in relation to the Programming Period 2007-13

This section of the analysis focuses on the irregularities reported in relation to the PP 2007-13. The closure for the programming period started in March 2017 9 ; it therefore offers an ideal opportunity to present an overview of what has happened. Consequently, the analysis will cover a greater time span than the previous section (2013 to 2017), to examine all information available, which dates back to 2008.

It will cover the following aspects:

·Objectives;

·Priorities and themes affected;

·Types of irregularity

4.2.1.Objectives concerned by the reported irregularities

The reported irregularities followed the pattern that could be expected in relation to the implementation cycle (Table CP10). The majority of the irregularities were notified over the last three years of the reference period and mainly concerned the Convergence objective (60% of the total), in line with the fact that this is the objective to which the greatest financial resources are allocated and in relation to which higher risks are associated. The anomaly concerning the year 2015 has already been explained. For 187 irregularities, the objective was not mentioned by the Member States.

Table CP11 provides information about the financial amounts involved in the reported irregularities. They broadly followed the same pattern of the number of irregularities in Table CP10, with the exception of the amounts linked to the Convergence objective reported in 2012, which exceeded those related to the following two years, and those related to 2016, which are higher than those reported in 2015. In 2016, irregular amounts reported in relation to the Cohesion Fund were exceptionally high, as already showed in Table CP2 and highlighted in section 4.1.

As for the number of irregularities, the majority of financial amounts were notified over the last three years and mainly concerned the Convergence objective (77%).

4.2.1.1.Irregularities reported as fraudulent by Objective

Table CP12 and CP13 include only the irregularities reported as fraudulent in relation to PP 2007-13. The trends are similar to those presented in the previous section for all irregularities in relation to PP 2007-2013. A difference that is worth highlighting is the strong increase in the number of irregularities in 2016 in relation to Convergence (while the sum of fraudulent and non fraudulent irregularities decreased) and the exceptional drop in 2016 in relation to 'Regional competitiveness and employment'.

With reference to the financial amounts, fluctuations are emphasized, as high profile cases can have a significant impact.

The higher share represented by the Convergence objective in comparison with that presented in the previous section is also significant (68% of cases and 88% of financial amounts).

Irregularities reported as fraudulent represented about 4.9% of the total number of irregularities reported for PP 2007-13. The highest percentage (Fraud Frequency Level – FFL 10 ) was related to the Fisheries (7.1%), the European Territorial Cooperation (6.6%) and to the Convergence (5.6%) objectives. Regional competitiveness and Employment had the lowest FFL (2.8%).

Financial amounts involved in irregularities reported as fraudulent represented about 14.7% of the total reported for PP 2007-13. The highest share (Fraud Amount Level – FAL 11 ) was related to the European Territorial Cooperation (19.9%), the Fisheries (18.2%) and the Convergence (16.7%) objectives. Regional competitiveness and Employment had the lowest FAL (4.7%).

The difference between FFL and FAL indicates the higher financial impact of fraudulent irregularities compared to the non-fraudulent infringements. As a matter of fact, the average financial value involved in irregularities reported as fraudulent is more than three times higher than that related to the non-fraudulent types.

4.2.1.2.Fraud and Irregularity Detection Rates by Objective

Table CP14 shows the FDR and the IDR per objective.

 Looking at the overall detection rate (FDR+IDR), Regional competitiveness and employment programmes show a relatively low level of detection. European Territorial Cooperation programmes, however, show an anomalously low level of detection (about four times lower than the previous objective), especially if one considers that the previous two indicators (FFL and FAL) were high. The situation is different for Convergence, Fisheries and Multiobjective programmes, where the detection rate approaches or is higher than 3%.

4.2.2.Priorities concerned by the reported irregularities 

4.2.2.1.Irregularities reported as fraudulent (fisheries not included)

The operational programmes financed by the Cohesion Policy are implemented in relation to the already mentioned objectives, but also along identified Priorities and Themes.

The information provided by the Member States allows for an analysis of the priority areas in relation to which projects potentially affected by fraudulent practices have been identified.

Table CP15 shows the number of irregularities reported as fraudulent by priority area since the beginning of the PP 2007-13, their related financial amounts, the average amount per irregularity, FFL, FAL and FDR.

In terms of numbers, the 'Priorities' most concerned were 'Research and Technological Development (RTD)', 'Increasing the adaptability of workers and firms, enterprises and entrepreneurs' and 'Improving access to employment and sustainability'.

Irregularities reported as fraudulent in relation to these three priorities represent about 37% of the total.

FFL is highest for 'Tourism' (11.7%) and 'Strengthening institutional capacity' (9.7%), while the top four priorities (in terms of FFL) in the Table are all above or equal to 9%, which is double the average.

From the financial amounts point of view, the most significant results concern 'Transport, 'RTD' and 'Urban and rural regeneration'. ‘Transport’ retains by far the highest average value, more than ten times R&TD and the overall average. Financial amounts related to the irregularities reported as fraudulent in relation to these three priorities represent 49% of the total.

FAL is highest for 'Urban and rural regeneration' (40%), 'Tourism' (33%), 'Investment in social infrastructure' (24%), and 'Increasing the adaptability of workers, firms, enterprises' (20%). 12 The priorities 'Tourism' and 'Urban and rural regeneration' stand out in terms of FDR.

Irregularities linked to the EFF have not been included. Reference to 'Technical assistance Fisheries' and 'Measures of common interest – fishery' in Table CP15 may depend on errors in encoding by Member States.

For about 27% of the irregularities used for this analysis information was not provided about the priority area concerned, decreasing in comparison with previous years.

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

The same analysis showed in the previous section for the irregularities reported as fraudulent is presented here for the irregularities not reported as fraudulent in relation to the PP 2007-13.

Table CP16 provides an overview of the number of irregularities not reported as fraudulent by priority area since the beginning of the PP 2007-13, their related financial amounts and average amount per irregularity and IDR.

Again, ‘Research and Technological Development (R&TD)’ was the priority with the highest number of occurrences, followed by ‘Environmental protection and risk prevention’ and ‘Transport’. ‘Research and Technological Development (R&TD)’ was first also in terms of financial amounts, closely followed by 'Transport' and, at a distance, by ‘Environmental protection and risk prevention’. Irregularities linked to these three priorities together represent 23.6% of the total number and 45.4% of the total amounts.

The priorities 'Tourism', ‘Research and Technological Development (R&TD)’, 'Information society' and  ‘Transport’ show a IDR higher than or equal to 2%.

Irregularities linked to the EFF have not been included. Reference to priorities specific to this policy area may depend on errors in encoding by national authorities.

The number of cases not reported as fraudulent for which information about the priority area concerned was missing remains high (45%) and higher than for the fraudulent irregularities, while it is improving.

4.2.2.3.Irregularities related to the priorities 'R&TD' and 'Transport' by theme

Research and Technological Development (R&TD)

As metioned, ‘Research and Technological Development (R&TD)’ is the priority for which the highest number of irregularities, fraudulent and non-fraudulent, have been detected and reported: in total, 4 965 cases, involving over EUR 2 billion.

Figure CP1 below, details the specific priority themes that were affected by these irregularities. The description of the themes has been shortened to simplify, but the full decription can be consulted in Annex 15. Please note that the larger the square, the higher the number of irregularities; the darker the colour, the higher the financial amounts involved.

Two "residual" themes are those showing the highest number of reported irregularities: 'Other investment in firms' and 'Other measures to stimulate research and innovation and entrepreneurship in SMEs'. Together they represented 48% of the reported irregularities, but only 21% of the related financial amounts. Conversely, the themes 'Investment in firms directly linked to research and innovation ' and 'R&TD activities in research centres' represented only 23.5% of the total number of reported irregularities, but accounted for almost 52% of the total financial amounts involved.

Figure CP2 shows the same level of detail for the irregularities reported as fraudulent.

Similarly to the overall picture, the highest number of irregularities reported as fraudulent affected the theme 'Other investment in firms', but it was followed by the theme 'Investment in firms directly linked to research and innovation'. The latter was also the theme with the largest share of the financial amounts involved in cases reported as fraudulent (40.5%), followed again - but at a distance - by the theme 'R&TD activities in research centres'. The latter was not frequent, but involved relatively high amounts, similarly to the theme 'Assistance in RTD, in particular SMEs'. On the contrary, the most frequently affected theme 'Other investment in firms' involved a low average financial amount.

The two most frequent themes accounted for 53.5% of cases and 53% of financial amounts. The two themes with the highest financial amounts accounted for 28% of cases and 55% of value.

Transport

As mentioned, 'Transport' was the priority for which the financial amounts involved in irregularities was similar to ‘Research and Technological Development (R&TD)’ (over EUR 1.8 billion). However, the average amount was the highest, both for irregularities reported as fraudulent (EUR 7,851,966) and not (EUR 876,902). 13  

Similar to Figure CP1, Figure CP3 below, details the specific priority themes that were affected by these irregularities.

'Regional/local roads' was the theme most frequently affected by irregularities (either fraudulent or non fraudulent), accounting alone for 46% of the total number. Nevertheless, the financial amounts involved in these cases were only 11% of the total. On the contrary, the themes 'Motorways (TEN-T)' and 'Railways' accounted only for 13% of the irregularities, but 60% of the financial amounts.

Figure CP4 shows the same level of detail for the irregularities reported as fraudulent.

The picture is similar when the focus is moved on the irregularities reported as fraudulent. 46% of these irregularities concern 'Regional/local roads' involving just 13% of the financial amounts. 'Motorways (TEN-T)' and 'Railways' accounted only for 19% of the irregularities reported as fraudulent, but 72% of the financial amounts.

4.2.2.4.Types of irregularities / modus operandi detected related to the priorities 'R&TD' and 'Transport'

Table CP17 provides an overview of the categories of irregularities reported in connection with the priority ‘Research and Technological Development (R&TD)’ within PP 2007-2013, including a focus on the irregularities reported as fraudulent. 14

The same irregularity may be associated to several categories of infringement. That is why the row of totals has been omitted: it would have resulted in multiple counting of the same notification of irregularity.

In general, 8% of cases affecting the priority ‘Research and Technological Development (R&TD)’ were reported as fraudulent (see table CP15).

Irregularities mainly took place during the implementation of a project as contract infringements, which implied that the project was not implemented according to what was initially agreed (category 'Infringement of contract provisions/rules'). This happened in 39% of all cases and 42% of cases reported as fraudulent. 8.6% of these violations were reported as fraudulent.

The following category refers to incorrect, missing, false or falsified supporting documents, which were used in 18% of all cases and 37% of cases reported as fraudulent. 84% of these violations were not reported as fraudulent, among which there were a few cases (17) of false or falsified supporting documents.

The category 'Eligibility / Legitimacy of expenditure / measure' was similarly present in all cases (17%) and in cases reported as fraudulent (15%).

Violation of public procurement rules were perpetrated in 14% of all 'RTD' cases (715 out of 4,965 irregularities – see Table CP17 and compare with Tables CP15 and CP16) and only 5.5% of cases reported as fraudulent (22 out of 398 irregularities – see Table CP17 and compare with Table CP15). Only 3% of the violations concerning public procurement were reported as fraudulent (22 violations out of 715 – see Table CP17).

In general, the category 'Ethics and Integrity' refers to violations concerning conflict of interest, bribery, corruption, but the residual type ‘Other irregularities concerning integrity and ethics’ was the most used (followed by 'conflict of interest'). Besides these two types of violation, only one case of corruption was reported.

Violations concerning 'ethics and integrity' were rarely reported, but were more frequent among irregularities reported as fraudulent (3%) than within the entire population of irregularities (0.5%). These violations are the ones with the relative highest frequency of potential fraud (48%).

Similarly to Table CP17, Table CP18 provides an overview of the categories of irregularities reported in connection with the priority ‘Transport’ within PP 2007-2013, including a focus on the irregularities reported as fraudulent.

In general, it can be noticed that 2.3% of cases affecting the priority ‘Transport’ were reported as fraudulent.

Infringements of 'public procurement' rules were the most reported (in 67% of cases), but only in less than 1% of cases these infringement were reported as fraudulent (9 violations out of 1,198 – see Table CP18).

Violations concerning 'ethics and integrity' were rarely reported, but were more frequent among irregularities reported as fraudulent (27%) than within the entire population of irregularities (0.7%). These violations were the ones with the highest relative frequency of potential fraud (92%). More specifically, the types of violations reported included 'Conflict of interest', 'Corruption' and 'Other irregularities concerning ethics and integrity'

Incorrect, missing, false or falsified documents were used only in 4% of all cases, but in 56% of cases reported as fraudulent. 70% of these violations were reported as non fraudulent, among which there were a few cases (3) of use of false or falsified documents.

Violations concerning 'Eligibility / Legitimacy of expenditure / measure' were the second most frequent category both among all irregularities and among the subset on irregularities reported as fraudulent.

4.2.2.5.Geographical distribution of irregularities (fraudulent and non-fraudulent) detected in relation to the 'R&TD' and 'Transport' priorities

Maps CP1 and CP2 show the geographical distribution of the irregularities (fraudulent and non-fraudulent) reported in relation to the priorities 'R&TD' and 'Transport'.

The contribution of Poland was significant and balanced between 'RTD' and 'Transport', as in both priorities this Member State detected about 25% of all relevant irregularities.

Other Member States were relatively more affected by (or were more efficient in detecting) irregularities related to 'RTD', such as Hungary, Italy, the United Kingdom, Portugal and Germany, while in other Member States irregularities related to 'Transport' weighed more, such as in Romania, Czech Republic, Latvia and Bulgaria. 15

4.3 Reasons for performing control

4.3.1 Irregularities reported as fraudulent

In the context of the antifraud cycle, the detection capability is a key feature, which contributes to the effectiveness and efficiency of the system for the protection of the EU budget.

Table CP19 provides an overview of the reasons why controls were performed with reference to the Cohesion policy for the PP 2007-2013, with a focus on controls that led to discover irregularities reported as fraudulent. 16 The description of the 'reason for performing control' has been shortened to simplify the Table and associated Charts and Graphs, but the full description can be consulted in Annex 14.

The straight lines in the graphs associated to Table CP19 represent the border between 'reasons' that led to identify irregularities with an average amount above or below the global average (that takes into account all potential frauds affecting the Cohesion policy for PP 2007-2013). The vertical distance between a point representing a specific reason and the straight line is an indicator of how higher or lower was the yield of controls started for that specific reason, in comparison with the hypothetical situation where these controls involved financial amounts in line with the global average 17 .

'Routine' is the most reported reason, but it shows a low average financial amount of the related irregularities.

The highest financial amounts were involved in irregularities where 'Judicial enquiry' was mentioned as a reason for performing the control. 62% of controls that started because of a judicial enquiry were concentrated in 3 Member States: Czech Republic, Poland and Romania.

Controls that were started because of information provided by whistle-blowers, informants, etc. or media were fewer, but led to good results, in particular in the case of media. The Czech Republic and Germany were the Member States with more tip-motivated controls leading to discover a potentially fraudulent irregularity (informants, whistle-blowers, etc.). Media-motivated controls were performed more frequently in the Czech Republic.

Controls that started because of 'information and/or request by an EU-body' are largely above-the-average, in terms of average financial amount of the related irregularities.

'Risk analysis' is not often reported as the reason for performing a control that led to identify an irregularity reported as fraudulent. Basically, all of these instances were reported by Slovakia. The average financial amount of these cases is largely above-the-average.

4.3.2 Irregularities not reported as fraudulent

Table CP20 provides an overview of the reasons why controls were performed with reference to the Cohesion policy and PP 2007-2013, with a focus on controls that led to identify irregularities not reported as fraudulent. 18 For an explanation of the associate graphs, please see section 3.3.1. The description of the 'reason for performing control' has been shortened to simplify the Table and associated Charts and Graphs, but the full description can be consulted in Annex 14.

'Routine' is the most reported reason, but it shows a low average financial amount.

On average, when a control is started because of a 'judicial' enquiry, the financial amount involved is very high. These cases were concentrated in Italy, the Czech Republic, Poland and Lithuania.

Also 'Media' is a reason that led to discover irregularities with an average financial amount above the relevant global average. Similarly to the irregularities reported as fraudulent, many of these cases were reported by the Czech Republic.

A noticeable number of cases were started because of information from an EU body or an irregularity detected and reported by an EU body. Both typologies showed high average financial amounts.

'Risk analysis' led to identify a number of irregularities, which involved an average financial amount below the relevant global average. Most of these irregularities were detected in Poland.

Another reason that might imply some form of risk analysis ('comparison of data') led to better results in terms of financial amounts, but it also showed a relatively low frequency or low 'detection capability' (208 cases against 7,851 cases identified by 'routine'). Lithuania, the Czech Republic and Portugal reported the majority of the 'Comparison of data' cases.

4.4.Antifraud and control activities by Member States – programming period 2007-2013

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

The present section aims at examining some aspects linked to the antifraud and control activities and results of Member States. Four elements are taken into account:

·the duration of the irregularities;

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

·the fraud detection rate (FDR - the ratio between the amounts involved in cases reported as fraudulent and the payments occurred in relation to the PP 2007-13) and the irregularity detection rate (IDR - the ratio between the amounts involved in cases not reported as fraudulent and the payments occurred in relation to the PP 2007-13)  19 ;

·the ratio of cases of established fraud on the total number of irregularities reported as fraudulent.

4.4.1.Duration of irregularities 

Of the 39,803 irregularities (fraudulent and non-fraudulent) reported by Member States in relation to the PP 2007-13, 19,663 (49% of the total) involved infringements that have been protracted during a span of time. For the 1,934 irregularities reported as fraudulent, this percentage is higher at about 61%. The remaining part of the dataset refers to irregularities which consisted of a single act identifiable on a precise date (about 23% of the whole dataset and 28% of that including exclusively the fraudulent irregularities) or for which no reliable information has been provided 20 (28% of the whole dataset and 12% of the irregularities reported as fraudulent).

The average duration of the irregularities which have been protracted over time was 21 months (i.e. 1 year and 9 month). For the irregularities reported as fraudulent, this average was similar: 20 months.

4.4.2.Detection of irregularities reported as fraudulent by Member State in relation to the programming period 2007-13

Map CP3 shows the number of irregularities reported as fraudulent by Member State in relation to the PP 2007-13.

Only Luxembourg has notified no irregularity as fraudulent; thirteen (13) Member States reported less than 30 potentially fraudulent irregularities; four (4) countries reported between 30 and 60; three (3) Member States between 60 and 90; six (6) more than 90.

Poland, Romania and Germany are the three countries which have reported the highest numbers.

4.4.3.Fraud detection rate

The fraud detection rate compares the results obtained by Member States in their fight against fraud with the related payments. Considering the multi-annual nature of the cohesion policy spending programmes, no annual analysis is proposed, focusing instead on the whole PP 2007-13, for which the documents for closure have been presented during 2017.

The FDR is the highest for Slovakia and Romania, above 1%. Other Member States (Czech Republic, Latvia, Slovenia, Poland and Portugal) show a FDR between 0.5% and 1%.

Programmes under the Territorial Cooperation Programme (designated in the table under the country code 'CB', last row before the total) can involve several countries and, therefore, paid amounts are spread among the beneficiaries in various Member States. However, in general, irregularities for these programmes are reported by the Member State in which the expenditure is paid out by the beneficiary in implementing the operation. For this reason, the sums paid have been included in the total, while the irregularities reported as fraudulent and the related amounts have already been computed in relation to the country having reported them. The 'CB' numbers have been included in the table to calculate the FDR related to these programmes, but they are not summed in the total row to avoid a double counting.

4.4.4.Irregularity Detection Rate

The irregularity detection rate compares the results obtained by Member States in detecting non-fraudulent irregularities with the related payments. Considering the multi-annual nature of the Cohesion policy spending programmes, no annual analysis is proposed, focusing instead on the whole programming period 2007-13, for which the documents for closure have been presented during 2017.

The IDR is the highest for Slovakia (nearly 10%) and for Czech Republic, Spain and Greece (between 4% and 5%).

Programmes under the Territorial Cooperation Programme (designated in the table under the "country-code" 'CB', last row before the total) can involve several countries and, therefore, paid amounts are spread among the beneficiaries in various Member States. However, in general, irregularities for these programmes are reported by the Member State in which expenditure is paid out by the beneficiary in implementing the operation. For this reason, the sums paid have been included in the total, while the irregularities not reported as fraudulent and the related amounts have already been computed in relation to the country having reported them. The 'CB' numbers have been included in the table to calculate the IDR related to these programmes, but they are not summed in the total row to avoid a double counting.

4.4.5.Ratio of established fraud (programming period 2007-13)

Table CP23 shows the ratio between the cases of established fraud and the total number of irregularities reported as fraudulent (including suspected and established fraud) in the period 2009-13. Taking into account only cases reported in 2017 would be meaningless, as the criminal proceedings leading to a conviction for fraud may take several years, while using the period 2010-14 or later periods would make it impossible to make a sound comparison with figures published in the 2013 Report.

Table CP23 is integrated with the ‘Dismissal ratio’, calculated as the differences between the total number of irregularities reported as fraudulent at the time of the 2013 Report and the total that takes into account the updates received until the end of 2017. A positive ratio means that Member States have classified as ‘suspected’ or ‘established fraud’ irregularities appearing as non-fraudulent in 2013.

In this respect, the average ratio of established fraud at EU level is 16%, increasing from 14% of 2016. The dismissal ratio is 11%.

If one considers exclusively the “decisions” (established + dismissed) of the 176 decided cases (98 established fraud and 78 dismissals), 56% is the ‘conviction rate’ and 44% the ‘dismissal rate’.

4.5 Other shared management Funds

There are other funds used under shared management. Table CP24 provides an overview of all the irregularities and related financial amounts that have been reported up to 2017 with reference to:

·Asylum, Migration and Integration Fund (AMIF): This Fund was set up for the period 2014-20, with a total of about EUR 3.1 billion. It is meant to promote the efficient management of migration flows and the implementation, strengthening and development of a common Union approach to asylum and immigration. The largest share of the total amount of the AMIF (approximately 88%) is to be channelled through shared management. Member States implement their multiannual National Programmes, which are prepared, implemented, monitored and evaluated by the responsible national authorities, in partnership with the relevant stakeholders in the field, including the civil society. All Member States except Denmark participate in the implementation of this Fund. Examples of beneficiaries of the programmes implemented under this Fund can be state and federal authorities, local public bodies, non-governmental organisations, humanitarian organisations, private 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. FEAD supports Member States' actions to provide material assistance to the most deprived, including food, clothing and other essential items for personal use. Material assistance needs 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 about 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 losing 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 2014-20, with a total of EUR 3.8 billion. The Fund promotes the implementation of the Internal Security Strategy, law enforcement cooperation and the management of the Union's external borders. The ISF is composed of two instruments, ISF Borders and Visa (B&V) and ISF Police. For the 2014-20 period

oEUR 2.76 billion is available for funding actions under the ISF B&V instrument, of which EUR 1.55 billion are to be channelled through shared management. All Member States except Ireland and the United Kingdom participate in the implementation;

oabout EUR 1 billion is available for funding actions under the ISF Police instrument, of which EUR 662 million are to be channelled through shared management. All Member States except Denmark and the United Kingdom participate in the implementation.

·Youth Employment Initiative (YEI): While supporting the Youth Guarantee, YEI is targeted to 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 total budget of the YEI 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 EUR 4.4 billion more from ESF national allocations.

5.Pre-Accession Policy (Pre-Accession Assistance and Instrument for Pre-Accession I and II)

Pre-Accession Assistance is provided through decentralised management where third countries distribute funds but account to the EU for how it is spent. In the last stages new Member States manage pre-accession funds under shared management to help them complete the transition. The goal of the EU as a global player is also promoted through direct management.

The assistance in pre-accession is provided on the basis of the European Partnerships of the potential candidates and the Accession Partnerships of the candidate countries. The current candidate countries are Albania, the Former Yugoslav Republic of Macedonia (FYROM), Montenegro, Serbia and Turkey. Potential candidate countries are Bosnia and Herzegovina and Kosovo 21 .

5.1.The Pre-accession Assistance (PAA), 2000-06 

The old Pre-accession Assistance (PAA), regarding the period 2000-06, was financed by a number of European Union programmes and financial instruments for candidate countries or potential candidate countries, namely the programmes for candidate countries, PHARE , SAPARD and ISPA , Phare Cross-Border Cooperation (CBC) and Coordination, Pre-accession financial assistance for Turkey 22 , Assistance for reconstruction, development and stabilisation for potential candidate countries ( CARDS ) 23 and Transition facility 24 .

5.2.The Instrument for Pre-accession 2007-13 – IPA I 

The Instrument for Pre-Accession Assistance (IPA), which covered the period 2007-2013, was delivered through five components. The policy and programming of IPA consisted of Multi-Annual Indicative Financial Framework (MIFF) on a three year basis, established by country, component and a theme, and Multi-Annual Indicative Planning Documents (MIPDs) per country or per groups of countries (regional and horizontal programmes). The Candidate Countries had to submit also Strategic Coherence Frameworks (SCF) and Multi-annual Operational Programmes, both regarding IPA Components III and IV. Their principal aim was to prepare beneficiary countries for the future use of the Cohesion policy instruments by imitating closely its strategic documents, National Strategic Reference Framework (NSRF) and Operational Programmes (OP), and management modes.

The financing of IPA was provided by the five following different components and European Commission's Directorate General 'Neighbourhood & Enlargement Negotiations' leads in the coordination of the instrument:

(1)Component I, Transition Assistance and Institution Building (TAIB), managed by the European Commission's Directorate General 'Neighbourhood & Enlargement Negotiations';

(2)Component II, Cross-Border Cooperation, in part managed by the European Commission's Directorate General 'Neighbourhood & Enlargement Negotiations' and in part managed, under shared management with Member States, by European Commission's Directorate General 'Regional Policy';

(3)Component III, Regional Development, managed by the European Commission's Directorate General 'Regional Policy';

(4)Component IV, Human Resources Development, managed by the European Commission's Directorate General 'Employment, Social Affairs and Inclusion'; and

(5)Component V - Rural Development, managed by the European Commission's Directorate General 'Agriculture and Rural Development'.

The pre- and post-accession assistance was implemented through a variety of management modes which take into account different levels of preparedness of the beneficiary countries. The assistance under IPA was designed also to prepare the beneficiary countries to assume full responsibility for the management of financial assistance granted by the EU.

The eligibility for IPA components differs depending on the state of preparedness. In the use of funds the IPA beneficiary countries were divided into two categories. Croatia and the EU candidate countries: the Former Yugoslav Republic of FYROM, Serbia and Turkey; were eligible for all five components of IPA. While the new candidate countries, Albania and Montenegro (candidate status awarded in 2010), remained outside the scope of intervention of IPA Component III, the regional development. The Potential candidate countries in the Western Balkans (Albania, Bosnia and Herzegovina, Montenegro and Kosovo) were eligible only for the first two components. 25

Implementation of Components I and II falls under the responsibility of DG 'Neighbourhood & Enlargement Negotiations', which initiated the components under a centralised management mode, with a view to transferring implementation management powers to the beneficiary countries as soon as their administrative capacities are considered sufficiently developed to ensure sound financial management. The EU Delegations play a major role in the delivery of IPA, in particular under the de-concentrated and decentralised management modes. 26

The implementation can be handled:

·directly by central management: funds are managed by DG 'Neighbourhood & Enlargement Negotiations' at headquarters;

·directly de-concentrated: funds are managed by EU Delegations under the supervision;

·directly centralised: cross-delegated when funds are managed by another service of the Commission through cross sub-delegation;

·indirectly in a centralised indirect management: funds are managed by executive agencies, specialised Community bodies (such as the European Investment Bank or the European Investment Fund) and national or international public-sector bodies or bodies governed by private law with a public-service mission;

·indirectly decentralised with ex ante control: funds are managed by accredited national authorities of the beneficiary country, but procurement is subject to ex ante control by the EC Delegation;

·decentralised without ex ante control: funds are managed by accredited national authorities of the beneficiary country and are not subject to ex ante controls by an EC Delegation;

·joint: funds are jointly managed with International Organisations (EBRD, EIB, Sigma, UN agencies, etc.)

5.3.The Instrument for Pre-accession 2014-20 – IPA II 

Prepared in partnership with the beneficiaries, IPA II sets a new framework for providing pre-accession assistance for the period 2014-2020.

The most important novelty of IPA II is its strategic focus. Country Strategy Papers are the specific strategic planning documents made for each beneficiary for the 7-year period. These will provide for a stronger ownership by the beneficiaries through integrating their own reform and development agendas. A Multi-Country Strategy Paper will address priorities for regional cooperation or territorial cooperation.

IPA II targets reforms within the framework of pre-defined sectors. These sectors cover areas closely linked to the enlargement strategy, such as democracy and governance, rule of law or growth and competitiveness. This sector approach promotes structural reform that will help transform a given sector and bring it up to EU standards. It allows a move towards a more targeted assistance, ensuring efficiency, sustainability and focus on results.

IPA II also allows for a more systematic use of sector budget support. Finally, it gives more weight to performance measurement: indicators agreed with the beneficiaries will help assess to what extent the expected results have been achieved.

·The priorities outlined in the Strategy Papers are translated into detailed actions, which are included in annual or multi-annual Action Programmes. IPA II Action Programmes take the form of Financing Decisions adopted by the European Commission.

·The bulk of the assistance is channelled through the Country Action Programmes for IPA II Beneficiaries, which are the main vehicles for addressing country-specific needs in priority sectors as identified in the indicative Strategy Papers.

·Multi-Country Action Programmes aim at enhancing regional cooperation (in particular in the Western Balkans) and at adding value to the Country Action Programmes through other multi-beneficiary actions.

·Cross-Border Cooperation Programmes represent the focus of assistance in the area of territorial cooperation between IPA II beneficiaries, another important form of financial assistance.

Assistance for agriculture and rural development is also addressed via Rural Development Programmes.

IPA II funded activities are implemented and managed in various ways, in accordance with the Financial Regulation:

·Under direct management; i.e. the implementation of the budget is carried out directly by the European Commission until the relevant national authorities are accredited to manage the funds.

·Under indirect management; i.e. budget implementation tasks are delegated to and carried out by entities entrusted by the European Commission; they can be:

-the IPA II beneficiary or an entity designated by it (one of the main objectives of IPA II is to encourage beneficiaries to take ownership and responsibility for implementation; indirect management by the IPAII beneficiary is therefore expected to become the norm);

-an agency of a Member State or, exceptionally, of a third donor country;

-an international organisation; or

-an EU specialised (but not executive) agency.

In other words, the European Commission delegates the management of certain actions to external entities, while still retaining overall final responsibility for the general budget execution.

·Shared management; i.e. implementation tasks are delegated to EU member states (only for cross–border cooperation programmes with EU countries).

In the context of direct management, Sector Budget Support is yet another tool for delivering pre-accession assistance and achieving sustainable results under IPA II. It consists of financial transfers to the national treasury account of an IPA II beneficiary and requires performance assessment and capacity development, based on partnership and mutual accountability. It is delivered through Sector Reform Contracts.

Implementation of IPA II includes a comprehensive monitoring mechanism. It provides for a review of overall performance of the progress in achieving results at the strategic, sector and action levels (i.e. results-based performance), in addition to monitoring of financial execution. Performance measurement will be based on indicators set out in the indicative Strategy Papers and the Programmes.

Joint monitoring committees (European Commission and beneficiaries) will continue to monitor the implementation of financial assistance programmes, as was the case for the previous period of IPA.

The Commission publishes an annual report on pre-accession assistance. This report covers the previous budget year.

5.4.General analysis

5.4.1.Pre-accession assistance (PAA)

Regarding the Pre-Accession Assistance (PAA), the number of reported irregularities decreased further in 2017 compared to the previous year. The downward trend, which started in 2009, was confirmed during the last five years, as Table PA1 shows.

With the phasing out of the pre-accession programmes, for the second year in a row, the number of irregularities reported as fraudulent approached zero.

In the past five years, most of the irregularities, fraudulent and non-fraudulent (97% of the total) and the highest aggregate amount (99.7% of the total) were reported by Romania and Bulgaria. In relation to the distribution of irregularities according to funds, the highest numbers related to SAPARD (58%), while the highest amounts involved related to ISPA (50.5%) and SAPARD (42%). Irregularities concerning ISPA recorded the highest average financial amount involved, which was nearly four times the average related to SAPARD.

5.4.2.Instrument for Pre-Accession (IPA I)

Generally it can be said that the trend of IPA reporting (financial framework 2007-13) has begun to develop in a stable upward curve which means a continuous increase in the number of irregularities reported and involved amounts since 2014. The increasing trend can be considered within the norm as the reporting of irregularities of IPA has only begun in recent years.

Table PA2 details the underlining data and shows the evolution of reporting of all the irregularities (reported and not reported as fraudulent) since 2013. The number of irregularities reported as non fraudulent jumped to a new level in 2014 and then experienced limited fluctuations in the following years. The financial amounts involved did not mirror this trend. In 2017, they doubled with respect to 2016 and reached the peak since 2013. Similarly to what happened for the irregularities not reported as fraudulent, the number of irregularities reported as fraudulent shifted upwards, but in 2015. The financial amounts experienced fluctuations that did not follow changes in numbers. Nevertheless, in 2017, the highest financial amounts were recorded (since 2013).

During the last five years, the highest number of reported irregularities was communicated by Turkey, Bulgaria and Croatia. Most of the financial amounts (89%) were involved in irregularities reported by Turkey. The highest number of irregularities was recorded in relation to Cross-Border Cooperation (38% of the total number) and IPARD (33%). IPARD recorded by far the highest financial amounts (55% of the total).

5.5.Specific analysis – Financial year 2017

5.5.1.Pre-Accession Assistance (PAA)

In 2017, only one irregularity was reported as fraudulent by Romania, as shown in Table PA3. Turkey reported 4 irregularities as non fraudulent.

All cases reported as non fraudulent concerned the Pre-accession financial assistance for Turkey. The irregularity reported as fraudulent cases concerned PHARE.

5.5.2.Instrument for Pre-Accession (IPA)

In relation to IPA I (2007-13), there were 17 irregularities reported as fraudulent in 2017, for an overall financial impact of more than EUR 3 million. Tables PA5 and PA6 show, respectively, the breakdown per country and per component.

In 2017 Turkey was the country reporting the highest number of irregularities and the related financial amounts. Concerning the irregularities reported as fraudulent, 15 out of these 17 cases were notified by Turkey.

Rural Development programmes accounted for the highest number of cases (49%) and, even more, financial amounts involved (72%).

Concerning the modus operandi, the most frequent category of irregularity refers to 'public procurement' (not in combination with other categories) and most of these cases are not reported as fraudulent. When the focus move on the irregularities reported as fraudulent, the most frequent category is 'documentary proof': in all these cases, the 'false and/or falsified documents' type of violation is mentioned.

For the programming period 2014-2020, no specific analysis is presented, because only one case has been reported so far.

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 27 , ‘direct management’ means that the Commission implements the budget by its departments, including its staff in the Union Delegations under the authority of their respective Head of Delegation, or through executive agencies.

For financial year 2017, a total of EUR 19.65 billion 28 has been effectively disbursed under the ‘direct management’ mode. Table DM1 presents the actual payments made in financial year 2017 for the twenty policy areas corresponding to 97.6% of the overall operational payments made under ‘direct management’.

Table DM1 – Payments made in financial year 2017 per policy area

6.2. General analysis

In 2017, for the twenty policy areas, the Commission services registered 1650 recovery items 29 in ABAC that were qualified as irregularities for a total financial value EUR 71.48 million. Among these recovery items, 65 have been reported as fraudulent, involving EUR 7.33 million irregular amounts.

However, it has to be underlined that qualifications attributed to recovery items may change over the years: it may happen that cases of irregularities are turned to suspicions of fraud or the other way round, suspicions of fraud are reclassified as non-fraudulent irregularities upon the closure of the OLAF investigation. As a consequence, no direct conclusion can be drawn from the data with regard to the general trend of irregularities or fraud in this budget area.

6.2.1. Five year analysis 2013-2017

The below analysis gives an overview of recovery data recorded in the ABAC system in the last five years. From a purely statistical point of view, it can be said that between 2013 and 2017, the average number of recovery items qualified as ‘irregularities reported as fraudulent’ 30 was 41. 2014 and 2017 are years where more such recovery items were registered with higher corresponding recovery amounts. The ratio between the amounts related to ‘irregularities reported as fraudulent’ and relative expenditure 31 is very small, it remains close to zero (0.027%) in the given five year period. This ratio has been stable for many years now. Figures are presented in Table DM2 below.

Table DM2 – Irregularities reported as fraudulent and related amounts, financial years 2013-2017

With regard to ‘irregularities not reported as fraudulent’ the average number of recovery items registered per year is 1575. The figure for 2017 is exactly in line with this average, as it is demonstrated by table DM3 below.

Table DM3 – Irregularities not reported as fraudulent and related amounts, financial years 2013-2017

Between 2013 and 2017, there were all together 7875 registered recovery items qualified as ‘irregularities not reported as fraudulent’ with the aggregate recovery amount of EUR 396.02 million.

The ratio between the aggregate irregular amounts corresponding to the recovery items (classified as ‘irregularities not reported as fraudulent’ between 2013 and 2017) and the reference figure of the related expenditure is about half a percent (0.490%). This ratio has been stable for many years now.

All these figures have to be interpreted in positive terms; they demonstrate 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 a picture of irregularity statistics with a breakdown of the twenty policy areas for year 2017.

Table DM4 – Irregularities reported by policy areas and related amounts, 2017

In the financial year 2017, the highest numbers of recovery items qualified as 'irregularities not reported as fraudulent' were recorded in the ‘Research and innovation’ budget area (487). It was also this policy field where the highest irregular amounts were registered (EUR 16.37 million). It was followed by ‘Communications networks, content and technology’ with the second highest number of recovery items (300) and related financial amount (EUR 15.32 million). These two policy areas account for almost half of the overall irregular recovery amounts for the year 2017 (49.40%). They are followed by the next policy areas: ‘Foreign Policy Instruments’ (EUR 5.23 million), ‘Mobility and transport’ (EUR 4.78 million) and ‘Humanitarian aid and civil protection’ (EUR 4.42 million). These three policy areas account for another 22.49% of the total irregular amounts recovered.

Regarding ‘irregularities reported as fraudulent’, there were 65 recovery items registered. Over the half of them concerned budget area ‘Communications networks, content and technology’ (38 items), followed by ‘Research and innovation’ (8 items), ‘Education and Culture’ (7 items) and budget areas.

The total relate irregular amounts were EUR 7.33 million, out of which policy area ‘Communications networks, content and technology’ alone counts for more than half (EUR 3.84 million).

The five year perspective of irregularities regarding the twenty policy fields is presented hereunder by table DM5.

Table DM5 – Irregularities reported by policy areas and related amounts, financial years 2013-2017

Over a five year period, it is also in ‘Communications networks, content and technology’ policy field, where the highest aggregate recovery amounts (EUR 11.88 million) were recorded in relation to ‘irregularities reported as fraudulent’ Representing more than half (55.15%) of the total amounts. It is followed by policy areas ‘Research and innovation’ (EUR 2.47 million), ‘International Cooperation and Development’ (EUR 1.79 million), and ‘Education and culture’ (EUR 1.69 million), yet with much smaller amounts.

Regarding ‘irregularities not reported as fraudulent’, the highest aggregate recovery amounts were recorded in the policy area of ‘Mobility and transport’ during the last five years (EUR 85.01 million). It is followed by ‘Research and innovation’ (EUR 77.64 million) and then by ‘Communications networks, content and technology’ (EUR 61.95 million) policy fields. These three policy areas account for about one third (32.27%) of the total recovery amounts related to ‘irregularities not reported as fraudulent’ over the past five years. Another one third (30.30%) of the aggregate recovery amounts were recorded in relation to policy fields ‘International Cooperation and Development’, ‘Energy’, ‘Foreign Policy Instruments’, ‘Education and culture’, and ‘Neighbourhood and enlargement negotiations’. However, compared to the overall payments made during the last five years for the twenty policy fields, the irregularity rate remains very low, on average 0.490%.

6.3.2. Recoveries according to legal entity residence

87.0% of the total number of recovery items and 88.7% if the corresponding recovery amounts qualified as ‘irregularities not reported as fraudulent’ concerned legal entities that are resident of the European Union. It should be noted however, that the residence of the legal entity is not necessarily the same as that of the main beneficiary. Nevertheless, in 84.3% of these irregularities and 86.5% of the corresponding amounts, the main beneficiary was also an EU Member State. In case of ‘irregularities reported as fraudulent’, these ratios are somewhat higher: 93.7% of the total number of recovery items and 95.2% if the corresponding recovery amounts concerned a legal entity residing in an EU country, and in 82.9% of these cases and 86.8% of the amounts concerned a final beneficiary that is also resident in an EU country.

Table DM6 – Recoveries per country of residence of the legal entity, 2013-2017

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

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 gives a breakdown of the recoveries by source of detection and by qualification in the last five years.

Table DM7 – Irregularities reported by source of detection and by qualification, 2013-2017

Regarding the ‘irregularities reported as fraudulent’, ‘OLAF’ has been marked as the source of detection in relation to 57.3% of recovery items corresponding to 67.3% of total recovery amounts. In 2017, 78.5% of such cases were detected by ‘OLAF’ together with 79.6% of related amounts. Meanwhile ‘Ex-post controls’ was the source of detection of another 34.5% of this type of recovery items corresponding to another 27.0% of recovery amounts.

The 82.3% of ‘irregularities not reported as fraudulent’ were detected through Commission controls. There is an increasing tendency over the past five years both in terms of number and of financial value of cases detected due to the effective ex-ante and ex-post controls. In 2017, 93.9% of these recovery items were detected by such controls involving 88.8% of the corresponding irregular amounts.

6.3.4. Types of irregularity

The Commission services also have to indicate the type of irregularity in the recovery context for the respective recovery item in question. Several types can be attributed to one recovery item. When it comes to ‘irregularities reported as fraudulent’ irregularity type ‘Amount ineligible’ appears the most frequently in the past five years, followed by types ‘Documents missing’. 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 occurrence of each type over the last five years.

Table DM8 – Types of irregularity, 2013-2017

The figures for irregularity type frequency are stable and have been providing the same pattern since many years.

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 beneficiary.

For the recovery orders issued between 2013 and 2017, 63.26% of the total irregular amounts have already been recovered. This percentage is exactly the same as for period 2012-2016. Yet, there are differences between the recovery rates depending on the qualification. The recovery rate for ‘irregularities reported as fraudulent’ (34.49%) remains well below the one calculated for ‘irregularities not reported as fraudulent’ (64.82%).

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

United Kingdom

ANNEXES

ANNEX 1

ANNEX 2

(The number of irregularities reported as fraudulent measures the results of efforts by Member States to counter fraud and other illegal activities affecting EU financial interests; it should not be interpreted as the level of fraud in their territories)

ANNEX 3