EUROPEAN COMMISSION
Brussels, 11.10.2019
SWD(2019) 365 final
COMMISSION STAFF WORKING DOCUMENT
Statistical evaluation of irregularities reported for 2018: 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
30th Annual Report on the Protection of the European Union's financial interests - Fight against fraud - 2018
{COM(2019) 444 final} - {SWD(2019) 361 final} - {SWD(2019) 362 final} - {SWD(2019) 363 final} - {SWD(2019) 364 final}
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 2014-2018
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. Cases 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 2014-2018
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 during the period 2014-2018
3.4.2.2.
Reported in 2018
3.4.3.
Fraud and Irregularity Detection by sector and Member State
3.4.3.1.
Rural development
3.4.3.2.
Market measures
3.4.3.3.
Direct payments to farmers
3.4.3.4.
Concentration by sector and type of irregularity
3.4.4.
Ratio of established fraud / Dismissal ratio
3.5.
Recovery cases
1. Introduction
1.1. Scope of the document
The present document is based on the analysis of the notifications provided by national authorities of cases of irregularities and suspected or established fraud. Their reporting is performed in fulfilment of a legal obligation enshrined in sectoral European legislation.
The document accompanies the Annual Report adopted on the basis of article 325(5) of the Treaty on the Functioning of the European Union (TFEU), according to which “The Commission, in cooperation with Member States, shall each year submit to the European Parliament and to the Council a report on the measures taken for the implementation of this article”.
For this reason, this document should be regarded as an analysis of the achievements of the 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.
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 four sections, dedicated to shared, decentralised and centralised management modes.
The sections dedicated to shared management, cover 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.
15 Annexes complement the information and data, 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 14 complement information on the methodology for the analysis of irregularities concerning expenditure, Annex 15 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 2019) and aims to provide an overview of the reported cases of fraud and irregularities reported for 2018 together with their financial impact.
2.2. General analysis –Trend analysis
2.2.1. Reporting years 2014-2018
The number of irregularities reported as fraudulent and non-fraudulent via OWNRES for 2018 (4 563) is about 11 % lower than the average number of cases reported for the 2014-2018 period (5 139).
The total estimated and established amount of TOR involved (EUR 615 million) is about 22 % higher than the average estimated and established amount for years 2014-2018 (EUR 504 million).
In 2018, seven big cases for a total amount of about EUR 216 million were reported compared to 2017, when two big cases with a total amount of about EUR 37 million affected the total estimated and established amount. Luxemburg and Malta 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 (2014-2018)
Annex 1 of the summary tables shows the situation on the cut-off date (15 March 2019) for the years 2014-2018.
2.2.1.1. Irregularities reported as fraudulent
The number of cases reported as fraudulent registered in OWNRES for 2018 (473) is currently 20% lower than the average number of cases reported for the 2014-2018 period (594).
The total estimated and established amount of TOR involved (EUR 165 million) represents a increase of 37% of the average estimated and established amount for the years 2014-2018 (EUR 120 million).
For 2018, the Czech Republic, Luxemburg, and Malta 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 (2014-2018)
On the cut-off date (15 March 2019), 10 % of all cases detected in 2018 were classified as fraudulent. The percentage increased slightly in comparison to 2017 (9,5 %).
Annex 2 of the summary tables shows the situation on the cut-off date for years 2014-2018.
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 2018 (4 090) was 10 % lower than the average number reported for 2014-2018 (4 545).
The total estimated and established amount of TOR (EUR 450 million) was 17 % higher than the average estimated and established amount for the years 2014-2018 (EUR 384 million).
Luxemburg and Malta did not report any case of irregularity exceeding an amount of EUR 10 000 for 2018.
CHART TOR3: OWNRES cases not reported as fraudulent and the related estimated and established amount (2014-2018)
Annex 3 of the summary tables shows the situation on the cut-off date for years 2014-2018.
2.2.2. OWNRES data vs TOR collection
In 2018, the total established amount of TOR (gross) was EUR 25.7 billion and about 98 % was duly recovered and made available to the Commission via the A-account. According to the OWNRES data, around EUR 615 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 2.43 % of the total collected TOR (gross) amount in 2018. This proportion has increased compared with 2017 when it was 1.96 %. A percentage of 2.43 % indicates that of every EUR 100 of TOR (gross) established, an amount of EUR 2.43 is registered as irregular (fraudulent or non-fraudulent) in OWNRES. There are differences among the Member States. In six Member States, the percentage is above the average of 2.43 %. The highest percentage for 2018 can be seen in France, Lithuania and Portugal with 4.67 %, 4.49 % and 4.27 % respectively.
For the seven 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 2018 was equal to 2.66 %. In comparison with the previous year (2.02%), this represents an increase of 0,64%. For France, the proportion of estimated and established OWNRES amounts to established TOR increased in 2018 (4,67%) compared to the previous year (1,43%), while for the Netherlands it has increased from 2,62% to 4,18% and for Spain and Italy decreased by 2,53 % and 0,14 % respectively. For the other three Member States, the average proportion of estimated and established OWNRES amounts to established TOR increased in 2018 (2,47 %) compared to the previous year (1,88 %).
TOR MAP1: Showing the percentage of estimated and established amount in OWNRES of established TOR for 2018
2.2.3. Recovery
The fraud and irregularity cases detected in 2018 correspond to an established amount of EUR 584 million. Nearly EUR 225 million of this was recovered in cases where an irregularity was found and EUR 95 million in fraudulent cases. In total EUR 320 million was recovered by all Member States for all cases which were detected in 2018. In absolute figures, Germany recovered the highest amount in 2018 (EUR 85 million) followed by France (84 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 48 % and 65 % (see CHART TOR4). The recovery rate for cases reported in 2018 is currently 55 %. In other words, out of every amount over EUR 10 000 of duties established and reported for 2018 in OWNRES as irregular/fraudulent, approximately EUR 5 500 has already been paid.
CHART TOR4: Annual recovery rates (2014-2018)
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 2018 are in Slovenia (100%), Sweden (97%), Czech Republic (95%), Finland (93 %), Hungary (91 %), France (89%) and Austria (84%). Differences in recovery results may arise from factors such as the type of fraud or irregularity, or the type of debtor involved. Because recovery is ongoing, it can be expected that the recovery rate for 2018 will also go up in the future.
On the cut-off date (15 March 2019), the overall recovery rate for all years 1989-2018 was 63 %.
2.3. Specific analysis
2.3.1. Cases reported as fraudulent
2.3.1.1. Modus operandi
A breakdown by types of fraud reveals that most fraudulent cases in 2018 relate to smuggling of goods, incorrect origin or country of dispatching, valuation or classification/misdescription.
Of all cases reported as fraudulent about 74 % concern such goods as tobacco, vehicles, electrical machinery and equipment, textiles, preparation of foodstuffs, articles of iron and steel and leather. In monetary terms those groups of goods represent about 77 % of all amounts estimated and established for cases reported as fraudulent. China, Brazil, South Korea, Belarus, United States and United Arab Emirates 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 2018, inspections by anti-fraud services (46 %) was the most successful method of detecting fraudulent cases followed by customs controls carried out at the time of releasing of goods (25 %) and post-release controls (19 %).
CHART TOR5: Method of detection 2018 – Cases reported as fraudulent – by number of cases
In monetary terms, of the EUR 165 million estimated or established in fraudulent cases registered for 2018, around 51 % were discovered during a post-release control, 39% during an inspection by anti-fraud services, 6 % during a control at the time of release of the goods.
CHART TOR6: Method of detection 2018 – Cases reported as fraudulent – by estimated and established amount
In seven Member States more than 50 % of all estimated and established amounts in fraudulent cases were detected by anti-fraud services. As regards amounts, controls at the time of release of goods were the most important method for detecting fraudulent instances in Denmark, Estonia, Croatia, Latvia, Poland, Slovenia, Slovakia, Finland, Sweden and the United Kingdom whereas post-release controls were in Bulgaria, France, Hungary, the Netherlands and Portugal.
In Cyprus, 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 2018, there were 169 cases of smuggled cigarettes registered (CN code 24 02 20 90) involving estimated TOR of around EUR 20 million. In 2017 the number of cases of smuggled cigarettes was 173, totalling around EUR 25 million.
The highest number of cases was reported by the UK (30), Spain (26) and Lithuania (19). The highest amount was reported by Greece (EUR 4.7 million). No cases were reported by nine Member States.
Table TOR1: Cases of smuggled cigarettes in 2018
|
TOR: Cases of smuggled cigarettes* in 2018
|
|
MS
|
Cases
|
Established and estimated amount
|
|
|
N
|
EUR
|
|
BE
|
5
|
2.914.764
|
|
BG
|
1
|
73.834
|
|
DE
|
7
|
334.529
|
|
EE
|
4
|
568.102
|
|
IE
|
9
|
1.468.085
|
|
EL
|
15
|
4.690.915
|
|
ES
|
26
|
2.172.336
|
|
FR
|
18
|
1.397.422
|
|
HR
|
2
|
264.959
|
|
IT
|
1
|
991.692
|
|
LV
|
7
|
779.838
|
|
LT
|
19
|
1.853.247
|
|
AT
|
1
|
30.643
|
|
PL
|
16
|
1.430.997
|
|
PT
|
1
|
51.144
|
|
SK
|
3
|
57.532
|
|
FI
|
3
|
66.719
|
|
SE
|
1
|
33.964
|
|
UK
|
30
|
1.148.881
|
|
Total
|
169
|
20.329.603
|
2.3.1.4. Cases reported as fraudulent by amount
In 2018, the estimated and established amount was below EUR 100 000 in 340 cases reported as fraudulent (72 % of all fraud cases), whereas it was above EUR 100 000 in 133 cases (28%).
The total estimated and established amount in cases reported as fraudulent, where the amount at stake was above EUR 100 000, amounted to EUR 153 million (93 % of the total estimated and established amount for cases reported as fraudulent).
Table TOR2: Cases reported as fraudulent by amount category in 2018
|
Amount, EUR
|
N
|
Estimated and established amount, EUR
|
|
< 100 000
|
340
|
11.826.806
|
|
>= 100 000
|
133
|
153.407.855
|
|
Total
|
473
|
165.234.662
|
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 incorrect use of preferential arrangements) and formal shortcomings (shortcomings in external transit 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 2018 most of the estimated and established amounts in OWNRES in the EU-28 (81 %) for cases reported as non-fraudulent related to the customs procedure ‘release for free circulation’. In all, 15% of all amounts estimated or established in cases not reported as fraudulent in 2018 involved inward processing. Other customs procedures are only marginally affected in 2018.
Of all cases reported as non-fraudulent about 50 % concern electrical machinery and equipment, vehicles, mechanical machinery and appliances, plastics, articles of iron and steel and textiles. In monetary terms those groups of goods represent about 64 % of all amounts estimated or established for cases reported as non-fraudulent. China, United States, Japan, Russia, India and Brazil 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 2018, most non-fraudulent cases (50 %) were revealed during post-release customs controls. Other methods of detection for non-fraudulent cases that featured frequently were voluntary admission (21 %), release controls (14 %), tax audits (9 %), followed by inspections by anti-fraud services (4%).
CHART TOR7: Method of detection 2018 – Cases not reported as fraudulent – by number of cases
Considering the estimated or established amounts, around 68 % of all irregularity cases registered for 2018 were discovered during a post-release control, 13 % were related to voluntary admission, 7 % to a control at the time of releasing the goods, whereas 6 % related to a tax audit and 4 % were found during an inspection by anti-fraud services.
CHART TOR8: Method of detection 2018 – Cases not reported as fraudulent – by estimated and established amounts
In 15 Member States, more than 50 % of all non-fraudulent cases — in amounts — were detected by post-release controls. In Portugal, Romania and Slovakia 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 29 million) and Germany (EUR 16 million). In 15 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 2018, solar panels originating in China were especially vulnerable to non-fraudulent reported irregularities in monetary terms. About 29 % (EUR 128 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 and the Netherlands were particularly affected by this type of goods and infringement. Another seven Member States reported also cases related to solar panels to a smaller extent. Mutual Assistance notices issued by OLAF with regard to those goods in the previous years raised the Member States’ attention and the need for customs controls on imports of solar panels. 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 2018, the established amount was below EUR 100 000 in 3 586 non-fraudulent cases (88 % of all irregularity cases), whereas it was above EUR 100 000 in 504 cases (12 %).
The total estimated and established amount in non-fraudulent cases where the amount at stake was above EUR 100 000 amounted to EUR 359 million (80 % of the total estimated and established amount for non-fraudulent cases).
Table TOR3: Cases not reported as fraudulent by amount category in 2018
|
Amount, EUR
|
N
|
Estimated and established amount, EUR
|
|
< 100 000
|
3 584
|
91.078.619
|
|
>= 100 000
|
506
|
358.627.831
|
|
Total
|
4 090
|
449.706.450
|
2.4. Member States’ activities
2.4.1. Classification of cases as fraudulent and non-fraudulent and related rates
For 2018, Member States reported 473 cases as fraudulent out of a total of 4 563 cases reported via OWNRES, which indicates a Fraud Frequency Level (FFL) of 10 %. The differences between Member States are relatively large. In 2018, 13 Member States categorised between 10-50 % of all cases reported as fraudulent. However, Czech Republic did not categorise any cases reported as fraudulent. Eight Member States categorised less than 10 % of cases as fraudulent. Four Member States registered more than 50 % of cases as fraudulent.
In 2018, the total estimated and established amount affected by fraud in the EU was EUR 165 million and the Fraud Detection Rate (FDR) was 0.65 %. For 2018, the highest percentages can be seen in France (3.90 %), Greece (2.31 %) and Croatia (2.24 %).)
The total estimated and established amount affected by cases not reported as fraudulent was more than EUR 450 million which indicates an Irregularity Detection Rate (IDR) of 1.78 %. The highest percentages can be seen in the Netherlands (4.10 %), Portugal (3.55 %) and the UK (3.45 %).
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 1989-2018 period, OWNRES shows that, on average, 22 % of the initially established amount was corrected (cancelled). The recovery rate (RR) for all years (1989-2018) is 41 %. The RR for cases reported as fraudulent and detected in 2018 was 70 % mainly because of one large debt recovered by France and is significantly above the average rate of 39% for fraudulent cases for the 2014-2018 period. 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 36 % (1989-2018) 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 2018 is 50%. On the cut-off date, the annual RR for the last five years has varied between 51% and 81%. The overall RR for all years (1989-2018) for all cases not reported as fraudulent is 72 %.
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)
|
Irregularities
|
HRR 1989-2015
|
|
Reported as fraudulent
|
56,37 %
|
|
Reported as non-fraudulent
|
90,72 %
|
|
Total
|
81,64 %
|
2.4.3. Commission’s monitoring
2.4.3.1. Examination of the write-off reports
In 2018, 12 Member States submitted 73 new write-off reports to the Commission. In 2018, the Commission assessed 188 cases totalling EUR 113 million. In 33 of these cases amounting to EUR 20 million, 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. Coupled with continuing trade facilitations and simplification of procedures and controls, this may undermine the control efficiency and thus pose risks to the protection of the EU financial interest.
In 2018, 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. "Control strategy in the field of customs value" and "Control of imports of solar panels" 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 release of goods to post-release customs controls. The customs controls before or at the time of release of goods remain however indispensable for addressing undervaluation and the detection of new types or patterns of fraud or irregularities.
The digitalisation of the global economy and new economic models like e-commerce is shifting the cross-border trade quickly from a few large/bulk shipments into a large number of low-value and small shipments.
With growing cross-border e-commerce the Member States’ customs control strategies need to be adapted to the changing business models and trade patterns such as e-commerce which poses risks for the EU’s financial interests and the effectiveness of the customs controls. Those risks are in particular related to abuse of the low-value consignment reliefs by undervaluation of e-commerce trade goods, by splitting consignments to be under the relief threshold, by importing of commercial consignments declared as gifts or by importing of goods ineligible for the relief.
A flexible combination of different controls is therefore needed to close any loophole exploited by fraudsters and to enable customs an effective protection of the EU’ financial interests. Therefore, the customs controls strategy should be frequently reviewed taking into account recent detections or new risks and addressing the challenges of the global economy and new business models like e-commerce.
Furthermore, EU-wide and international cooperation in detection of irregular cases is more and more required taking into account the fraud diversion and spreading of specific fraud mechanism.
2.4.3.3. Particular cases of Member State failure to recover TOR
If TOR are not established or recovered because of an administrative error by a Member State, the Commission applies the principle of financial liability. Member States have been held financially liable in 2018 for over EUR 35 million, and new cases are being given appropriate follow-up.
PART II - EXPENDITURE
Sustainable growth: natural resources
The emphasis of the European Union's (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.
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 entirely financed by the European Agricultural Guarantee Fund (EAGF);
oRural development programmes of the Member States (RD), which are mainly co-financed through the European Agricultural Fund for Rural Development (EAFRD).
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 are 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 CAP has been the most important EU 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 (EC) is responsible for the management of the EAGF and the EAFRD. However, the EC 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 EC.
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 CAP sectorial regulations and vary from one sector to another.
The expenditure made by the paying agencies is then reimbursed by the EC 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 EC 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, giving the detail of the share devoted to market measures and direct payments to farmers.
3.2.General analysis
3.2.1.Irregularities reported 2014-2018
In general, Member States are requested to communicate irregularities with financial amounts involved above EUR 10 000. However, a number of cases with irregular financial amounts equal or below this threshold have been reported by several Member States. Table NR3 provides an overview by Member State. Furthermore, Member States reported cases with financial amounts involved equal to zero. This may be due to the fact that the competent national authority did not have enough information yet to quantify the irregular amounts involved. However, this should not be the case once the case is closed or expired. Table NR3 provides also an overview by Member State of the closed/expired cases, for which the national autorithies have not mentioned the irregular financial amounts involved.
It is not clear why there are some Member States that reported many more 'below-the-threshold' irregularities than others. It should be considered that an irregularity may consist of irregular or fraudulent operations which are interlinked and whose total financial impact exceeds EUR 10 000, even though each operation remains below the threshold. In this case, a number of Member States may have chosen to report these irregularities separately, while other Member States may have combined them in one irregularity. Another explanation may relate to irregularities that were reported because the initial estimation of the irregular financial amounts involved exceeded EUR 10 000, but subsequent updates lowered these financial amounts below the threshold. Furthermore, about 30% of the 'below-the-threshold' irregularities were still open at the cut-off date; the competent national authority might have decided to report them anyway, pending the exact quantification of the financial amount involved. Other explanations may refer to mis-typing or mis-interpretation of the reporting rules.
As shown by Table NR3, there were about 650 irregularities that taken separately were associated to a financial amount equal or below EUR 10 000, which represented less than 4% of all the relevant irregularities. In order to make use of all available information reported by the Member States, all these irregularities are considered in the analysis for this Report. However, Table NR3 provides the reader with additional information to put into context data about detections in different Member States.
Table NR4 shows the number of irregularities (fraudulent and non-fraudulent) reported by the Member States for the period 2014-18 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);
·'Unclear', where information is not considered enough to classify the irregularity in any of the other categories.
Annex 11 provides a detailed explanation about the classification of cases.
When inputting a case into the Irregularities Management System (IMS), 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 2019.
In 2018, the number of the irregularities related to CAP decreased by 5% (in comparison with 2017) and this brought them to the lowest level recorded during the last five years. The irregularities notified by a minority of Member States (Italy, Romania, Portugal, Spain, Bulgaria, France and Lithuania) represented more than 70% of the total number of the irregularities reported in 2018.
The two types of support (RD and SA) 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. As a consequence, the irregularities related to RD noticeably increased until 2015, then declined at a rather constant and sustained pace during 2016-2017, before stabilising in 2108 (see the chart associated to Table NR4). Overall, the decrease from the 2015 peak has been about -36%. Following a different pattern, the irregularities affecting SA have been relatively stable over time, fluctuating between 1 000 and 1 200 reported cases.
Table NR5 provides information about the financial amounts involved in the cases considered in Table NR4.
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 2014-2018, cases which involved financial amounts over 1 million represented less than 1% in terms of numbers, but 32% in terms of amounts. 62% of these 'over 1 million' cases concerned RD, while 36% concerned SA. 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 over-interpreted. However, the continuous growth of the financial value of irregularities related to RD until 2015 and the specular decrease thereafter were in line with the general trend of irregularities shown in Table NR4.
In 2018, the financial amounts involved in irregularities related to rural development accounted for about 55% of the total. However, one has to bear in mind that, in 2018, RD represented about 20% of the total resources devoted to the CAP. In fact, as in past years, the weight of the financial amounts involved in irregularities on payments is very different between the two types of support, as it is 0.2% for SA and 1.4% for RD (0.5% on the overall 2018 CAP expenditure). This is consistent with the findings of the European Court of Auditors (ECA) referring to 2017, according to which payments made on an entitlement basis (including direct aid to farmers, which is the biggest part of SA) are not affected by a material level of error. According to ECA, direct payments to farmers have benefited from simplified land eligibility rules and an effective ex-ante control system (IACS) that allows automated cross-checks between databases. Payments made on a reimbursement basis (which include rural development) are affected by a higher level of error. See also Section 3.3.2.
In 2018, the financial amounts have decreased by 14% in comparison with 2017, which is more than the decrease in terms of numbers. During the overall period under consideration, SA financial amounts have been following a rather horizotal trend with ups and downs due to a few cases with exceptional amounts involved. Concerning RD financial amounts, in 2018, although the number of irregularities was stable, they continued on the declining path that had started after the 2015 peak, but at a slower pace. This translated in a slight decrease of the average financial amount (AFA) of RD irregularites, which has been broadly stable during 2015-2018. Considering the overall period 2014-2018, the AFA involved in SA cases was higher than in RD cases (+49%).
The AFA of the reported irregularities can be seen as an indicator of the detection capacity. Targeting the limited resources that are available for detection, investigation and (where relevant) prosecution on cases with a higher financial impact can be beneficial in terms of efficiency, recovery and deterrence.
As mentioned, trends are overly influenced by irregularities with exceptional financial amounts, and during 2014-2018 this was particularly the case for SA. This had an obvious impact also on the trends related to AFAs. Graph NR1 shows these trends. The higher volatility related to SA is clear. In order to get a better grasp of the underlying dynamics, Graph NR1 shows also the SA and RD trends, net of irregularities with exceptional financial amounts involved. After this 'filtering', the AFAs of RD and SA irregularities were broadly aligned during the period under consideration, with the exception of 2018. In this year, the AFA of SA irregularities significantly exceeded that of RD irregularities (+30%).
Most of the SA cases with exceptional financial amounts referred, at least in part, to market measures (MM). In general, taking the whole period 2014-2018 together, when SA is considered net of all SA cases concerning market measures, its AFA is lower than that of RD cases. Consistently, the AFAs of SA, net of MM, basically overlap with AFAs of direct payments to farmers (DA), with the exception of 2015.
Given the above, in an attempt to isolate the 'core' trends, Graph NR2 show the SA, RD, MM and DA AFAs during the last five years, when the first and the last percentiles are excluded from the analysis.
Graph NR2 shows that irregularities including a market measure component recorded the highest AFA, which is increasing. The AFA of SA irregularities followed a rather stable trend, with a slight tendency to increase over time. The AFA of RD cases fluctuated around those of the SA cases, with a slight tendency to decrease. The difference was significant in 2018 (-20% for RD AFA), but considering past behaviour, it is not expected to be persistent. The lowest AFA was that related to irregularities with a DA component. However this average has been following an upward trend during 2014-2018.
3.2.2.Irregularities reported as fraudulent
For the period 2014-18, Table NR6 provides an overview of the number of irregularities reported as fraudulent by the Member States in relation to the type of support concerned. After the significant decrease in 2017, the number of fraudulent irregularities was more stable (-7% in 2018 with respect to 2017). This was the result of moderate decreases in the number of both RD and SA irregularities.
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 and 2018 they were broadly aligned. As a result, over the period 2014-2018, the number of RD irregularities reported as fraudulent was still higher than the number of SA ones, but the share of the total was just 59%. During 2014-2018, 47 cases concerned both RD and SA. In most of these cases, violations concerning RD were combined with violations concerning direct payments to farmers.
In 2018, the irregularities notified by the first two Member States (Romania and Italy) represented about 61% of the total number of irregularities reported as fraudulent. This concentration was much higher than in 2017 (about 54%) and in 2014 (about 52%). The first ten countries taken together reported 237 cases as fraudulent, which represented about 95% of the total (in 2017 the first ten countries accounted for about 89% and in 2014 about 93% of the total irregularities reported as fraudulent). Significant changes in the number of irregularities reported as fraudulent were recorded in Poland (decrease) and Romania (increase). Concentration of detections is analysed further in Section 3.4.3.1.
Table NR7 provides information about the financial amounts involved in the cases considered in Table NR6. Taking into account the whole 2014-18 period, financial amounts involved in SA cases were predominant (55% of the total amount). However, the share of the RD on the total (43%) was well above the share of the resources allocated to RD on the total of the CAP resources over the same period.
In 2018, the overall financial amounts rose by 11%. After the peak recorded in 2016, the financial amounts related to RD dropped in 2017 (-60%, similar to the number of cases) and remained broadly stable in 2018. The trend of the financial amounts related to SA was heavily influenced by the fact that in each of the years 2014 (Poland), 2015 (France), 2017 (Poland) and 2018 (Poland) one case worth between EUR 20 and 30 million was detected. These 'exceptional' irregularities were all referring to market measures. Net of these cases the irregular financial amounts detected in relation to SA were more stable during 2014-2017, but still doubled in 2018.
Considering the overall period 2014-2018, the AFA involved in SA cases was double that for RD cases (+98%). As mentioned, this is mainly due to irregularities concerning market measures, where potential frauds with exceptional financial amounts happened to be reported. In fact, in 2016 such exceptional cases did not emerge and the AFA of SA fell below that of RD cases. 2018 is a special year: even net of the exceptional irregularity reported by Poland, the AFA of SA was higher than that of RD cases. Net of these exceptional cases, there was no clear pattern: the AFA of potential frauds in SA was still higher than that of RD cases in 2014 and 2018, but not in the period 2015-2017. When SA is considered net of all cases concerning market measures, the AFA is far lower than for RD cases.
Starting from the irregularities that have been selected in relation to Graph NR2, Graph NR3 shows the 'core' trend of the average financial amounts of the SA, RD, MM and DA irregularities reported as fraudulent during the last five years.
The AFAs for SA irregularities and for irregularities with a DA component were broadly stable and lower than for the other categories. The AFA for RD irregularities has been following a rising trend until 2017, but fell in 2018 to the level of SA and DA cases. The AFA of irregularities with a MM component, which are much higher than for the other categories, has been growing during the last 2 years.
3.2.3.Irregularities not reported as fraudulent
Regarding irregularities not reported as fraudulent, the number of those communicated in relation to RD has been constantly increasing until 2015, while that related to SA remained stable or recorded minor variations (see Table NR8). Also the irregular financial amounts linked to RD peaked in 2015 (as highlighted in Table NR9). The irregular financial amounts linked to SA fluctuated around an annual average of about EUR 70 million, with significant annual variations.
In terms of number of irregularities (Table NR8), RD has regularly and significantly exceeded SA across the whole 2014-2018 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 NR9), after the peak in 2015, irregularities related to RD gradually decreased, while irregularities related to SA experienced significant changes of opposite signs. This was mainly due to the fact that in each of the years 2014 (France), 2015 (France, Greece) and 2017 (Romania) the Member States detected one or two cases with 'exceptional' financial amounts involved, something which did not happen in 2016 and 2018.
During 2014-2018, the AFA of RD cases was broadly flat, floating around EUR 60 000, which was the result of similar trends for numbers and financial amounts (see Tables NR8 and NR9). Considering the overall period 2014-2018, the AFA involved in SA cases was higher than in RD cases (+28%). This is mainly due to cases with 'exceptional' financial amounts, mostly concerning market measures.
Graph NR4 shows the 'core' trend of the AFA of the SA, RD, MM and DA irregularities not reported as fraudulent during the last five years. The highest AFAs were related to irregularities with a MM component. The AFAs related to the other categories were more aligned, with SA cases and cases with a DA component following an increasing 'core' trend (at least before 2017) and the opposite for RD cases.
It is interesting comparing AFAs of fraudulent and non-fraudulent irregularities. Apart from 2014, this difference was not significant for SA and DA irregularities. For RD irregularities instead, fraudulent cases had a significantly and increasingly higher AFA than non-fradulent irregularities. This stopped abruptly in 2018. The AFAs of fraudulent irregularities with a MM component were constantly and significantly higher than those of the corresponding non-fraudulent irregularities. The difference decreased until 2016, but then started increasing in 2017 and accelerate in 2018.
3.3.Specific analysis
3.3.1.Modus operandi
3.3.1.1.Support to agriculture (SA)
Table NR10 provides an overview of the most frequent categories (or combinations of categories) of irregularities linked to cases reported as fraudulent in relation to SA in 2018 and the financial amounts involved. It also presents how these most recurrent categories (or combinations of categories) featured in the period 2014-2018.
The most recurrent modi operandi were related to 'documentary proof' or to the 'request' (not combined with other categories of irregularity). Each category is subdivided 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 2018 and in the overall period 2014-2018.
Irregularities concerning 'Product, species and/or land' (not combined with other categories of irregularity) were also quite recurrent. More specifically, in the overall period 2014-2018, most of these infringements concerned the type 'overdeclaration and/or declaration of ficticious product, species and/or land', while in 2018 they concerned 'unauthorised use'.
During 2014-2018, 57 irregularities were reported as pertaining to the category 'Ethics and integrity' (not combined with other categories of irregularity). 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. In 2018, the category 'Ethics and integrity' appeared relatively often also in combination with other categories of irregularity. These cases were reported by Bulgaria and most of them were related to conflict of interest.
Table NR11 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 2018 and the financial amounts involved. It also presents how these most recurrent categories (or combinations of categories) featured in the period 2014-2018.
When looking at these irregularities, violations concerning the 'request' were by far the most recurrent category. More specifically, the most recurrent type of violation, both in 2018 and 2014-2018, was by far 'false or falsified request for aid', followed by 'incorrect or incomplete request for aid' and 'Product, species, project and/or activity not eligible for aid'. Violations concerning the other category 'documentary proof' were also quite frequent and, considering the overall period 2014-2018, often related to the type of violation 'false or falsified documents' (about 190 cases in 2014-2018). However this reporting of cases of 'false or falsified documents' as non-fraudulent mostly happened in the past; in 2018 there were only 4 such cases. For most of the SA irregularities not reported as fraudulent where the type of violation was 'false or falsified documents' or 'false or falsified request for aid' there were no ongoing penal proceedings.
Three other prevalent categories of SA irregularities not reported as fraudulent were related to:
·'(Non)action'. In this area, the three most reported types pertained to the action itself (not implemented or not completed), and 'refusal to repay not spent or unduly paid amounts';
·'Product, species and/or land'. For this category, the majority of violations concerned 'Overdeclaration and/or declaration of fictitious product, species and/or land';
·'Beneficiary'. Here the most reported type of violation was 'Operator/beneficiary not having the required quality'.
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 concerning ethics and integrity'.
3.3.1.2.Rural development (RD)
Table NR12 provides an overview of the most frequent categories of irregularities reported as fraudulent in RD in 2018 and the related financial amounts. It also presents how these most recurrent categories have featured during the period 2014-2018.
In 2018 and in 2014-2018, 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') was the most reported.
Within the CAP, 'RD cases reported as fraudulent' is the domain where the category Ethics and integrity ranked higher, with 141 irregularities in 2014-2018. 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, such as the one referring to the beneficiary. For this category (considered also in combination with other categories), the most reported type of violation was 'Operator/beneficiary not having the required quality', which may have been used, especially for fraudulent irregularities, in relation to cases of creation of artificial conditions.
Table NR13 provides an overview of the most frequent categories of irregularities not reported as fraudulent in RD in 2018 and the related financial amounts. It also presents how these most recurrent categories have featured during the period 2014-2018.
When looking at these irregularities, the most frequently detected category was 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 high also in relation to irregularities reported as fraudulent (see Table NR12).
'(Non-)action' was followed by 'documentary proof' representing about 10% of the non-fraudulent cases in 2018 (including 'Documents missing and/or not provided' as the most reported type of violation). During 2014-2018, a number of 'documentary proof' cases (48) concerned the 'false and/or falsified documents' type of violation. The same applies to the category 'request', where a number of cases (16) were related to the 'false or falsified request of aid' type of violation.
In relative terms, the category Beneficiary is more frequent among RD cases not reported as fraudulent than in other CAP areas (about 9% of cases in 2018 and 8.5% in the overall 2014-2018). Within this category, 'Operator/beneficiary not having the required quality' is the most reported type of violation.
Apart from one case of conflict of interest, infringements related to 'Ethics and integrity' were reported as 'other irregularities concerning ethics and integrity'. Most of these irregularities were reported by Spain.
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, for the purpose of this analysis, in these two categories of the cases reported by the Member States.
Table NR14 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 were heavily influenced by few exceptional cases. Net of these cases, the FDR for market measures would be 0.37% rather than 1.07%. Similarly, excluding the few (3) 'exceptional' non fraudulent irregularities, the IDR would be 1.04% rather than 1.37%.
3.3.3.Market measures – fraudulent and non-fraudulent irregularities
As showed in Table NR14, market measures feature high FDR and IDR. Table NR15 shows the frequency and financial amounts of irregularities reported as fraudulent in relation to market measures for the period 2014-2018, while Table NR16 shows the same data with reference to irregularities not reported as fraudulent.
The category 'products of the wine-growing sector' was the most recurrent, but 'fruit and vegetables' was the one with the highest financial amounts, in particular due to the high AFA of cases reported as fraudulent. Other categories with high AFA were 'Pigmeat, eggs and poultry, bee-keeping and other animal products', 'Food programmes' (for cases not reported as fraudulent), 'Sugar' (for cases not reported as fraudulent) and 'Promotion' (for cases reported as fraudulent).
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.
In last year's Report, an analysis of the ‘reasons for performing control’ was introduced and led to the recommendation to further exploit the potential of risk analysis, tailoring the approach to the different types of expenditure and taking advantage of best practices and the risk elements highlighted in that Report. Furthermore, it was recommended to facilitate and assess the spontaneous reporting of potential irregularities and strengthen the protection of whistle-blowers that are also a crucial source for investigative journalism.
Tables NR17-NR22 suggest that so far there has been little improvement on the ground. However, as last year's Report was adopted at the beginning of September 2018, it may be too early to draw any conclusion. Effective evolution from reactive to proactive detections based on risk analysis may take time.
With a focus on controls that led to discover irregularities reported as fraudulent in RD, Table NR17 provides information on the number of controls that were performed because of reasons that can be linked to the above mentioned recommendations. It compares the situation until 2017 with the situation in 2018. In the last year, Member States did not detect any irregularity on the basis of risk analysis or information published by the media. The share of irregularities detected following tips slightly increased from 6% to 7%.
With a focus on controls that led to discover irregularities not reported as fraudulent in RD, Table NR18 compares the situation until 2017 with the situation in 2018. There were no significant changes in the use risk analysis or information published by the media. With specific reference to risk analysis, no Member State that had not reported this type of detections in 2014-2017 started to report them in 2018. During this year detections specifically based on risk analysis were confined to six Member States. The share of irregularities detected following tips slightly increased.
3.3.4.2 Irregularities in relation to market measures
With a focus on controls that led to discover irregularities reported as fraudulent in MM, Table NR19 compares the situation until 2017 with the situation in 2018. The categories 'Scrutiny 4045' and Scrutiny 485' refer to Regulation 4045/1989 and Regulation 485/2008, which 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). While Reg. 485/2008 explicitly introduced the concept of risk analysis, Reg. 4045 already required consideration for risk factors and concentration on sectors or undertakings where the risk of fraud is high. In 2018, apart from a declining share concerning 'Scrutiny 485' the Member States did not detect any irregularity on the basis of risk analysis, information published by the media or tips.
With a focus on controls that led to discover irregularities not reported as fraudulent in MM, Table NR20 compares the situation until 2017 with the situation in 2018. In the last year, there was no clear increase in the use of risk analysis with respect to the period 2014-2017. On the one hand, the use of 'comparison of data' rose by more than 1 pp, but this was based on few cases and it is not clear what kind of activity was reported under this reason. On the other hand, the share of irregularities detected on the basis of scrutiny ex-Reg. 485 decreased by more than 2pp. The share of irregularities detected following tips slightly increased, but on the basis on very few cases.
3.3.4.3 Irregularities in relation to direct payments
With a focus on controls that led to discover irregularities reported as fraudulent in DA, Table NR21 compares the situation until 2017 with the situation in 2018. For an explanation about the categories 'Scrutiny 4045' and Scrutiny 485', see above Section 3.3.4.2. In 2018, apart from a declining share concerning tips, the Member States did not detect any irregularity on the basis of risk analysis, scrutiny or information published by the media.
With a focus on controls that led to discover irregularities reported as not fraudulent in DA, Table NR22 compares the situation until 2017 with the situation in 2018. In the last year, there was no increase in the use of risk analysis or information published in the media with respect to the period 2014-2017. The share of irregularities detected following tips slightly increased, from 1.5% to 2.5%.
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 2018 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;
(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 17 974 irregularities (fraudulent and non-fraudulent) reported by Member States in 2014-2018 in relation to CAP, 10 359 (58% of the total) involved infringements that have been protracted during a span of time. For the 1 786 irregularities reported as fraudulent, this percentage is higher at about 65%. The remaining part of the dataset refers to irregularities which consisted of a single act identifiable on a precise date (about 36% of the whole dataset and 33% of that including exclusively the fraudulent irregularities) or for which no reliable information has been provided (6% 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 just 2 months more: 28 months.
3.4.2.Detection of irregularities reported as fraudulent by Member State
3.4.2.1.Reported during the period 2014-2018
Table NR23 offers an overview of the irregularities reported as fraudulent by Member States during the period 2014-2018. It also shows the related amounts, overall payments for the agricultural policy and the FDR.
Finland has notified no irregularities as fraudulent; another seventeen (17) Member States reported less than 30 potentially fraudulent irregularities; four (4) Member States reported between 30 and 60; six (6) Member States more than 60.
Romania, Poland, Hungary and Italy are the four countries which have reported the highest numbers, while Poland, Romania, France and Bulgaria reported the highest amounts. Bulgaria, Estonia, Poland and Romania's FDRs approached 0.5%, about double the Lithuania and Hungary's FDRs, which ranked fifth and sixth..
3.4.2.2.Reported in 2018
Table NR24 offers an overview of the irregularities reported as fraudulent by Member States in 2018. It also shows the related amounts, overall payments for the agricultural policy and the FDR.
Twelve Member States notified no irregularities as fraudulent; most Member States reported less than 30 potentially fraudulent irregularities; only 2 Member States reported more than 30 irregularities.
Romania, and Italy were the Member States which have reported the highest numbers, while Poland and Romania reported the highest amounts. Bulgaria's FDR is 1.5%, more than double the second and third highest FDRs, which have been recorded by Romania and Poland, respectively.
3.4.3.Fraud and Irregularity Detection by sector and Member State
3.4.3.1.Rural development
Table NR25 and Map NR1 provide an overview of the irregularities reported as fraudulent by Member States during the period 2014-2018 in relation to rural development. It also shows the related amounts, overall payments for rural development and the FDR.
These irregularities are exclusively referred to rural development. A number of additional cases concerned both rural develoment and support to agriculture, including market measures or direct payments (see Table NR6, NR7 and Annex 11), but considering them is not likely to significantly change the picture. This applies also to Table 26.
24 Member States have reported potentially fraudulent cases in relation to RD during the period 2014-2018. Romania, Poland and Hungary reported the highest mumbers. The highest financial amounts were communicated by Romania, Poland, Hungary and Bulgaria. Estonia shows the highest FDR, above 1%, while the FDRs of Romania, Lithuania, Hungary and Bulgaria are between 0.5% and 1%.
Table NR26 and Map NR2 provide an overview of the irregularities not reported as fraudulent by Member States during the period 2014-2018 in relation to rural development. Table NR26 also shows the related amounts, overall payments for rural development and the IDR.
Romania, Portugal, Spain, Poland, Italy and Hungary reported the highest numbers. The highest financial amounts were communicated by Romania. Lithuania shows the highest IDR, above 4%, while the IDRs of Portugal, Romania Bulgaria, the Netherlands, Malta and Estonia exceeds 2%.
Tables NR25 and NR26 suggest that the reporting of irregularities was concentrated in a few Member States and that this concentration could go beyond what could be expected on the basis of the distribution of payments related to rural development among Member States.
Graphs NR5 help assessing this hypothesis. Respectively for fradulent and non-fraudulent irregularities, Graphs NR5a and NR5b show the cumulative percentage distribution of the number of cases and related financial amounts involved in relation to rural development. The Member States are sorted on the basis of the number of irregularities reported.
Graph NR5a shows that the first three Member States (Romania, Poland and Hungary) reported nearly 70% of all fraudulent irregularities related to rural development, while they received 25% of the payments. This percentage is noticeably lower in relation to non-fraudulent irregularities (less than 50%), but it is still well above the share of payments received. While Romania was still the Member State with the highest number of cases reported, Portugal and Spain ranked second and third.
In general, the cumulative distributions of number of cases and financial amounts broadly overlap. They rise fast and are quite far from the cumulative distribution of payments related to rural development; this is clearly emphasised when focusing on fraudulent irregularities. To better assess the contribution of each Member State to these patterns, Graph NR5c and NR5d present the individual shares of number of cases, financial amounts involved and payments, respectively for fraudulent and non-fraudulent irregularities.
This corroborates the hypothesis that the concentration of detections is not explained by the concentration of payments during the period 2014-2018. This may be due to many different factors, including different underlying levels of irregularities and fraud, a different quality of the prevention or detection activities or different practices concerning the stage of the procedure when potentially fraudulent irregularities are reported.
This difference in concentration between detections and payments is less evident for non-fraudulent irregularities, which might be taken as an indication of more homogenous approaches to management and administrative controls, even if the examination of data concerning single Member States (see Graph NR5d) highlights significant discrepancies. The concentration of detections is instead more accentuated for fraudulent irregularities, suggesting that different approaches to the use of criminal law to protect the EU budget may be an additional and significant factor causing further inhomogeneity among Member States.
3.4.3.2.Market measures
Table NR27 and Map NR3 provide an overview of the irregularities reported as fraudulent by Member States during the period 2014-2018 in relation to market measures. The table also shows the related amounts, overall payments for market measures and the FDR.
A part of these irregularities are not exclusively referred to market measures, but the reporting authority may have also included budget lines/posts referring to other measures, including direct payments, rural development or other payments related to budget years before 2006 (see Annexes 11 and 13 for the detailed explanation about the classification of cases in relation to CAP expenditure). These irregularities have been included in their full value in Table NR27. This applies also to Table 28 below.
17 Member States have reported potentially fraudulent cases in this area (2 more than in the period 2013-2017). France, Poland and Hungary reported the highest numbers. The highest financial amounts were communicated by Poland, France and Bulgaria. Poland and Bulgaria show the highest FDRs (around 10%).
Table NR28 and Map NR4 provide an overview of the irregularities not reported as fraudulent by Member States during the period 2014-2018 in relation to market measures. It also shows the related amounts, overall payments for market measures and the IDR.
23 Member States have reported non fraudulent cases with reference to market measures (one more than during 2013-2017). 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 IDRs.
Tables NR27 and NR28 suggest that the reporting of irregularities was concentrated in a few Member States and that this concentration could go beyond what could be expected on the basis of the distribution of payments related to market measures among Member States. Graphs NR6 help assessing this hypothesis. For a general explanation about these graphs, see Section 3.4.3.1.
Graph NR6a shows that three Member States (France, Poland and Hungary) reported about 70% of all fraudulent irregularities related to market measures, while they received about 30% of payments. This percentage is lower in relation to non-fraudulent irregularities (about 65%) and it is in line with the share of payments received by these Member States. France was accompanied by Spain and Italy in the group of Member States with the highest number of cases not reported as fraudulent.
The cumulative distributions of number of fraudulent cases and related financial amounts related to market measures rise fast and much faster than the cumulative distribution of payments related to market measures. This is less clear for non-fradulent irregularities, where the patterns of detections and payments are more aligned. To better assess the contribution of each Member State to these patterns, Graphs NR6c and NR6d present the individual shares of number of cases, financial amounts involved and payments, respectively for fraudulent and non-fraudulent irregularities.
This corroborates the hypothesis that the concentration of detections is not explained by the distribution of payments, especially not for fraudulent irregularities. This suggests the need for more homogeneity concerning the use of criminal law to protect the EU.
3.4.3.3.Direct payments to farmers
Table NR29 and Map NR5 provide an overview of the irregularities reported as fraudulent by Member States during the period 2014-2018 in relation to direct payments to farmers. It also shows the related amounts, overall payments for direct payments and the FDR.
A part of these irregularities are not exclusively referred to direct payments, but the reporting authority may have also included budget lines/posts referring to other measures, including market measures, rural development or other payments related to budget years before 2006 (see Annexes 11 and 13). These irregularities have been included in their full value in Table NR29. This applies also to Table 30 below.
15 Member States have reported potentially fraudulent cases in this area. Romania, Italy and Poland reported the highest numbers. The highest financial amounts were communicated by Italy. Italy and Romania show the highest FDRs, which are lower than 0.1%. For the other Member States, FDRs are almost zero.
Table NR30 and Map NR6 provide an overview of the irregularities not reported as fraudulent by Member States during the period 2014-2018 in relation to direct payments. It also shows the related amounts, overall payments for direct payments and the IDR.
23 Member States have reported non fraudulent cases concerning direct payments. Italy and Romania reported both the highest numbers and the highest financial amounts. Romania and Italy show the highest IDRs (about 0.4%).
Tables NR29 and NR30 suggest that the reporting of irregularities was concentrated in a few Member States and that this concentration could go beyond what could be expected on the basis of the distribution of payments related to direct payments among Member States. Graphs NR7 help assessing this hypothesis. For a general explanation about these Graphs, see Section 3.4.3.1.
Graph NR7a shows that three Member States (Romania, Italy and Poland) reported more than 85% of all fraudulent irregularities related to direct payments, while they received about 20% of payments. This percentage is lower in relation to non-fraudulent irregularities (about 70%), but still clearly exceeded the share of payments received by these Member States. Italy and Romania were accompanied by Spain in the group of the Member States with the highest number of cases not reported as fraudulent.
In general, the cumulative distributions of number of cases and financial amounts broadly overlap. They rise fast and are quite far from the cumulative distribution of payments related to direct payments; this is clearly emphasised when focusing on the fraudulent irregularities. To better assess the contribution of each Member State to these patterns, Graph NR7c and NR7d present the individual shares of number of cases, financial amounts involved and payments, respectively for fraudulent and non-fraudulent irregularities.
This corroborates the hypothesis that the concentration of detections is not explained by the distribution of payments. This may be due to different factors, including inhomogeneous management and control systems and, for the fraudulent irregularities, different approaches to the use of criminal law to protect the EU.
3.4.3.4.Concentration by sector and type of irregularity
In Sections 3.4.3.1-3.4.3.3, focusing on different sectors of agriculture expenditure, the concentration of detections in different Member States have been analysed, comparing it with the distribution of related payments.
Graphs NR8 and NR9 are based on an overall measure of the distance between the distribution of detections in different Member States and the distribution of payments received by the Member States in the same period.
These graphs confirm and summarise findings from the previous sections. They show that 'direct payments' was the sector with the largest distance between detections and payments received. Rural development and market measures are more similar. The distance is always lower for non-fraudulent irregularities, especially for rural development and market measures. This might be taken as an indication that management and administrative controls are more homogeneous among Member State than the approaches to the use of the criminal law for the protection of the EU budget and/or reporting of suspected fraud.
3.4.4.Ratio of established fraud / Dismissal ratio
Since the PIF Report 2014, 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 NR31, therefore, updates the table already published in the last four Reports indicating that the 'ratio of established fraud' has slightly increased in comparison to last year (from 12% to 14%). The 'dismissal ratio' increased from 17% to 22%. This means that the number of cases that had been reported during 2009-2013 that were still classified as fraudulent at the end of 2018 has decreased by 22% from the end of 2013. This decrease may be due to cases that have been cancelled or that have been re-classified as non-fraudulent, which justify taking this measure as a dismissal ratio. However, it must be considered that between 2014 and 2018, a number of cases that had initially been classifed as non-fraudulent may have been re-classified as fraudulent, contributing to compensate at least part of the decrease. If these cases were not considered in the calculation, the dismissal ratio would be higher.
Focusing on the cases that had been reported during 2009-2013 and that were still classified as fraudulent at the end of 2018 (including irregularities initially classified as non-fraudulent and then re-classified as fraudulent), 14% of them are considered as established fraud (ratio of established fraud).
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 2018 Annual Management and Performance Report for the EU Budget.
EUROPEAN COMMISSION
Brussels, 11.10.2019
SWD(2019) 365 final
COMMISSION STAFF WORKING DOCUMENT
Statistical evaluation of irregularities reported for 2018: 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
30th Annual Report on the Protection of the European Union's financial interests - Fight against fraud - 2018
{COM(2019) 444 final} - {SWD(2019) 361 final} - {SWD(2019) 362 final} - {SWD(2019) 363 final} - {SWD(2019) 364 final}
Contents
4.
The European Structural and Investment Funds (ESIF)
4.1.
General analysis
4.1.1.
Irregularities reported as fraudulent
4.1.1.1.
Trend by programming period
4.1.1.2.
Trend by Fund
4.1.2.
Irregularities not reported as fraudulent
4.1.3. Irregularities reported in relation to the PP 2014-2020: comparison with PP 2007-2013
4.2.
Specific Analysis – Irregularities reported in relation to the Programming Period 2007-13
4.2.1.
Objectives concerned by the reported irregularities
4.2.1.1.
Irregularities reported as fraudulent by Objective
4.2.1.2.
Fraud and Irregularity Detection Rates by Objective
4.2.2.
Priorities concerned by the reported irregularities
4.2.2.1.
Irregularities reported as fraudulent (fisheries not included)
4.2.2.2.
Irregularities not reported as fraudulent (fisheries not included)
4.2.2.3.
PP 2007-2013: irregularities related to the priorities 'Tourism' and 'Environment' by theme
4.2.2.4.
Types of irregularities / modus operandi detected related to the priorities 'Tourism' and 'Environment protection and Risk prevention'
4.2.2.5.
Geographical distribution of irregularities (fraudulent and non-fraudulent) detected in relation to the 'Tourism' and 'Environment protection and Risk prevention'
4.3 Reasons for performing control
4.4.
Antifraud and control activities by Member States
4.4.1.
Duration of irregularities
4.4.2.
Detection of irregularities reported as fraudulent by Member State
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
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) – 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 Section, 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 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 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.
This Section of the report focuses on the programming period (PP) 2007-2013 and starts analysing the PP 2014-2020, mainly through a comparison with the irregularities reported during the first 5 years of implementation of the PP 2007-2013.
4.1.General analysis
In general, Member States are requested to communicate irregularities with financial amounts involved above EUR 10 000. However, a number of cases with irregular financial amounts equal or below this threshold have been reported by several Member States. Table CP1 provides an overview by Member State. Furthermore, Member States reported cases with financial amounts involved equal to zero. This may be due to the fact that the competent national authority did not have enough information yet to quantify the irregular amounts involved. However, this should not be the case once the case is closed or expired. Table CP1 provides also an overview by Member State of the closed/expired cases, for which the national autorithies have not mentioned the irregular financial amounts involved.
It is not clear why there are some Member States that reported much more 'below-the-threshold' irregularities than others. It should be considered that an irregularity may consist of irregular or fraudulent operations which are interlinked and whose total financial impact exceeds EUR 10 000, even though each operation remains below the threshold. In this case, a Member State may have chosen to report these irregularities separately, while other Member States may have combined them in one irregularity. Another explanation may relate to irregularities that were reported because the initial estimation of the irregular financial amounts involved exceeded EUR 10 000, but subsequent updates lowered these financial amounts below the threshold. Furthermore, more than 60% of the 'below-the-threshold' irregularities were still open at the cut-off date; the competent national authority might have decided to report them anyway, pending the exact quantification of the financial amount involved. Other explanations may refer to mis-typing or mis-interpretation of the reporting rules.
As shown by Table CP1, there were about 2 200 irregularities (less than 7% of all the relevant irregularities) that taken separately were associated to a financial amount equal or below EUR 10 000. In order to make use of all available information reported by the Member States, all these irregularities are considered in the analysis for this Report. However, Table CP1 provides the reader with additional information to put into context data about detections in different Member States.
In comparison with the other budget sectors, the analysis of the cohesion policy poses a higher level of complexity, as information refers to different PPs, which are regulated by different rules.
Table CP2 offers an overview of the number of irregularities (both fraudulent and non-fraudulent) reported from 2014 to 2018, by PP and fund.
With reference to PP 2007-2013, Table CP2 does not suggest any major deviation from known trends and patterns in detection and reporting of irregularities, with the exception of year 2015, when the number of reported irregularities doubled, before decreasing in the following years. The increase in 2015 was for the greatest part linked to the reporting of irregularities by one Member State (Spain), which covered about half of the total number of irregularities reported in 2015. 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.
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 CP3 offers an overview by PP and fund of the financial amounts involved in irregularities detected and reported to the EC over the last five years. While the number of reported irregularities peaked in 2015 and significantly decreased in the following years, the involved financial amounts were stable in 2016, before declining at a much slower pace. This trend implied an accelerating raise of the average financial amounts (AFA) (+23% in 2016, +30% in 2017 and +141% in 2018).
Graphs CP1 provide the details about the trend of AFAs for CF, ERDF and ESF in PP 2007-2013 and PP 2014-2020.
With reference to the Cohesion Fund, the financial amounts involved in irregularities related to PP 2007-2013 significantly increased in 2016 (+37%) while the financial amounts in 2018 were pushed by irregularities related to PP 2014-2020. The strong increase in 2016 was mainly due to one irregularity reported by Slovakia, where financial amounts exceeded EUR 150 million. Similarly, 36% of the financial amounts reported in 2018 with reference to PP 2014-2020 was involved in one irregularity detected in Slovakia.
With regard to the ERDF, there was a steep upward trend in the AFAs of the irregularities both in PP 2007-2013 (+25% in 2016, +46% in 2017 and +113% in 2018) and 2014-2020 (+309% in 2018). Taking into account the last 5 years as a whole, the AFA involved in irregularities related to PP 2014-2020 was much higher than that related to PP 2007-2013, but it is based on less irregularities and can be more easily affected by a low number of 'exceptional' cases; nearly EUR 600 million out of about 830 million (see Table CP3) were related to just 2 cases. Considering all cases reported during 2014-2018, the AFA of cases related to the ERDF was less than half of that of CF cases.
Concerning the ESF, in 2018, for PP 2007-2013, there were persisting high financial amounts reported despite a steep decrease in the number of irregularities reported (+104% in the AFA) and a strong increase of the financial amounts reported in the same year for PP 2014-2020 (+374% in the AFA). However, concerning PP 2007-2013, this is mainly due to one irregularity reported by Portugal, representing about 60% of all relevant financial amounts reported in 2018. Data for PP 2014-2020 is less affected by single cases, but one irregularity accounted for about 30% of all relevant financial amounts reported in 2018 (three irregularities accounted for about 50%).
Given the above, even if data on AFAs might point to some improvement in the targeting of control activities (see Graphs CP1), the trend of the financial amounts must always be assessed while bearing in mind that it can be strongly influenced by single observations of significant value. During 2014-2018, cases which involved over EUR 5 million represented less than 1% in terms of numbers, but 44% in terms of amounts. 71% of these cases concerned the ERDF, while 21% concerned the Cohesion Fund. In such a context, where 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.
In an attempt to isolate the 'core' trends, Graphs CP2 show the financial amounts and AFAs during the last five years, where the first and the last percentiles are excluded from the analysis. In Graphs CP2, PP 2007-2013 and PP 2014-2020 are kept separate. For PP 2007-2013, the AFAs involved in cases related to ESF and EFF have been relatively stable during the last five years, while those involved in irregularities related to CF and ERDF have been following upward trends.
Extending the analysis to the whole programming period (Graph CP3), it can be noticed that:
·the rising trend of CF AFA started in 2015 after four years when it had continuously decreased, with the exception of 2012, from the peak it had reached during the fourth year of implementation (2010);
·The ERDF AFA followed a more stable rising trend, which accelerated since 2016 and has not reverted yet;
·during the third year of implementation (2009), the ESF AFA jumped to the level where it remained quite stable until 2018;
·The EFF AFA continuosly rose (with the exception of 2011) until the seventh year of implementation (2013) and then it remained quite stable until 2018.
Graph CP4b suggests similar patterns in relation to PP 2014-2020:
·CF AFA has experienced a sharp rise, which differently from PP 2007-2013 briefly stopped in 2017 before strongly resuming in 2018. If the PP 2007-2013 patterns are confirmed for this programming period, as the number of controls increase towards a peak that could be reached in 2022-2023, the CF AFA may be expected to decrease, but improvements in terms of risk analysis for targeting controls could induce different patterns. So far, apart from 2017, CF AFA for PP 2014-2020 has been higher than in the corresponding years of the previous programming period;
·The trend of ERDF AFA is similar to that recorded for PP 2007-2013, even if the ups and downs have been more 'extreme' for PP 2014-2020. However, it should be considered that, for example, the peak for ERDF in 2016 was just based on 7 irregularities. 2018 is the fifth year of implemention. At the same time of PP 2007-2013, a rising trend started that has not stopped yet (with the exception of 2015). Improvements in terms of risk analysis for targeting controls might sustain a similar pattern also for the current programming period. So far, ERDF AFA for PP 2014-2020 has been higher than that for the previous programming period;
·ESF and EMFF AFA follow more stable patterns.
For the years 2014-2018, PP 2007-2013 and PP 2014-2020 are considered together in Graphs CP5, which confirm the rise of the AFAs of irregularities related to CF and ERDF.
Graphs CP6 deepen the analysis of the AFAs, making the distinction between irregularities reported as fraudulent and not reported as fraudulent. For all funds, the AFAs involved in fraudulent irregularities was constantly and, in particular for CF and ERDF, significantly higher than those related to non-fraudulent irregularities. This underlines the importance of co-operation with the judicial authorities in protecting the EU financial interests.
With respect to fraudulent irregularities, the AFAs involved in CF cases plummeted from a peak in 2014, while remaining at a level that is still double the one related to ERDF cases. The AFA involved in ERDF cases increased significantly during the last five years.
With respect to non-fraudulent irregularities, the AFA involved in CF cases followed the opposite trend: it strongly increased from 2014 to 2017 and in 2018, while decreasing, it remained at a level that is significantly higher than in 2014. The AFA involved in ERDF cases has been increasing since 2015 and was stable in 2018.
The findings reported above support the hypothesis of some improvement in the targeting of control activities, which could be underpinned and made durable by the implementation of the recommendations that have been made in last year's Report, in particular concerning risk analysis.
4.1.1.Irregularities reported as fraudulent
4.1.1.1.Trend by programming period
Table CP4 provides an overview by PP and fund of the irregularities reported as fraudulent in the last five years (2014-2018). In some cases, the Member States reported irregularities as non- fraudulent, while a penal procedure had been started. This may be due to the need to wait for some procedural steps before classifying the irregularity as fraudulent. These cases are not included as fraudulent in the analysis for this Report; considering them as such would increase the number of fraudulent irregularities by about 9% (3% in terms of financial amounts involved).
Irregularities reported as fraudulent have been following a stable trend since 2016. With respect to the peak in 2015, the number of the irregularities reported in 2018 has decreased by just 11%, while it is still 41% higher than the level in 2014.
This is the result of different dynamics with reference to different programming periods. During the last five years, while the fraudulent irregularities linked to the PP 2000-06 have been decreasing to reach nearly 0 since 2016, those linked to the PP 2007-13 have peaked in 2015, gradually decreased in the following years and dropped in 2018 so that in this year they were overcome by those related to PP 2014-2020. These dynamics were linked to the implementation cycle of PP 2007-2013 and the closure of PP 2000-2006. Reporting related to PP 2014-2020 basically started in 2017 and accelerated in 2018. Nearly 20% of all cases reported in 2018 were reported as fraudulent (about 15% for the period 2015-2018). These percentages are significantly higher than those referring to PP 2007-2013. This tendency to focusing on fraudulent behaviours is analysed further in the next Sections.
Table CP5 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 and skyrocketed in 2018. Growth in 2017 was mainly pushed by PP 2007-2013 (all funds). In 2018, PP 2007-2013 continued to contribute to growth through the ESF, whose financial amounts increased again, but this was due to one case reported by Portugal, where exceptional financial amounts were involved. For PP 2014-2020, as it could be expected, in 2018 the financial amounts involved in fraudulent irregularities increased for all funds, but the increase related to the ERDF was extreme. This was mainly due to two irregularities reported by Slovakia, accounting for nearly EUR 600 million. However, also net of these cases, the financial amounts involved in ERDF cases would have increase by about EUR 107 million, which is still significant.
Focusing on PP 2007-2013, the financial amounts involved in irregularities reported as fraudulent for the ERDF were predominant (79% in 2014-2018), also due to the high share of EU financing that is channel through this fund. A similar trend was emerging also with reference to PP 2014-2020.
4.1.1.2.Trend by Fund
The analysis of the same data presented in Tables CP4 and CP5 but focussed on the distribution of the irregularities reported as fraudulent by Fund (Tables CP6 and CP7), highlights the following situations:
(1)ERDF: This fund was impacted by the highest number of cases and absolute financial amounts (but not relative to payments). 2015 witnessed a jump in the total number of irregularities (+98% with respect to 2014). Since then, the number of fraudulent irregularities detected in the Member States remained at this new higher level. In 2018, this was possible because the drop of new cases related to PP 2007-2013 was compensated by the sharp rise of the number of irregularities detected in relation to PP 2014-2020 (see also Section 4.1.3 about a comparison between PP 2007-2013 and PP 2014-2020).
Instead of peaking in 2015, the financial amounts continued to increase until 2018, when they litteraly burst. The extreme rise in 2018 was strongly influenced by the two irregularities reported by Slovakia (summing up to nearly EUR 600 million). However, even net of these two cases, the increase from 2017 would still be noticeable (+31%). The AFA significantly increased during 2016-2018, by about 20% each year (considering 2018 net of 2 cases where exceptional financial amounts were involved – see also Graph CP5b);
(2)ESF: 2015 witnessed a peak in the total number of irregularities (+18% with respect to 2014), after which it declined at a sustained pace. The variations in the related financial amounts were much more accentuated and did not necessarily follow the changes in numbers.
In 2015, the financial amounts recorded an increase of nearly 500%. This was influenced by a sudden, isolated and extreme rise related to PP 2000-2006, based on 2 'exceptional' irregularities reported by Italy and accounting for more than EUR 40 million (out of EUR 48 million). In addition, while the number of cases related to PP 2007-2013 increased by 50%, the financial amounts increased nearly fourfold. Also in this case, the disproportionate rise of the financial amounts was mainly due to one 'exceptional' irregularity, this time reported by Portugal. The following two years, the financial amounts dropped back, before bouncing up in 2018 (+188% with respect to 2017). Again, this jump in 2018 was due to one irregularity reported by Portugal where exceptional financial amounts were involved;
(3)Potential frauds affecting the Cohesion fund are now reported regularly (since 2010), and from 2016 to 2018 they tripled, in terms of number, and more than doubled, 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.
4.1.2.Irregularities not reported as fraudulent
Table CP8 provides an overview by PP and fund of the irregularities not reported as fraudulent in the last five years (2014-2018). Table CP9 shows the financial amounts involved in these irregularities. 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.
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 related to PP 2007-2013 was fast for the ERDF (as from 2016 and accelerating in 2017), the ESF (as from 2017) and the CF (as from 2016 and accelerating in 2018). The financial amounts followed a different pattern and increased further in 2016, before rapidly falling as from 2017, but not as much as the number of irregularities.
The AFAs for PP 2007-2013 have been experiencing different trends depending on the Fund: for the CF they have been decreasing since 2017, while for the ESF, 2018 is the first year of decrease after two years of rise. The AFAs of the ERDF have instead been increasing at an accelerated pace since 2016 (+23% in 2016, +42% in 2017 and +88% in 2018). As mentioned, these trends are influenced by few irregularities where 'exceptional' financial amounts were involved. 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.
The financial amounts reported in relation to PP 2000-2006 are fading towards zero. In 2016, the reporting of irregularities referring to PP 2014-2020 started and increased in 2017 and 2018, as implementation was progressing. Number and financial amounts were still low, but they can be expected to grow during next years, in line with the implementation cycle. Taking all Funds together, during the period 2014-2018, the AFA for PP 2014-2020 was quite lower than for PP 2007-2013.
Graph CP6d in Section 4.1 shows, for the different funds, the 'core' trend of AFAs of irregularities not reported as fraudulent, taking PP 2007-2013 and PP2014-2020 together. AFA of CF strongly increased until 2017, before falling in 2018. Also the AFA of ERDF, which was constantly and significantly lower than that of CF, increased until 2017, but remained stable in 2018. The AFA of ESF and EFF/EMFF followed a flatter trend, which was still slightly increasing for ESF.
4.1.3. Irregularities reported in relation to the PP 2014-2020: comparison with PP 2007-2013
The current Programming Period started in 2014, about 5 years ago. Reporting of irregularities basically started in 2016 and increased in 2017 and 2018 (see Table CP2). To put this trend into perspective, it is worth comparing it with the number and financial amounts of the irregularities that were recorded during the first 5 years of PP 2007-2013. Tables CP10 and CP11 provide this information.
The following Graphs provide for an even more precise comparison based on the actual date of reporting. In any case, it must be borne in mind that this comparison is affected by the fact that the irregularities related to PP 2007-2013 are more 'mature' than irregularities related to PP 2014-2020, which have been just reported. The number and the financial amounts involved in the irregularities related to PP 2007-2013 are the result of several years of investigation (after detection) that brought into the picture additional information to confirm or refute the hypothesis that an irregularity had been perpetrated, to classify the irregularity (fraudulent or non-fraudulent), to quantify the financial amounts actually involved, etc.
As shown by Graph CP7, after about 5 years for the start of the programming period, the number of irregularities reported as fraudulent was higher for PP 2014-2020 than for PP 2007-2013. There was a slower start of detection related to the current programming period, but during the fifth year of implementation there was a strong acceleration that filled the gap. The comparison is more difficult in terms of financial amouts (see Graph CP8) because of the impact of a few cases with exceptional financial amounts involved. The financial amounts reported in relation to PP 2014-2020 are much higher than the previous PP, but there was a noticeable jump at the beginning the fifth year of implementation due to the two cases already mentioned above, which summed up to about EUR 600 million. However, it should be noticed that also PP 2007-2013 experienced a similar, even if smaller, jump, because, at the end of the fourth year of implementation, a case where about EUR 120 million were involved was reported. Taking these outliers out of the analysis, the financial amounts involved in the fraudulent irregularities reported within PP 2014-2020 were still higher than the financial amounts reported within PP 2007-2013 during the same period after the start of the programming period.
This is the outcome of different patterns followed by different funds (see Graphs CP9a-CP9c). The irregularities reported as fraudulent in relation to CF and ERDF significantly increased, while those related to the ESF have been lagging behind by a rather stable number of cases. However, the financial amounts associated to the fraudulent irregularities related to ESF for PP 2014-2020 were considerably higher than those for PP 2007-2013. The irregularities related to the fisheries policy have been 11 for PP 2014-2020, while for PP 2007-2013 only one irregularity had been reported.
While the increase of CF fraudulent irregularities was mostly due to detections in Slovakia, the increase of ERDF fraudulent irregularities had a broader basis: 13 Member States recorded an increase (in particular, Hungary with 35 cases more than PP 2007-2013, followed by Slovakia – +12 – Czech Republic - +11 – and Poland - +10) and 9 Member States a decrease (in particular the UK with 12 cases less than PP 2007-2013). For the ESF, about half of the Member States have not reported any fraudulent case related to PP 2014-2020 and had done the same after a comparable amount of time after the start of PP 2007-2013. For the rest, 6 Member States recorded an increase and 9 Member States a decrease. These changes have been significant for Germany (minus 48 cases), Poland (plus 37 cases, evenly spread during the fourth and fifth year of implementation) and, to a lesser extent, Bulgaria (minus 12, due to no reporting for PP 2014-2020).
The irregularities not reported as fraudulent showed a completely different behaviour. The decrease in the number and financial amounts reported after 5 years from the start of the programming period is striking (see CP10 and CP11). This significant difference between PP 2007-2013 and the current 2014-2020 warrants for further analysis.
The number and related amounts of irregularities not reported as fraudulent can be influenced by the state of implementation of the programming period. An indicator to gauge the state of implementation may be the interim payments that have been made to the Member States, as these payments should reflect the progression of eligigle expenditure. This is shown by Graph CP12, including CF, ERDF and ESF, which absorb most of the financial resources.
During the first 5 years from the start of PP 2014-2020 (from 2014 to 2018), the Member States have received less interim payments than during the first 5 years from the start of PP 2007-2013 (from 2007 to 2011). At the end of 2018, this (cumulative) gap still amounted to about -25%, but it was higher before (see CP12). This may contribute to explain the difference in terms of number of non-fraudulent irregularities, which is higher (about -60% - see Table CP10 and Graph CP10).
A closer look at Graph CP10 and the underlying data reveals that a significant share of the gap is due to a sudden acceleration in the number irregularities related to 2010 (fourth year of implementation of PP 2007-2013), which were reported at the beginning of 2011. More than half of this jump was due to irregularities reported by two Member States (Greece and the UK – see also below Graph CP16). Then during the fifth year of implementation (2011) the number of irregularities continued to grow at a sustained pace. PP 2014-2020 followed a different pattern. There was no significant increase related to 2017 (fourth year of implementation, as it was 2010 for PP 2007-2013); reporting continued to raise at the same pace, instead of accelerating. At the beginning of 2019 (with reference to the year 2018, fifth year of implementation), a noticeable increase in the number of irregularities reported took place. This sudden growth was smaller than the one recorded for PP 2007-2013 after four (and not five) years from the start of the programming period (see above), but it might corroborate the hypothesis that, at least in part, this gap in reporting may have been influenced by delayed implementation of the programming period.
In Graphs CP 13-15, the irregularities not reported as fraudulent are split by fund. The widest gap is recorded for the ERDF, for which the irregularities reported were just one third of those reported during the first 5 years of PP 2007-2013. For the CF and ESF, there was still a significant gap with respect to PP 2007-2013, even if it was not as wide as for ERDF. Furthemore, for the CF this negative gap was decreasing, in terms of numbers, while the financial amounts reported in relation to PP 2014-2020 were significantly higher than those related to PP 2007-2013. For the ESF, the negative gap started to widen towards the end of fifth year of implementation, both in terms of number and financial amounts. Also for the fisheries policy, the number of irregularities was decreasing (from 30 for PP 2007-2013 to 15 for PP 2014-2020) while the financial amounts were broadly stable around 1million.
Given that ERDF showed the widest and most persistent gap between PP 2007-2013 and PP 2014-2020, Graph CP16 shows the comparison, MS by MS, in terms of number of irregularities not reported as fraudulent, with specific reference to this fund. These data should be read while comparing the stage of implementation of the two PPs, for example on the basis of the payments already received by the Member State (see above). This is outside the scope of this Report, but the competent national authorities can build on it to tailor and deepen the analysis, to ensure that the decrease in reporting is not due to lower quality and intensity of detections and enforcement activities. For the majority of MS, the numbers of non-fraudulent irregularities related to the two PPs are on persistently diverging paths (Austria, Belgium, the Czech Republic, Germany, Spain, Finland, Greece, Italy, Lithuania, Latvia, the Netherlands, Poland, Romania, Sweden, Slovenia). For other Member States, at the cut-off dates, the gap was significant, while there had been times during these five years when the number of non-fraudulent irregularities related to PP 2014-2020 were nearer to those related to PP 2007-2013 (Portugal, Slovakia, the UK). Finally, there are Member States were there was no significant gap (Cyprus, Denmark, Estonia, Malta) or the irregularities related to the current PP were more than those related to PP 2007-2013 (Bulgaria, France, Croatia, Hungary). During the first five years of both PP 2007-2013 and PP 2014-2020, Ireland and Luxembourg have not reported any non-fraudulent irregularity related to ERDF.
Graphs CP17 shows the same comparison MS by MS, but in terms of financial amounts. For the majority of MS, the financial amounts involved in non-fraudulent irregularities related to the two PPs were on persistently diverging paths (Austria, the Czech Republic, Germany, Spain, Greece, Hungary, Italy, Lithuania, Latvia, the Netherlands, Romania, Sweden, Slovenia, the UK). For other Member States, at the cut-off dates, the gap was significant, while there had been times during these five years when the financial amounts involved in non-fraudulent irregularities related to PP 2014-2020 were nearer to those related to PP 2007-2013 (Estonia, Poland, Portugal). Finally, there are Member States were there was no significant gap (Denmark, Malta) or the irregular financial amounts detected in relation to the current PP were more than those related to PP 2007-2013 (Belgium, Bulgaria, Cyprus, Finland, France, Croatia, Slovakia). As mentioned, during the first five years of both PP 2007-2013 and PP 2014-2020, Ireland and Luxembourg have not reported any non-fraudulent irregularity related to ERDF.
This comparative analysis between PP 2007-2013 and 2014-2020 suggests the need for the Member States to carefully monitor the situation, also in order to exclude that the decrease of non-fraudulent irregularities reported is due to a decline in the intensity or quality of detection activities. At least in part, this decrease might be a delay due to a slower implementation of PP 2014-2020 in comparison with PP 2007-2013 (see above in this Section). However, this effect should fade down as the implementation of PP 2014-2020 catches up. Besides detection efforts and degree of implementation, other explanatory factors may lay in differences in the management and control systems of the different Member States in relation to the two programming periods, with an impact in terms of prevention.
In general, rules on thematic concentration might have led to more effective spending. Focusing more on the management side, the 2007-2013 National Strategic Reference Frameworks (NSRF) have been replaced with the 2014-2020 Partnership Agreements. Inter alia, the latter must present an assessment of the administrative capacities of the authorities involved in implementation of the ESI Funds together with – where necessary – a summary of actions in order to improve them. In addition, the legal framework at the basis of PP 2014-2020 requests the managing authorities put in place effective and proportionate anti-fraud measures taking into account the risks identified. Furthermore, with reference to PP 2014-2020 the possibility to use simplified cost options has been extended, but the impact depends on the extent to which implementing partners took advantage of this possibility.
Another change that can be of relevance to explain the pattern of non-fraudulent irregularities is the introduction of annual accounts that are prepared by the Member Stares and then examined and accepted by the EC each year (instead of at the closure of the programming period only). An unqualified audit opinion is necessary to accept accounts. This might have contributed to strenghtening internal control at Member State level. In this framework, Member States may have an increased tendency to exclude from the annual accounts expenditure for which they have doubts about legality and regularity; this expenditure can be included in an application for interim payment relating to subsequent accounting years, while for the current year, it is automatically recovered by the EC (without constituting a financial correction and without reducing support from the Fund to the relevant operational programme).
These are just a few examples of factors that might potentially influence the number of irregularities reported, but the actual relevance and impact of these or other changes in the different Member States should be properly evaluated before being taken as the explanation of a persistent decline in detections.
Changes in the legal framework and implementation context, including anti-fraud systems, may be reflected in the most reported types of irregularities detected by the Member States. The following Tables provide an overview for the irregularities reported as fraudulent (Table CP12) and not reported as fraudulent (Table CP13) by the Member States in relation to PP 2007-2013 and PP 2014-2020. As above, for PP 2007-2013, only the irregularities that had been reported after a comparable period of time from the start of the programming period are considered.
For the irregularities reported as fraudulent, Table CP12 shows significant increases in the number of cases related to incorrect/missing or false documents, infringement of public procurement rules and ethics & integrity, which nevertheless were not always accompanied by increases in the financial amounts involved. The most significant declines concerned violations related to eligibility/legitimacy of expenditure or measure and the infringement of contract provisions/rules.
For the irregularities not reported as fraudulent, Table CP13 shows that for each of the four most reported categories for PP 2014-2020, the number of cases where they were mentioned is about one third of the number of cases where they had been mentioned for PP 2007-2013 after a comparable period of time. In relative terms, multiple financing experienced the biggest decrease, while infringements concerning the request, accounts and bankruptcy were more stable with respect to PP 2007-2013. 'Product, species and/or land' was the only category with an increase in comparison with PP 2007-2013. Most of these violations were reported by Poland and mainly concerned variations in quality or content.
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; 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 (2014 to 2018), to examine all information available, which dates back to 2008. Comparisons between the first years of implementation of PP 2007-2013 and the situation concerning PP 2014-2020 until December 2018 are included, as relevant.
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 CP14). The majority of the irregularities were notified over the period 2015-2017, which was between the ninth and eleventh year from the start of the programming period. They 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 (see Section 4.1). For 186 irregularities, the objective was not mentioned by the Member States.
Table CP15 provides information about the financial amounts involved in the reported irregularities. They broadly followed the same pattern of the number of irregularities in Table CP14, 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 were higher than those reported in 2015 (which was instead the peak, in terms of numbers). In 2016, irregular amounts reported in relation to the Cohesion Fund were exceptionally high, as already showed in Table CP3 and highlighted in Section 4.1;
·the Multiobjective actions reported in 2018, where the irregularities fell abruptly while the financial amounts involved were stable. This was impacted by two cases reported in 2018 by Slovakia, whose irregular financial amounts summed up to about EUR 160 million. To put it into perspective, it can be considered that the two biggest cases reported during the previous year (by Spain) summed up the about EUR 75 million. See also Section 4.2.1.1, about fraudulent irregularities.
As for the number of irregularities, the majority of financial amounts were notified during the period 2015-2017 and mainly concerned the Convergence objective (75%).
4.2.1.1.Irregularities reported as fraudulent by Objective
Tables CP16 and CP17 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. It is worth highlighting the record-high reporting of irregular financial amounts in 2018 for the Multiobjective actions. This was due to 4 large cases (with more than EUR 10 million involved in each irregularity) reported by Slovakia, Portugal and the Czech Republic, summing up to about EUR 97 million.
The higher share represented by the Convergence objective in comparison with that presented in the previous Section was also significant (69% of cases and 83% 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) was related to the Fisheries (6.8%), the European Territorial Cooperation (6.8%) and to the Convergence (5.7%) objectives. Regional competitiveness and Employment had the lowest FFL (2.8%).
Financial amounts involved in irregularities reported as fraudulent represented about 15.8% of the total reported for PP 2007-13. The highest share (Fraud Amount Level – FAL) was related to Fisheries (18.7%), Convergence (17.5%), the European Territorial Cooperation (16.9%). Regional competitiveness and Employment had the lowest FAL (4.8%).
The difference between FFL and FAL indicates the higher financial impact of fraudulent irregularities compared to the non-fraudulent infringements; 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 CP18 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 Multiobjective programmes, Convergence and Fisheries where the detection rate is about 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 CP19 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 represented about 39% of the total.
FFL was highest for 'Tourism' (11.8%) and the top four priorities (in terms of FFL) in Table CP19 were all above or about 9%, which was nearly double the average.
From the financial amounts point of view, the most significant impact concerned 'RTD' and 'Transport'. Financial amounts related to the irregularities reported as fraudulent in relation to these two priorities represented 44% of the total. ‘Transport’ retained by far the highest average value, about eight times R&TD and nine times the overall average. These two priorities were followed, at a distance, by another group of priorities that were affected by significant irregular financial amounts: 'Urban and rural regeneration', 'Tourism' and 'Environmental protection and risk prevention'.
FAL was highest for 'Tourism' (34%), 'Urban and rural regeneration' (33%), 'Improving human capital' (32%). The priorities 'Tourism' and 'Urban and rural regeneration' stood 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 CP19 may depend on errors in encoding by Member States.
For about 25% of the irregularities used for this analysis, information was not provided about the priority area concerned, decreasing in comparison with previous years.
Table CP20 is related to PP 2014-20. It shows the number of irregularities reported as fraudulent by priority area since the beginning of the PP, their related financial amounts, and allows the comparison with the situation concerning PP 2007-2013 when the same period of time had passed after the start of the programming period. Comparison with the full 2007-2013 would be misleading as projects pertaining to different priorities can have different timelines for the implementation; this may influence the time when irregularities are more likely to be detected. This is possibly the reason why only one irregularity has been reported with reference to the priority 'Transport' for PP 2014-2020. In fact, this happened also for PP 2007-2013 when the same amount of time had passed after the start of the programming period (see Table CP20).
The priorities for the PP 2014-2020 are listed in the Commission Implementing Regulations (EU) 184/2014 and 215/2014 and they are different from the priorities for PP 2007-2013. In Table CP20, the priorities for PP 2014-2020 are reported in white; contrary to the Regulations in force, the Member States continued to encode the irregularities in IMS using the priorities that were valid for PP 2007-2013. The correct priorities were used only in 3 cases out of 233.
First of all, in Table CP20, it can be noticed that the fraudulent irregularities detected by the Member States increased by about 15%, from 199 to 233. The number of cases where the priority was not specificed decreased from more than 50% to 15%, which was a remarkable improvement. However, this improvement impacts on the comparison at the level of single priorities, because, to a different extent, increases in the number of irregularities may have been underpinned by the higher number of irregularities for which the priority has been specified rather than by the higher number of detections. This is impacting even more the analysis of the non-fraudulent irregularities (see Section 4.2.2.2).
With reference to PP 2014-2020, the prevalence of the priority 'R&TD' was even more marked than for PP 2007-2013. The priority 'Improving access to employment and sustainabily' ranked second in relation to PP 2014-2020, with a number of cases similar to PP 2007-2013, but higher financial amounts involved. A relatively high number of irregularities (and related financial amounts) have been detected in relation to 'Environment protection and risk prevention', which was not yet the case at the same stage of PP 2007-2013. This is mostly due to reporting by Slovakia (see also Section 4.2.2.3).
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 CP21 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’. Then there was a group of four priorities that recorded between 1 500 and 2 000 irregularities each. Two of them relate to investments in infrastructures ('Investment in social infrastructure' and 'Transport') while the other two refer more to investing in human capital ('Improving human capital' and ‘Increasing the adaptability of workers and firms, enterprises and entrepreneurs'). ‘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 24% of the total number and 46% 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 remained high (43%) and higher than for the fraudulent irregularities, while it was improving.
Table CP22 is related to PP 2014-20. It shows the number of irregularities not reported as fraudulent by priority area since the beginning of the PP, their related financial amounts, and allows the comparison with the situation concerning PP 2007-2013 when the same period of time had passed after the start of the programming period. As mentioned above, there are new priorities for PP 2014-2020; they are reported in white in Table CP22. Contrary to the Regulations in force, the Member States continued to encode the irregularities in IMS using the priorities that were valid for PP 2007-2013. The correct priorities were used only in about 50 cases out of 1 400.
First of all, it can be noticed that the non-fraudulent irregularities detected by the Member States decreased by about 60%, as already highlighted in Section 4.1.3. The number of cases where the priority was not specificed decreased from more than 63% to 16%, which was a remarkable improvement. As mentioned, this improvement has a significant impact on the comparison between single priorities in different programming periods. In relation to the first five years of implementation of PP 2007-2013, 2 070 non-fraudulent irregularites had been left with no specification of the affected priority. In relation to PP 2014-2020, this declined to just 218.
'R&TD' was the priority most affected by irregularities, with an increasing number of cases and financial amounts involved, with respect to PP 2007-2013. The priority that recorded the highest relative increase in numbers was 'Energy', mostly due to reporting by the UK and Poland. For several other priorities, the number of irregularities increased, but it must be considered that, to a different extent, this may have been influenced by the huge difference between the two PP, in terms of cases where the priorty was not specified (see Section 4.2.2.1). Despite this, 'Trasport' fell to less than one third of the number of cases reported for PP 2007-2013 after the same period from the start of the programming period. However, the financial amounts decreased only by less than a half. A similar pattern was being followed by 'Increasing the adaptability of workers and firms, enterprises and entrepreneurs' and 'Investment in social infrastructure'. However, for the latter, the financial amounts decreased much more. It can be considered that the new priorities 'Social, health and education infrastructure and related' and 'Investing in education, training and vocational training for skills and lifelong learning investment' covered similar initiatives, but with 19 irregularities reported, they could not compensate.
Apart from 'R&TD', 'Environmental protection and risk prevention' was basically the only priority which recorded a significant increase in financial amounts in PP 2014-2020.
4.2.2.3.PP 2007-2013: irregularities related to the priorities 'Tourism' and 'Environment' by theme
Concerning the impact of potential fraud on the priority 'Transport', the financial amounts involved in irregularities concerning the themes:
·'Railways' significantly decreased (-70%), as a result of three cases cancelled by Italy;
·'National roads' increased nearly fivefold, because of a new irregularity detected by Romania and a case reported by Italy in 2016, which has been re-classified as fraudulent and to which much higher irregular financial amounts have been associated.
In terms of number of non-fraudulent irregularities, 'Regional/local roads' remained the most affected theme, with 44% of the total. In terms of financial amounts, the themes 'Railways' and 'Motorways (TEN-T)' were still the most impacted, accounting together for about 58% of the total. The irregular financial amounts involved in the theme 'Railways' increased by about EUR 20 million (which is just about 5%) but the number of irregularities increased by 37%, mainly due to cases reported by Italy.
Given the above, this year the analysis of two other priorities is provided:
·'Tourism', which is the priority with the highest incidence of fraud;
·‘Environmental protection and risk prevention’, which is a priority that ranks among the most affected by non-fraudulent irregularities and recorded the second highest average financial amount related to fraudulent irregularities.
Tourism
As metioned, ‘Tourism’ is the priority with the highest FFL (11.8%), FAL (34%) and FDR (1.4%). In addition, it has the highest IDR.
Figure CP1 details the specific priority themes that were affected by irregularities reported as fraudulent. The larger the square, the higher the number of irregularities; the darker the colour, the higher the financial amounts involved.
The residual theme 'Other assistance to improve tourist services' was by far the most impacted. It represented about 74% of the irregularities reported as fraudulent, and about 71% of the related financial amounts. About half of these irregularities were detected in Romania, while Slovakia was the Member State with the highest financial amounts involved. Four countries (Slovakia, Romania, Czech Republic and Portugal) accounted for 94% of the financial amounts. Two other themes shared the remaining irregularities: 'Protection and development of natural heritage' and 'Promotion of natural assets' (most of cases and irregular financial amounts detected in Romania).
Figure CP2 shows the same level of detail for the irregularities not reported as fraudulent.
The picture is similar to the one referring to the fraudulent irregularities: the residual theme was involved in 71% of the non-fraudulent irregularities, accounting for 80% of the financial amounts. About half of these irregularities (and related financial amounts) was detected in Poland and the Czech Republic. The two other themes recorded a similar number of irregularities.
Environmental protection and risk prevention
As mentioned, ‘Environmental protection and risk prevention’ was hit by the second highest number of non-fraudulent irregularities (after 'R&TD') and the third highest level of irregular (non-fraudulent) financial amounts (after 'R&TD' and 'Transport'). At the same time, this priority was not immune from fraud: it recorded the fifth highest level of irregular financial amounts (after 'R&TD', 'Transport', 'Urban and rural regeneration' and 'Tourism').
Similar to Figure CP1, Figure CP3 details the specific priority themes that were affected by these irregularities reported as fraudulent.
The highest number of fraudulent irregularities related to 'Management of household and industrial waste'. About half of the fraudulent irregularities and 60% of the related financial amounts concerning this theme were detected in Slovakia. The highest level of irregular financial amounts pertained to 'Water treatment (waste water)', which reached an average financial amount of about EUR 3.2 million. Half of the fraudulent irregularities and about 80% of the related financial amounts concerning this theme were detected in Slovakia. Also 'Risk prevention' was quite impacted by fraud, with most cases in the Czech Republic and most of the irregular financial amounts detected in Poland.
As mentioned in Section 4.2.2.1, in relation to PP 2014-2020 and differently from what had happened during the same period after the start of PP 2007-2013, the priority ‘Environmental protection and risk prevention’ has already been impacted by a significant number of fraudulent irregularities. Most of them are still related to 'Management of household and industrial waste' and reported by Slovakia.
Figure CP4 shows the same level of detail for the irregularities not reported as fraudulent.
The highest number of non-fraudulent irregularities related to 'Water treatment (waste water)'. About half of the non-fraudulent irregularities and related financial amounts concerning this theme were detected in Poland. Adding 'Management of household and industrial waste', these two themes covered about half of the non-fraudulent irregularities related to this priority. The theme 'Management and distribution of water (drinking water)' ranked third, both in terms of number of irregularities and financial amounts involved (mainly because of detections in Romania). Then 'Risk prevention' was also significantly impacted by non-fraudulent irregularities, with Italy, Poland and the Czech Republic accounting for about half of cases and irregular financial amounts.
As mentioned in Section 4.2.2.2, in relation to PP 2014-2020, the financial amounts involved in non-fraudulent irregularities concerning the priority ‘Environmental protection and risk prevention’ significantly increased in comparison with PP 2007-2013 during the same period after the start of the programming period. Most of these irregular financial amounts are still related to 'Water treatment (waste water)', but they have been reported by Slovakia.
4.2.2.4.Types of irregularities / modus operandi detected related to the priorities 'Tourism' and 'Environment protection and Risk prevention'
Table CP23 provides an overview of the categories of irregularities reported in connection with the priority ‘Tourism’ within PP 2007-2013.
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, 12% of cases affecting the priority ‘Tourism’ were reported as fraudulent (see table CP19).
Focusing on the irregularities reported as fraudulent, the most mentioned categories were referring to 'incorrect/missing/false or falsified documents' and the 'eligibility or legitimacy of the expenditure/measure', often combined in the same case. Infringements of public procurement rules were less frequent, but they were associated to higher average irregular financial amounts (more than EUR 800 000). The violations concerning 'ethics and integrity' concerned conflict of interest or bribery/corruption.
Focusing of the irregularities not reported as fraudulent, infringements of public procurement rules were the most mentioned, followed by violations concerning the 'eligibility or legitimacy of the expenditure/measure'. They were often combined in the same case. The categories incorrect/missing/false or falsified documents' and 'contract provisions/rules' were also used quite often and the latter was the one with the highest irregular financial amounts involved (among the aforementioned most reported categories).
The categories 'ethics and integrity' and 'incorrect/missing/false or falsified documents' featured the highest FFLs (respectively 69% and 43%), followed, at a distance, by 'eligibility or legitimacy of the expenditure/measure' (17%). 'Infringement of public procurement rules' and 'Violations of contract provisions/rules' had relatively low FFLs (respectively 5% and 8%).The average financial amounts associated to these categories were much higher in case the related irregularities were reported as fraudulent.
Similarly to Table CP23, Table CP24 provides an overview of the categories of irregularities reported in connection with the priority ‘Environment protection and Risk prevention'’ within PP 2007-2013.
In general, it can be noticed that 2.7% of cases affecting this priority were reported as fraudulent (see table CP19).
Focusing on the irregularitiers reported as fraudulent, the most mentioned categories were referring to 'Infringement of public procurement rules' and 'eligibility or legitimacy of the expenditure/measure', often combined in the same case. 'Incorrect/missing/false or falsified documents' were mentioned less often, but with the highest financial amounts involved. Half of the violations concerning 'ethics and integrity' concerned corruption. One case was about conflict of interest.
Focusing of the irregularities not reported as fraudulent, 'Infringements of public procurement rules' were by far the most mentioned, followed by violations concerning 'contract provisions/rules' and 'eligibility or legitimacy of the expenditure/measure'.
The FFL for 'Infringement of public procurement rules' and 'of contract provisions/rules' were low (about 2%). 'Incorrect/missing/false or falsified documents' had the highest FFL among the most reported categories (about 16%).
4.2.2.5.Geographical distribution of irregularities (fraudulent and non-fraudulent) detected in relation to the 'Tourism' and 'Environment protection and Risk prevention'
Maps CP1 and CP2 show the geographical distribution of the irregularities (fraudulent and non-fraudulent) reported in relation to the priorities Tourism and 'Environment protection and Risk prevention'. It is worth reminding that this is based on the irregularities for which the Member States have specified the priority affected by the irregularity. For example, France has never specified the affected priority, so even if a number of irregularities might possibly concern Tourism or 'Environment protection and Risk prevention', this cannot be reflected in this analysis and in Maps CP1 and CP2.
Some Member States were relatively more affected by (or were more efficient in detecting) irregularities related to 'Tourism', such as Hungary and the United Kingdom, while in other Member States irregularities related to 'Environment protection and Risk prevention' weighed more, such as in Bulgaria and Poland.
4.3 Reasons for performing control
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.
In last year's Report, an analysis of the reasons for performing controls was introduced and led to the recommendation to further exploit the potential of risk analysis, tailoring the approach to the different types of expenditure and taking advantage of best practices and the risk elements highlighted in that Report. Furthermore, it was recommended to facilitate and assess the spontaneous reporting of potential irregularities from the civil society and strengthen the protection of whistle-blowers that are also a crucial source for investigative journalism.
Tables CP25 and CP26 seem to confirm that so far there has been little improvement on the ground. However, as last year's Report was adopted at the beginning of September 2018, it is probably too early to draw any conclusion. Effective evolution from reactive to proactive detections based on risk analysis may take time.
With a focus on controls that led to discover irregularities reported as fraudulent, Table CP25 provides information on the number of controls that were performed because of reasons that can be linked to the above mentioned recommendations. It compares the situation until 2017 with the situation in 2018. On the one hand, Table CP25 does not show any significant change concerning the use of risk analysis. On the other hand, it shows a noticeable increase in the share of fraudulent irregularities detected through tips (from 7% to 17%), but this was not broad-based in terms of the Member States contributing to this improvement. Table CP25 shows also that, to a lesser extent, there was an increase in the share of fraudulent irregularities detected through the use of information published by the media (from 2% to 3.5%).
Table CP26 provides the same overview of Table CP25, with a focus on controls that led to discover irregularities not reported as fraudulent.
On the one hand, Table CP26 does not show any significant change concerning the share of non-fraudulent irregularities detected through tips (as it was instead the case for the fraudulent irregularities). On the other hand, it shows some increase in the share of non-fraudulent irregularities detected through the use of risk analysis (from 0.9% to 4.2%) and, to a lesser extent, making use of information published by the media (from 0.3% to 1.4%). Nearly all non-fraudulent irregularities detected through risk analysis in 2018 were reported by Poland and the Czech Republic, which were amongst the Member States that detected more often irregularities on the basis of risk analysis also before 2018.
4.4.Antifraud and control activities by Member States
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);
·the ratio of cases of established fraud on the total number of irregularities reported as fraudulent.
4.4.1.Duration of irregularities
With reference to the Cohesion and Fisheries policies, of the 40 776 irregularities (fraudulent and non-fraudulent) reported by Member States in relation to the PP 2007-13, 20 298 (50% of the total) involved infringements that have been protracted during a span of time. For the 2 010 irregularities reported as fraudulent, this percentage was higher, at about 60%. 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 30% of that including exclusively the fraudulent irregularities) or for which no reliable information has been provided by the Member States (27% of the whole dataset and 11% 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.
Figures CP5 and CP6 show the average duration of the different phases a case can go through, from perpetration to case closure. Figure CP5 focuses on irregularities reported as fraudulent, while Figure CP6 covers the ones not reported as fraudulent. Both Figures refer to the PP 2007-2013 (Cohesion and Fisheries policies).
Both for fraudulent and non-fraudulent irregularities, on average, it took more than two years to come to the suspicion that an irregularities had been or was being perpetrated. Once the suspicion arose, the Member State detected the irregularity in less than half a year. Then the irregulary was reported to the Commission only after eight months from the detection. The only significant difference between fraudulent and non-fraudulent irregularities was in the average time from the reporting to the Commission to the case closure, which was much longer for the irregularities reported as fraudulent. This is consistent with the longer duration of penal proceedings. This is reflected also in the procedures for imposing sanctions or penalties. They started after a similar time period after detection (8 or 10 months for fraudulent and non-fraudulent irregularities, respectively), but then it took, on average, one year to close the procedure in case of a non-fraudulent irregularity and nearly two years in case of a fraudulent irregularity. This may be due to overlaps with the penal procedure.
Figure CP7 shows the average times for the irregularities referring to PP 2014-2020 (Cohesion and Fisheries policies). These average times were shorter than the ones related to PP 2007-2013. However, it should be considered that these durations are based on much less cases and that irregularities that are more craftily hidden or that are more difficult to investigate will probably add as time passes, pushing these averages up. The average times in Figure CP7 are similar to those in Figure CP8, which refers to the cases related to PP 2007-13 that had been reported after a comparable period of time from the start of the programming period.
4.4.2.Detection of irregularities reported as fraudulent by Member State
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; fourteen (14) Member States reported less than 30 potentially fraudulent irregularities; Three (3) countries reported between 30 and 60; three (3) Member States between 60 and 90; seven (7) more than 90.
Poland, Romania and Germany are the three countries which have reported the highest numbers.
Map CP4 shows the geographic distribution of detections related to the current PP 2014-2020. Twenty (20) Member States have already reported at least one irregularity as fraudulent.
Map CP5 refers to the irregularities that had been reported after a comparable period of time from the start of the programming period 2007-13. It is too early to draw any conclusion. However, it is noticeble the decrease in the number of irregularites reported as fraudulent by Germany and the increase of those reported by Poland, Hungary and Slovakia.
For PP 2007-2013, Map CP3 suggests that the concentration of reporting of irregularities in certain Member States could go beyond what could be expected on the basis of the distribution of payments related to the cohesion and fisheries policies among Member States. Also the analysis of the irregularities that affected the priorities 'Tourism' and 'Environment protection and risk prevention' suggests that the majority of irregularities and financial amounts in these domains were reported by very few Member States (see Section 4.2.2.3.).
Graphs CP18 help assessing the level of concentration. Respectively for fraudulent and non-fraudulent irregularities, Graphs CP18a and CP18b show the cumulative percentage distribution of the number of cases and related financial amounts involved in relation to cohesion and fisheries policies. The Member States are sorted on the basis of the number of irregularities reported.
Graph CP18a shows that the first three Member States (Poland, Romania and Germany) reported slightly more than 40% of all fraudulent irregularities related to cohesion and fisheries, while they received a little more that 30% of the payments. The same percentages related to non-fraudulent irregularities were a little higher (about 50% and 40%, respectively). While Poland was still among the Member State with the highest number of cases reported, Spain and Czech Republic ranked first and third.
In general, the cumulative distributions of number of cases and financial amounts rose fast - which points to concentration of detections in a limited number of Member States - and did not overlap with the cumulative distribution of payments related to cohesion and fisheries – which points to the fact that the aforementioned concentration is not fully explained by the share of payments received. However, the rise of the cumulative distributions of number of cases and financial amounts is smoother than for agriculture (see Sections 3.4.3.1-3.4.3.3) and the distance from cumulative distribution of payments looks smaller (see also below), in particular for non-fraudulent irregularities. To better assess the contribution of each Member State to these patterns, Graph CP18c and CP18d present the individual shares of number of cases, financial amounts involved and payments, respectively for fraudulent and non-fraudulent irregularities.
It seems that the concentration of detections is not fully explained by the distribution of payments during the programming period 2007-2013, but this was less evident than in agriculture (during the period 2014-2018). Graphs CP19 and CP20 are based on an overall measure of the distance between the distribution of detections in different Member States and the distribution of payments received by the Member States in the same period. They confirm that the distance for cohesion and fisheries is smaller, especially with reference to fraudulent irregularities. This may suggest that approaches of Member States to the use of criminal law to protect the EU budget might be more homogeneous in the cohesion and fisheries policies than in the agriculture domains.
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 (see Table CP 27).
The FDR is the highest for Slovakia and Romania, above 1%. Other Member States (Czech Republic, Latvia, Poland, Portugal and Slovenia) 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.
Table CP28 shows data about fraud detection in the MS with reference to the ongoing PP 2014-2020. These data are expected to change as implementation progresses. If the trend of the previous PP is confirmed, most of the fraudulent irregularities are still to be detected. This will be counterbalanced by the growing amounts of payments to the Member States. It is too early to draw any conclusion and the FDR in Table CP28 can not be directly compared with those in Table CP27, but Section 4.1.3 already contains a preliminary comparison between PP 2007-2013 and PP 2014-2020.
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 (see Table CP 29).
The IDR is the highest for Slovakia (more than 10%) and for Czech Republic, Spain and Greece (between 3% 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.
Table CP30 shows data about fraud detection in the MS with reference to the ongoing PP 2014-2020. These data are expected to change as implementation progresses. If the trend of the previous PP is confirmed, most of the fraudulent irregularities are still to be detected. This will be counterbalanced by the growing amounts of payments to the Member States. It is to early to draw any conclusion and the IDR in Table CP30 can not be directly compared with those in Table CP29, but Section 4.1.3 already contains a preliminary comparison between PP 2007-2013 and PP 2014-2020.
4.4.5.Ratio of established fraud (programming period 2007-13)
Table CP31 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 2018 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 CP31 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 2018. 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 17%, increasing from 16% of 2017. The dismissal ratio is 15%. This means that the number of cases that had been reported during 2009-2013 that were still classified as fraudulent at the end of 2018 has decreased by 15% from the end of 2013. This decrease may be due to cases that have been cancelled or that have been re-classified as non-fraudulent, which justify taking this measure as a dismissal ratio. However, it must be considered that between 2014 and 2018, a number of cases that had initially been classifed as non-fraudulent may have been re-classified as fraudulent, contributing to compensate at least part of the decrease. If these cases were not considered in the calculation, the dismissal ratio would be higher. Focusing on the cases that had been reported during 2009-2013 and that were still classified as fraudulent at the end of 2018 (including irregularities initially classified as non-fraudulent and then re-classified as fraudulent), 17% of them are considered as established fraud (ratio of established fraud).
If one considers exclusively the “decisions” (established + dismissed) of the 208 decided cases (102 established fraud and 106 dismissals), 49% is the ‘conviction rate’ and 51% the ‘dismissal rate’.
4.5 Other shared management Funds
There are other funds used under shared management. Table CP32 provides an overview of all the irregularities and related financial amounts that have been reported by the Member States up to 2018 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.
EUROPEAN COMMISSION
Brussels, 11.10.2019
SWD(2019) 365 final
COMMISSION STAFF WORKING DOCUMENT
Statistical evaluation of irregularities reported for 2018: 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
30th Annual Report on the Protection of the European Union's financial interests - Fight against fraud - 2018
{COM(2019) 444 final} - {SWD(2019) 361 final} - {SWD(2019) 362 final} - {SWD(2019) 363 final} - {SWD(2019) 364 final}
Contents
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 2018
5.5.1.
Pre-Accession Assistance (PAA)
5.5.2.
Instrument for Pre-Accession (IPA)
5.5.3.
Instrument for Pre-Accession (IPA II)
6.
Direct Management
6.1. Introduction
6.2. General analysis
6.2.1. Five year analysis 2014-2018
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
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 Republic of North Macedonia, Montenegro, Serbia and Turkey. Potential candidate countries are Bosnia and Herzegovina and Kosovo.
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, Assistance for reconstruction, development and stabilisation for potential candidate countries (
CARDS
) and Transition facility.
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 Republic of North Macedonia, 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.
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.
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 EC 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 2018 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, in 2018, non-fradulent irregularities were not reported. However, the irregularities reported as fraudulent increased.
In the past five years, most of the fraudulent irregularities (87%, in terms of number, and 92%, in terms of financial amount) were reported by Romania. Most of the non-fraudulent irregularities were reported by Romania and Bulgaria (93%, in terms of number, and 99%, in terms of financial amount). In relation to the distribution of irregularities according to funds, both the highest number (50%) and financial amounts (47%) related to SAPARD. PHARE was also affected by a significant share of the reported irregularities (40%), while ISPA recorded by far the highest average financial amout per irregularity (sevent times higher than the one related to the SAPARD cases)
5.4.2.Instrument for Pre-Accession (IPA I)
Since 2014, the trend of IPA reporting (financial framework 2007-13) has begun to develop in an upward curve, both in terms of number of irregularities and involved amounts. 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 2014. The number of irregularities not reported as fraudulent jumped to a new level in 2014 and then continued to grow 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 2014, before decreasing in 2018, despite the still increasing number of irregularities. Similarly to what happened for the irregularities not reported as fraudulent, the number of irregularities reported as fraudulent shifted upwards, but in 2015, and then continued to increase. The financial amounts experienced fluctuations that did not strictly follow changes in numbers. In 2017, the highest financial amounts were recorded (since 2014).
During the last five years, the highest number of reported irregularities was communicated by Turkey (57%), Bulgaria and Croatia. Most of the financial amounts (90%) were involved in irregularities reported by Turkey. When focusing on fraudulent irregularities, Turkey was still the Countries reporting most of the irregularities (73%) and financial amounts (89%). 15% of the irregularities were repoted by Serbia. The highest number of irregularities was recorded in relation to IPARD (37%) and Cross-Border Cooperation (31%). IPARD recorded by far the highest financial amounts (66% of the total).
5.5.Specific analysis – Financial year 2018
5.5.1.Pre-Accession Assistance (PAA)
In 2018, four irregularities were reported as fraudulent by Romania and Turkey, as shown in Table PA3. No irregularities were reported as non-fraudulent.
These irregularities affected in particular TIPAA, to which most of the financial amounts were related.
5.5.2.Instrument for Pre-Accession (IPA)
In relation to IPA I (2007-13), there were 13 irregularities reported as fraudulent in 2018, for an overall financial impact of about EUR 1.2 million. Tables PA5 and PA6 show, respectively, the breakdown per country and per component.
In 2018, Turkey was the country reporting the highest number of irregularities and the related financial amounts. Concerning the irregularities reported as fraudulent, 10 out of these 13 cases were notified by Turkey.
Rural Development programmes accounted for the highest number of cases (45%) and, even more, financial amounts involved (69%).
Concerning the modus operandi, the most frequent category of irregularity refers to 'Ethics and integrity' (not in combination with other categories) and most of these cases are not reported as fraudulent. This category includes conflict of interest and corruption, but the cases detected have been reported using a residual code 'Other'.
5.5.3.Instrument for Pre-Accession (IPA II)
For the programming period 2014-2020, the first irregularity was detect in 2017 by Turkey and reported as fraudulent.
In 2018, reporting accelerated with 17 irregularities (see Table PA7). 10 of these irregularities were reported by Turkey and Serbia, including all irregularities reported as fraudulent. Bulgaria nearly completed the picture with 5 irregularities, all reported as not fraudulent.
As shown by Table PA8, most of these irregularities are evenly shared among the Cross Border Co-operation programmes (reported by Bulgaria and Serbia) and rural development (mostly reported by Turkey).
6.Direct Management
6.1. Introduction
This chapter contains a descriptive analysis of the data on recovery orders issued by Commission services in relation to expenditures managed under ‘direct management’ mode, which is one of the three implementation modes the Commission can use to implement the budget.
According to the Financial Regulation, the Commission implements the budget directly (‘direct management’) as set out in Articles 125 to 153, by its departments, including its staff in the Union delegations under the authority of their respective Head of delegation, in accordance with Article 60(2), or through executive agencies as referred to in Article 69.
For the financial year 2018, a total of EUR 20 825 million has been disbursed under the ‘direct management’ mode. Table DM1 presents the actual payments made in the financial year 2018 for the policy areas under ‘direct management’.
Table DM1 – Payments made in financial year 2018 per policy area
6.2. General analysis
For the financial year 2018, the Commission services registered 1 623 recovery items in ABAC that were qualified as irregularities for a total financial value EUR 73.77 million. Among these recovery items, 44 have been reported as fraudulent, involving EUR 6.17 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 2014-2018
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 2014 and 2018, the average number of recovery items qualified as ‘irregularities reported as fraudulent’ was 57. 2015 was a year when less such recovery items were registered with lower corresponding recovery amounts. The ratio between the amounts related to ‘irregularities reported as fraudulent’ and relative expenditure is very small, it remains close to zero (0.036%) 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 2014-2018
With regard to ‘irregularities not reported as fraudulent’ the average number of recovery items registered per year is 1 718. The figure for 2018 fits in the slightly decreasing five-year trend, which was interrupted only in 2015 (see table DM3).
Table DM3 – Irregularities not reported as fraudulent and related amounts, financial years 2014-2018
Between 2014 and 2018, there were all together 8 590 registered recovery items qualified as ‘irregularities not reported as fraudulent’, with an aggregate recovery amount of EUR 389.76 million.
The ratio between the aggregate irregular amounts corresponding to the recovery items (classified as ‘irregularities not reported as fraudulent’ between 2014 and 2018) and the reference figure of the related expenditure is about half a percent point (0.440%). This ratio has been stable since 2016 (around 0,3-0,4%).
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 policy areas for year 2018.
Table DM4 – Irregularities reported by policy areas and related amounts, 2018
In the financial year 2018, the highest numbers of recovery items qualified as 'irregularities not reported as fraudulent' were recorded in the ‘Communications networks, content and technology’ budget area (316). This was also the policy field where the highest irregular amounts were registered (EUR 13.99 million). It was followed by ‘Research and innovation’ with the second highest number of recovery items (309) and related financial amount (EUR 11.68 million). The third policy area, both in terms of number of non-fraudulent irregularities and related financial amounts, is ‘International cooperation and development' (EUR 9.41 million). These three policy areas account for 52% of the overall irregular recovery amounts for the year 2018.
With reference to ‘irregularities reported as fraudulent’, there were 44 recovery items registered. Half of them concerned the budget area ‘Communications networks, content and technology’ (22 items), followed by ‘Education and Culture’ (6 items) and ‘Research and innovation’ (5 items).
The total related irregular amounts were EUR 6.17 million, of which one third is referred to the policy area ‘Communications networks, content and technology’ (EUR 2.04 million).
The five-year perspective of irregularities regarding the policy fields is presented hereunder in table DM5.
Table DM5 – Irregularities reported by policy areas and related amounts, financial years 2014-2018
Over a five-year period, it is again in the ‘Communications networks, content and technology’ policy field, where the highest aggregate recovery amounts (EUR 18.53 million) were recorded in relation to ‘irregularities reported as fraudulent’ (more than half of the total amounts). It is followed at a distance by the policy areas ‘Education and culture’ (EUR 3.81 million) and ‘Research and innovation’ (EUR 3.17 million).
During the last five years, the highest aggregate recovery amounts related to ‘irregularities not reported as fraudulent’ were recorded in the policy area ‘Research and innovation’ (EUR 80.45 million). It was followed by ‘Mobility and transport’ (EUR 65.21 million) and ‘Communications networks, content and technology’ (EUR 57.31 million). These three policy areas accounted for more than half (52%) of the total recovery amounts related to ‘irregularities not reported as fraudulent’ over the past five years. Compared to the overall payments made during the same period for all fields, the irregularity rate remained very low (on average 0.440%+0.036% = 0.476%).
6.3.2. Recoveries according to legal entity residence
For the last five years, 86% of the total number of recovery items and 88% of 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 72% of these irregularities and for 70% 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: 91% of the total number of recovery items and 94% of the corresponding recovery amounts concerned a legal entity residing in an EU country, and in 82% of these cases and 83% 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, 2014-2018
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, 2014-2018
Regarding the ‘irregularities reported as fraudulent’, ‘OLAF’ has been marked as the source of detection in relation to 56% of recovery items corresponding to 78% of total recovery amounts. Meanwhile ‘Ex-post controls’ was the source of detection of another 38% of this type of recovery items corresponding to another 19% of recovery amounts.
85% of ‘irregularities not reported as fraudulent’ were detected through Commission controls (ex-ante and ex-post controls).
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’, the irregularity type ‘Amount ineligible’ was the most frequent in the past five years, followed by ‘Documents missing’. In relation to ‘irregularities not reported as fraudulent’, ‘Amount ineligible’ was the most frequent irregularity type, followed by ‘Under-performance/Non-performance’ and ‘Documents missing’. Table DM8 provides the full picture regarding the frequency of each type over the last five years.
Table DM8 – Types of irregularity, 2014-2018
The figures for irregularity type frequency are stable and have been following the same pattern during 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 to the beneficiary.
For the recovery orders issued between 2014 and 2018, 58% of the total irregular amounts have already been recovered. There are differences between the recovery rates depending on the qualification. The recovery rate for ‘irregularities reported as fraudulent’ (28%) remains well below the one calculated for ‘irregularities not reported as fraudulent’ (60%).
COUNTRY FACTSHEETS
Belgium - Belgique/België
Bulgaria - България
Czech Republic - Česká republika
Denmark - Danmark
Estonia - Eesti
Ireland - Éire
Croatia - Hrvatska
Italy - Italia
Cyprus - Κύπρος
Latvia - Latvija
Lithuania - Lietuva
Luxembourg
Hungary - Magyarország
Malta
Austria - Österreich
Poland - Polska
Portugal
Romania - România
Slovenia - Slovenija
Slovakia - Slovensko
Finland – Suomi-Finland
Sweden - Sverige
United Kingdom
ANNEXES
Annex 1
|
|
TOR: Total number of fraudulent and non-fraudulent cases discovered with the related estimated and established amount 2014-2018
|
|
MS
|
2014
|
2015
|
2016
|
2017
|
2018
|
|
|
N
|
EUR
|
N
|
EUR
|
N
|
EUR
|
N
|
EUR
|
N
|
EUR
|
|
BE
|
147
|
19.048.837
|
253
|
15.381.576
|
213
|
14.800.873
|
223
|
24.965.787
|
256
|
42.770.603
|
|
BG
|
28
|
634.160
|
27
|
745.534
|
13
|
343.818
|
20
|
1.258.312
|
6
|
601.490
|
|
CZ
|
83
|
12.327.345
|
72
|
3.674.130
|
82
|
5.727.119
|
89
|
8.355.714
|
94
|
4.696.506
|
|
DK
|
71
|
5.336.711
|
91
|
6.222.118
|
79
|
12.258.546
|
58
|
2.416.910
|
54
|
7.401.412
|
|
DE
|
1.781
|
95.550.296
|
2.136
|
140.563.082
|
1.853
|
86.145.500
|
2.000
|
108.871.648
|
1.509
|
107.827.233
|
|
EE
|
8
|
249.167
|
9
|
247.557
|
9
|
1.303.483
|
5
|
322.079
|
9
|
677.107
|
|
IE
|
28
|
4.313.814
|
32
|
3.340.624
|
35
|
6.402.932
|
35
|
3.189.457
|
36
|
4.615.501
|
|
EL
|
48
|
12.188.688
|
57
|
16.692.582
|
46
|
16.496.661
|
43
|
14.630.570
|
30
|
6.480.744
|
|
ES
|
413
|
47.411.444
|
320
|
24.817.480
|
303
|
45.263.054
|
264
|
48.337.739
|
314
|
33.934.611
|
|
FR
|
426
|
47.886.717
|
382
|
28.690.422
|
346
|
48.020.494
|
299
|
28.037.557
|
280
|
96.151.343
|
|
HR
|
10
|
647.638
|
14
|
975.020
|
17
|
609.108
|
15
|
1.094.608
|
16
|
1.102.842
|
|
IT
|
155
|
62.036.016
|
152
|
12.771.224
|
112
|
13.805.644
|
145
|
18.025.093
|
104
|
9.827.329
|
|
CY
|
11
|
162.729
|
4
|
127.072
|
8
|
332.446
|
5
|
128.966
|
4
|
70.088
|
|
LV
|
26
|
1.717.375
|
30
|
1.995.004
|
32
|
4.056.870
|
12
|
555.952
|
18
|
1.072.073
|
|
LT
|
49
|
2.892.165
|
47
|
1.325.639
|
26
|
915.350
|
57
|
2.339.517
|
45
|
5.125.206
|
|
LU
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
|
HU
|
87
|
1.419.634
|
27
|
1.213.969
|
16
|
4.121.423
|
26
|
6.294.351
|
11
|
1.238.194
|
|
MT
|
4
|
1.466.945
|
5
|
623.612
|
2
|
320.682
|
2
|
366.319
|
0
|
0
|
|
NL
|
393
|
42.787.270
|
462
|
111.187.120
|
523
|
132.231.615
|
450
|
75.625.235
|
503
|
130.744.804
|
|
AT
|
81
|
6.389.271
|
75
|
3.909.658
|
61
|
15.345.478
|
56
|
7.365.832
|
47
|
2.184.744
|
|
PL
|
213
|
10.611.911
|
129
|
5.053.147
|
166
|
6.974.203
|
99
|
3.265.078
|
149
|
8.193.145
|
|
PT
|
58
|
3.652.681
|
22
|
3.764.190
|
17
|
6.609.241
|
38
|
5.457.304
|
37
|
9.398.614
|
|
RO
|
75
|
7.096.470
|
93
|
8.008.639
|
57
|
5.531.161
|
32
|
3.028.787
|
25
|
2.425.741
|
|
SI
|
19
|
1.201.576
|
12
|
446.511
|
1
|
25.222
|
12
|
491.867
|
13
|
969.765
|
|
SK
|
35
|
1.753.766
|
10
|
605.925
|
18
|
1.026.172
|
11
|
756.807
|
11
|
550.903
|
|
FI
|
35
|
1.446.295
|
38
|
1.739.021
|
40
|
2.385.846
|
31
|
2.058.548
|
32
|
2.945.510
|
|
SE
|
87
|
4.066.009
|
79
|
3.000.495
|
101
|
6.022.090
|
169
|
10.737.269
|
151
|
5.963.715
|
|
UK
|
1.198
|
69.461.143
|
971
|
45.162.720
|
835
|
83.372.748
|
811
|
99.691.527
|
809
|
127.971.890
|
|
Total
|
5.569
|
463.756.072
|
5.549
|
442.284.072
|
5.011
|
520.447.778
|
5.007
|
477.668.832
|
4.563
|
614.941.111
|
Annex 2
|
|
TOR: Total number of fraudulent cases discovered with the related estimated and established amount 2014-2018
|
|
MS
|
2014
|
2015
|
2016
|
2017
|
2018
|
|
|
N
|
EUR
|
N
|
EUR
|
N
|
EUR
|
N
|
EUR
|
N
|
EUR
|
|
BE
|
26
|
13.145.504
|
45
|
7.486.346
|
41
|
8.952.164
|
28
|
14.561.421
|
39
|
35.939.701
|
|
BG
|
24
|
497.380
|
23
|
648.683
|
11
|
331.471
|
19
|
1.192.724
|
5
|
542.270
|
|
CZ
|
0
|
0
|
2
|
47.149
|
2
|
148.057
|
0
|
0
|
0
|
0
|
|
DK
|
2
|
696.296
|
6
|
2.681.773
|
5
|
8.555.495
|
1
|
87.789
|
2
|
167.285
|
|
DE
|
143
|
13.756.734
|
159
|
29.702.791
|
117
|
5.423.401
|
59
|
7.285.945
|
95
|
18.731.575
|
|
EE
|
2
|
108.304
|
5
|
134.899
|
4
|
71.272
|
4
|
310.930
|
4
|
568.102
|
|
IE
|
4
|
2.249.080
|
8
|
1.544.668
|
6
|
1.176.186
|
1
|
33.992
|
10
|
1.497.154
|
|
EL
|
35
|
9.953.507
|
34
|
13.390.124
|
38
|
7.897.411
|
33
|
14.329.015
|
21
|
5.205.677
|
|
ES
|
122
|
31.249.790
|
75
|
4.956.829
|
50
|
3.198.014
|
34
|
3.162.346
|
44
|
3.906.486
|
|
FR
|
135
|
33.844.347
|
99
|
14.865.623
|
92
|
25.954.197
|
98
|
13.221.533
|
60
|
80.276.451
|
|
HR
|
8
|
513.850
|
5
|
249.286
|
5
|
342.904
|
8
|
831.921
|
12
|
1.028.297
|
|
IT
|
51
|
54.349.363
|
40
|
5.553.956
|
22
|
6.916.737
|
23
|
1.947.383
|
38
|
5.800.213
|
|
CY
|
2
|
22.192
|
3
|
112.709
|
7
|
332.446
|
4
|
118.402
|
1
|
12.878
|
|
LV
|
19
|
866.731
|
18
|
1.616.073
|
16
|
938.871
|
8
|
359.109
|
7
|
779.838
|
|
LT
|
14
|
712.907
|
17
|
559.196
|
10
|
266.102
|
38
|
1.332.822
|
20
|
1.900.284
|
|
LU
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
|
HU
|
8
|
185.714
|
5
|
180.657
|
2
|
86.787
|
4
|
332.664
|
1
|
771.268
|
|
MT
|
3
|
1.391.777
|
1
|
18.961
|
2
|
320.682
|
2
|
366.319
|
0
|
0
|
|
NL
|
7
|
414.169
|
3
|
1.596.447
|
9
|
515.657
|
10
|
3.358.199
|
18
|
2.365.801
|
|
AT
|
23
|
3.627.369
|
10
|
1.001.186
|
14
|
5.716.261
|
7
|
5.654.247
|
3
|
87.272
|
|
PL
|
37
|
3.433.335
|
59
|
1.751.606
|
92
|
2.977.357
|
52
|
1.858.778
|
41
|
2.239.388
|
|
PT
|
4
|
454.899
|
7
|
3.214.944
|
1
|
5.299.535
|
6
|
839.593
|
3
|
1.604.104
|
|
RO
|
14
|
366.332
|
21
|
990.209
|
16
|
2.743.678
|
9
|
297.917
|
3
|
50.386
|
|
SI
|
13
|
1.067.985
|
3
|
139.295
|
0
|
0
|
4
|
171.727
|
8
|
405.956
|
|
SK
|
3
|
256.714
|
3
|
117.282
|
3
|
707.196
|
0
|
0
|
5
|
115.016
|
|
FI
|
3
|
74.840
|
6
|
412.415
|
6
|
119.457
|
4
|
83.383
|
5
|
267.571
|
|
SE
|
3
|
214.245
|
0
|
0
|
2
|
92.247
|
4
|
4.328.446
|
1
|
33.964
|
|
UK
|
44
|
2.329.868
|
42
|
990.109
|
9
|
299.933
|
9
|
482.705
|
27
|
937.725
|
|
Total
|
749
|
175.783.234
|
699
|
93.963.217
|
582
|
89.383.521
|
469
|
76.549.311
|
473
|
165.234.661
|
Annex 3
|
|
TOR: Total number of non-fraudulent cases with the related estimated and established amount - 2014-2018
|
|
MS
|
2014
|
2015
|
2016
|
2017
|
2018
|
|
|
N
|
EUR
|
N
|
EUR
|
N
|
EUR
|
N
|
EUR
|
N
|
EUR
|
|
BE
|
121
|
5.903.333
|
208
|
7.895.230
|
172
|
5.848.708
|
195
|
10.404.367
|
217
|
6.830.902
|
|
BG
|
4
|
136.779
|
4
|
96.851
|
2
|
12.347
|
1
|
65.587
|
1
|
59.220
|
|
CZ
|
83
|
12.327.345
|
70
|
3.626.981
|
80
|
5.579.062
|
89
|
8.355.714
|
94
|
4.696.506
|
|
DK
|
69
|
4.640.414
|
85
|
3.540.345
|
74
|
3.703.051
|
57
|
2.329.121
|
52
|
7.234.128
|
|
DE
|
1.638
|
81.793.561
|
1.977
|
110.860.291
|
1.736
|
80.722.099
|
1.941
|
101.585.704
|
1.414
|
89.095.658
|
|
EE
|
6
|
140.863
|
4
|
112.658
|
5
|
1.232.211
|
1
|
11.149
|
5
|
109.005
|
|
IE
|
24
|
2.064.734
|
24
|
1.795.956
|
29
|
5.226.746
|
34
|
3.155.465
|
26
|
3.118.347
|
|
EL
|
13
|
2.235.181
|
23
|
3.302.458
|
8
|
8.599.250
|
10
|
301.554
|
9
|
1.275.067
|
|
ES
|
291
|
16.161.654
|
245
|
19.860.651
|
253
|
42.065.040
|
230
|
45.175.393
|
270
|
30.028.125
|
|
FR
|
291
|
14.042.370
|
283
|
13.824.800
|
254
|
22.066.297
|
201
|
14.816.024
|
220
|
15.874.892
|
|
HR
|
2
|
133.787
|
9
|
725.734
|
12
|
266.204
|
7
|
262.687
|
4
|
74.545
|
|
IT
|
104
|
7.686.653
|
112
|
7.217.268
|
90
|
6.888.907
|
122
|
16.077.710
|
66
|
4.027.116
|
|
CY
|
9
|
140.537
|
1
|
14.363
|
1
|
0
|
1
|
10.564
|
3
|
57.210
|
|
LV
|
7
|
850.644
|
12
|
378.930
|
16
|
3.117.998
|
4
|
196.843
|
11
|
292.235
|
|
LT
|
35
|
2.179.258
|
30
|
766.443
|
16
|
649.248
|
19
|
1.006.695
|
25
|
3.224.922
|
|
LU
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
|
HU
|
79
|
1.233.920
|
22
|
1.033.311
|
14
|
4.034.636
|
22
|
5.961.687
|
10
|
466.926
|
|
MT
|
1
|
75.168
|
4
|
604.651
|
0
|
0
|
0
|
0
|
0
|
0
|
|
NL
|
386
|
42.373.101
|
459
|
109.590.673
|
514
|
131.715.958
|
440
|
72.267.036
|
485
|
128.379.003
|
|
AT
|
58
|
2.761.902
|
65
|
2.908.472
|
47
|
9.629.217
|
49
|
1.711.585
|
44
|
2.097.472
|
|
PL
|
176
|
7.178.576
|
70
|
3.301.541
|
74
|
3.996.846
|
47
|
1.406.300
|
108
|
5.953.757
|
|
PT
|
54
|
3.197.782
|
15
|
549.246
|
16
|
1.309.706
|
32
|
4.617.711
|
34
|
7.794.511
|
|
RO
|
61
|
6.730.138
|
72
|
7.018.430
|
41
|
2.787.483
|
23
|
2.730.870
|
22
|
2.375.356
|
|
SI
|
6
|
133.591
|
9
|
307.216
|
1
|
25.222
|
8
|
320.139
|
5
|
563.809
|
|
SK
|
32
|
1.497.052
|
7
|
488.643
|
15
|
318.976
|
11
|
756.807
|
6
|
435.887
|
|
FI
|
32
|
1.371.455
|
32
|
1.326.606
|
34
|
2.266.388
|
27
|
1.975.165
|
27
|
2.677.938
|
|
SE
|
84
|
3.851.764
|
79
|
3.000.495
|
99
|
5.929.843
|
165
|
6.408.823
|
150
|
5.929.751
|
|
UK
|
1.154
|
67.131.275
|
929
|
44.172.610
|
826
|
83.072.815
|
802
|
99.208.822
|
782
|
127.034.165
|
|
Total
|
4.820
|
287.972.838
|
4.850
|
348.320.855
|
4.429
|
431.064.257
|
4.538
|
401.119.521
|
4.090
|
449.706.450
|
Annex 4
|
|
TOR: Percentage of the financial impact of OWNRES cases to the collected and made available TOR (gross) in 2018 per Member State
|
|
MS
|
Gross amount TOR collected (A account)
|
All
|
Fraudulent
|
Non-fraudulent
|
|
|
|
OWNRES established and estimated amount
|
Percentage OWNRES/ gross TOR
|
OWNRES established and estimated amount
|
Percentage OWNRES/ gross TOR
|
OWNRES established and estimated amount
|
Percentage OWNRES/ gross TOR
|
|
|
EUR
|
EUR
|
%
|
EUR
|
%
|
EUR
|
%
|
|
BE
|
2.605.160.504
|
42.770.603
|
1,64%
|
35.939.701
|
1,38%
|
6.830.902
|
0,26%
|
|
BG
|
120.546.317
|
601.490
|
0,50%
|
542.270
|
0,45%
|
59.220
|
0,05%
|
|
CZ
|
333.294.541
|
4.696.506
|
1,41%
|
0
|
0,00%
|
4.696.506
|
1,41%
|
|
DK
|
421.859.377
|
7.401.412
|
1,75%
|
167.285
|
0,04%
|
7.234.128
|
1,71%
|
|
DE
|
4.999.734.214
|
107.827.233
|
2,16%
|
18.731.575
|
0,37%
|
89.095.658
|
1,78%
|
|
EE
|
41.242.082
|
677.107
|
1,64%
|
568.102
|
1,38%
|
109.005
|
0,26%
|
|
IE
|
356.401.517
|
4.615.501
|
1,30%
|
1.497.154
|
0,42%
|
3.118.347
|
0,87%
|
|
EL
|
225.288.406
|
6.480.744
|
2,88%
|
5.205.677
|
2,31%
|
1.275.067
|
0,57%
|
|
ES
|
1.910.119.170
|
33.934.611
|
1,78%
|
3.906.486
|
0,20%
|
30.028.125
|
1,57%
|
|
FR
|
2.058.694.268
|
96.151.343
|
4,67%
|
80.276.451
|
3,90%
|
15.874.892
|
0,77%
|
|
HR
|
45.852.052
|
1.102.842
|
2,41%
|
1.028.297
|
2,24%
|
74.545
|
0,16%
|
|
IT
|
2.271.237.062
|
9.827.329
|
0,43%
|
5.800.213
|
0,26%
|
4.027.116
|
0,18%
|
|
CY
|
28.829.016
|
70.088
|
0,24%
|
12.878
|
0,04%
|
57.210
|
0,20%
|
|
LV
|
53.312.705
|
1.072.073
|
2,01%
|
779.838
|
1,46%
|
292.235
|
0,55%
|
|
LT
|
114.101.823
|
5.125.206
|
4,49%
|
1.900.284
|
1,67%
|
3.224.922
|
2,83%
|
|
LU
|
25.125.758
|
0
|
0,00%
|
0
|
0,00%
|
0
|
0,00%
|
|
HU
|
241.361.284
|
1.238.194
|
0,51%
|
771.268
|
0,32%
|
466.926
|
0,19%
|
|
MT
|
16.065.932
|
0
|
0,00%
|
0
|
0,00%
|
0
|
0,00%
|
|
NL
|
3.128.684.495
|
130.744.804
|
4,18%
|
2.365.801
|
0,08%
|
128.379.003
|
4,10%
|
|
AT
|
262.092.022
|
2.184.744
|
0,83%
|
87.272
|
0,03%
|
2.097.472
|
0,80%
|
|
PL
|
918.734.486
|
8.193.145
|
0,89%
|
2.239.388
|
0,24%
|
5.953.757
|
0,65%
|
|
PT
|
219.866.963
|
9.398.614
|
4,27%
|
1.604.104
|
0,73%
|
7.794.511
|
3,55%
|
|
RO
|
219.780.701
|
2.425.741
|
1,10%
|
50.386
|
0,02%
|
2.375.356
|
1,08%
|
|
SI
|
87.993.071
|
969.765
|
1,10%
|
405.956
|
0,46%
|
563.809
|
0,64%
|
|
SK
|
116.727.140
|
550.903
|
0,47%
|
115.016
|
0,10%
|
435.887
|
0,37%
|
|
FI
|
172.748.885
|
2.945.510
|
1,71%
|
267.571
|
0,15%
|
2.677.938
|
1,55%
|
|
SE
|
617.626.338
|
5.963.715
|
0,97%
|
33.964
|
0,01%
|
5.929.751
|
0,96%
|
|
UK
|
3.677.057.294
|
127.971.890
|
3,48%
|
937.725
|
0,03%
|
127.034.165
|
3,45%
|
|
Total
|
25.289.537.421
|
614.941.111
|
2,43%
|
165.234.661
|
0,65%
|
449.706.450
|
1,78%
|
Annex 5
|
|
TOR: Recovery rates (RR) per cut-off date
|
|
MS
|
2017
|
2018
|
|
|
Established amount
|
Recovered amount
|
RR
|
Established amount
|
Recovered amount
|
RR
|
|
|
EUR
|
EUR
|
%
|
EUR
|
EUR
|
%
|
|
|
1
|
2
|
3=2/1
|
1
|
2
|
3=2/1
|
|
BE
|
16.629.676
|
11.184.943
|
67%
|
22.044.258
|
11.300.647
|
51%
|
|
BG
|
1.258.312
|
132.243
|
11%
|
601.490
|
97.201
|
16%
|
|
CZ
|
8.355.714
|
4.819.621
|
58%
|
4.696.506
|
4.467.278
|
95%
|
|
DK
|
2.416.910
|
2.221.505
|
92%
|
7.401.412
|
6.131.166
|
83%
|
|
DE
|
108.871.648
|
94.986.635
|
87%
|
107.827.233
|
84.937.555
|
79%
|
|
EE
|
322.079
|
11.149
|
3%
|
677.107
|
89.986
|
13%
|
|
IE
|
3.155.465
|
3.080.086
|
98%
|
3.118.347
|
1.933.034
|
62%
|
|
EL
|
8.381.459
|
212.608
|
3%
|
4.433.723
|
278.332
|
6%
|
|
ES
|
46.695.822
|
13.165.105
|
28%
|
31.762.275
|
22.411.605
|
71%
|
|
FR
|
26.975.788
|
12.968.296
|
48%
|
94.753.921
|
83.959.602
|
89%
|
|
HR
|
1.094.608
|
413.389
|
38%
|
1.102.842
|
530.187
|
48%
|
|
IT
|
17.013.388
|
3.390.795
|
20%
|
8.787.390
|
3.001.627
|
34%
|
|
CY
|
128.966
|
43.302
|
34%
|
70.088
|
57.210
|
82%
|
|
LV
|
555.952
|
51.897
|
9%
|
1.072.073
|
260.684
|
24%
|
|
LT
|
2.339.517
|
425.866
|
18%
|
5.125.206
|
3.181.380
|
62%
|
|
LU
|
0
|
0
|
0%
|
0
|
0
|
0%
|
|
HU
|
6.294.351
|
5.648.656
|
90%
|
1.238.194
|
1.124.657
|
91%
|
|
MT
|
366.319
|
0
|
0%
|
0
|
0
|
0%
|
|
NL
|
74.316.412
|
26.852.677
|
36%
|
129.994.060
|
32.551.628
|
25%
|
|
AT
|
7.365.832
|
6.205.569
|
84%
|
2.184.744
|
1.845.505
|
84%
|
|
PL
|
3.265.078
|
1.343.898
|
41%
|
8.159.660
|
4.047.943
|
50%
|
|
PT
|
4.982.829
|
2.635.890
|
53%
|
9.347.470
|
3.719.205
|
40%
|
|
RO
|
2.876.537
|
1.348.510
|
47%
|
2.396.606
|
788.592
|
33%
|
|
SI
|
491.867
|
491.867
|
100%
|
969.765
|
969.765
|
100%
|
|
SK
|
756.807
|
756.807
|
100%
|
550.903
|
319.131
|
58%
|
|
FI
|
2.058.548
|
1.829.838
|
89%
|
2.945.510
|
2.741.186
|
93%
|
|
SE
|
10.711.486
|
6.285.130
|
59%
|
5.929.751
|
5.735.508
|
97%
|
|
UK
|
99.004.048
|
60.237.766
|
61%
|
127.147.990
|
43.347.909
|
34%
|
|
Total
|
456.685.417
|
260.744.046
|
57%
|
584.338.523
|
319.828.526
|
55%
|
Annex 6
|
|
TOR: Estimated and established amount per customs procedure per Member State 2018
|
|
MS
|
Fraudulent
|
Non-fraudulent
|
|
|
Release for free circulation
|
Transit
|
Customs warehousing
|
Inward processing
|
Other
|
Release for free circulation
|
Transit
|
Customs warehousing
|
Inward processing
|
Other
|
|
BE
|
33.021.865
|
344.723
|
|
16.192
|
2.556.920
|
3.971.961
|
819.259
|
381.246
|
1.531.704
|
126.731
|
|
BG
|
365.918
|
176.352
|
|
|
|
59.220
|
|
|
|
|
|
CZ
|
|
|
|
|
|
4.503.807
|
19.560
|
|
173.139
|
|
|
DK
|
144.120
|
|
23.165
|
|
|
7.135.725
|
|
|
98.402
|
|
|
DE
|
18.698.778
|
|
|
|
32.797
|
69.409.682
|
355.791
|
1.697.423
|
16.490.747
|
1.142.014
|
|
EE
|
|
|
|
|
568.102
|
109.005
|
|
|
|
|
|
IE
|
|
|
|
|
1.497.154
|
2.885.837
|
|
11.383
|
36.788
|
184.339
|
|
EL
|
805.756
|
50.132
|
|
|
4.349.789
|
292.995
|
|
982.072
|
|
|
|
ES
|
3.906.486
|
|
|
|
|
23.334.674
|
|
|
6.675.246
|
18.205
|
|
FR
|
78.445.150
|
22.329
|
14.149
|
251.865
|
1.542.958
|
10.929.267
|
156.734
|
84.754
|
3.753.411
|
950.726
|
|
HR
|
687.979
|
340.317
|
|
|
|
74.545
|
|
|
|
|
|
IT
|
4.808.521
|
991.692
|
|
|
|
2.354.582
|
34.079
|
13.550
|
95.938
|
1.528.967
|
|
CY
|
12.878
|
|
|
|
|
57.210
|
|
|
|
|
|
LV
|
760.830
|
|
|
|
19.008
|
229.964
|
26.501
|
|
34.738
|
1.032
|
|
LT
|
|
47.037
|
|
|
1.853.247
|
3.158.820
|
29.171
|
36.931
|
|
|
|
LU
|
|
|
|
|
|
|
|
|
|
|
|
HU
|
771.268
|
|
|
|
|
466.926
|
|
|
|
|
|
MT
|
|
|
|
|
|
|
|
|
|
|
|
NL
|
1.334.190
|
|
111.419
|
920.192
|
|
105.097.367
|
660.617
|
5.986.970
|
15.700.105
|
933.944
|
|
AT
|
87.272
|
|
|
|
|
1.965.230
|
101.524
|
|
12.718
|
18.000
|
|
PL
|
1.364.489
|
874.899
|
|
|
|
4.634.955
|
1.318.802
|
|
|
|
|
PT
|
1.604.104
|
|
|
|
|
7.794.511
|
|
|
|
|
|
RO
|
21.251
|
|
|
|
29.135
|
2.375.356
|
|
|
|
|
|
SI
|
405.956
|
|
|
|
|
563.809
|
|
|
|
|
|
SK
|
57.484
|
57.532
|
|
|
|
435.887
|
|
|
|
|
|
FI
|
251.085
|
|
16.487
|
|
|
2.555.806
|
10.365
|
|
111.767
|
|
|
SE
|
33.964
|
|
|
|
|
5.257.998
|
141.452
|
363.108
|
105.317
|
61.876
|
|
UK
|
937.725
|
|
|
|
|
105.266.076
|
525.328
|
|
21.242.761
|
|
|
Total
|
148.527.069
|
2.905.014
|
165.220
|
1.188.249
|
12.449.110
|
364.921.215
|
4.199.184
|
9.557.437
|
66.062.781
|
4.965.833
|
Annex 7
|
|
TOR: Method of detection by number of cases per Member State 2018
|
|
MS
|
N
|
Fraudulent
|
Non-fraudulent
|
|
|
|
All
|
Release controls
|
Post-release controls
|
Inspections by anti-fraud services
|
Tax audit
|
Voluntary admission
|
Other
|
All
|
Release controls
|
Post-release controls
|
Inspections by anti-fraud services
|
Tax audit
|
Voluntary admission
|
Other
|
|
BE
|
256
|
39
|
|
1
|
34
|
|
|
4
|
217
|
32
|
152
|
8
|
7
|
6
|
12
|
|
BG
|
6
|
5
|
1
|
3
|
1
|
|
|
|
1
|
|
1
|
|
|
|
|
|
CZ
|
94
|
0
|
|
|
|
|
|
|
94
|
5
|
60
|
1
|
|
27
|
1
|
|
DK
|
54
|
2
|
2
|
|
|
|
|
|
52
|
25
|
19
|
|
|
2
|
6
|
|
DE
|
1.509
|
95
|
|
11
|
81
|
1
|
|
2
|
1.414
|
115
|
623
|
12
|
278
|
363
|
23
|
|
EE
|
9
|
4
|
4
|
|
|
|
|
|
5
|
|
4
|
1
|
|
|
|
|
IE
|
36
|
10
|
|
|
10
|
|
|
|
26
|
3
|
5
|
1
|
11
|
2
|
4
|
|
EL
|
30
|
21
|
8
|
2
|
7
|
|
|
4
|
9
|
|
2
|
7
|
|
|
|
|
ES
|
314
|
44
|
3
|
6
|
28
|
6
|
|
1
|
270
|
99
|
49
|
10
|
75
|
33
|
4
|
|
FR
|
280
|
60
|
27
|
20
|
13
|
|
|
|
220
|
63
|
95
|
39
|
|
23
|
|
|
HR
|
16
|
12
|
4
|
1
|
7
|
|
|
|
4
|
2
|
2
|
|
|
|
|
|
IT
|
104
|
38
|
2
|
4
|
11
|
17
|
4
|
|
66
|
8
|
33
|
9
|
|
11
|
5
|
|
CY
|
4
|
1
|
|
|
|
|
|
1
|
3
|
|
3
|
|
|
|
|
|
LV
|
18
|
7
|
7
|
|
|
|
|
|
11
|
1
|
8
|
|
1
|
1
|
|
|
LT
|
45
|
20
|
|
3
|
17
|
|
|
|
25
|
|
24
|
1
|
|
|
|
|
LU
|
|
0
|
|
|
|
|
|
|
0
|
|
|
|
|
|
|
|
HU
|
11
|
1
|
|
1
|
|
|
|
|
10
|
3
|
7
|
|
|
|
|
|
MT
|
|
0
|
|
|
|
|
|
|
0
|
|
|
|
|
|
|
|
NL
|
503
|
18
|
5
|
10
|
|
|
2
|
1
|
485
|
178
|
250
|
|
|
57
|
|
|
AT
|
47
|
3
|
1
|
1
|
1
|
|
|
|
44
|
3
|
27
|
|
|
8
|
6
|
|
PL
|
149
|
41
|
14
|
25
|
1
|
|
|
1
|
108
|
12
|
79
|
11
|
|
6
|
|
|
PT
|
37
|
3
|
|
1
|
2
|
|
|
|
34
|
7
|
5
|
22
|
|
|
|
|
RO
|
25
|
3
|
1
|
|
2
|
|
|
|
22
|
|
|
22
|
|
|
|
|
SI
|
13
|
8
|
6
|
|
2
|
|
|
|
5
|
3
|
2
|
|
|
|
|
|
SK
|
11
|
5
|
3
|
|
1
|
|
1
|
|
6
|
1
|
2
|
3
|
|
|
|
|
FI
|
32
|
5
|
5
|
|
|
|
|
|
27
|
21
|
1
|
|
|
5
|
|
|
SE
|
151
|
1
|
1
|
|
|
|
|
|
150
|
2
|
107
|
1
|
|
40
|
|
|
UK
|
809
|
27
|
26
|
1
|
|
|
|
|
782
|
3
|
505
|
1
|
|
273
|
|
|
Total
|
4.563
|
473
|
120
|
90
|
218
|
24
|
7
|
14
|
4.090
|
586
|
2.065
|
149
|
372
|
857
|
61
|
Annex 8
|
|
TOR: Method of detection by established and estimated amounts per Member State 2018
|
|
MS
|
ALL
|
Fraudulent
|
Non-fraudulent
|
|
|
|
All
|
Release controls
|
Post-release controls
|
Inspections by anti-fraud services
|
Tax audit
|
Voluntary admission
|
Other
|
All
|
Release controls
|
Post-release controls
|
Inspections by anti-fraud services
|
Tax audit
|
Voluntary admission
|
Other
|
|
BE
|
42.770.603
|
35.939.701
|
|
55.152
|
35.000.383
|
|
|
884.166
|
6.830.902
|
1.283.529
|
2.080.170
|
770.359
|
918.866
|
1.571.027
|
206.951
|
|
BG
|
601.490
|
542.270
|
102.519
|
420.282
|
19.470
|
|
|
|
59.220
|
|
59.220
|
|
|
|
|
|
CZ
|
4.696.506
|
0
|
|
|
|
|
|
|
4.696.506
|
66.084
|
3.542.995
|
24.571
|
|
976.339
|
86.517
|
|
DK
|
7.401.412
|
167.285
|
167.285
|
|
|
|
|
|
7.234.128
|
1.595.050
|
678.584
|
|
|
85.814
|
4.874.680
|
|
DE
|
107.827.233
|
18.731.575
|
|
947.378
|
17.655.517
|
27.257
|
|
101.423
|
89.095.658
|
2.836.590
|
55.461.751
|
494.061
|
13.450.216
|
16.062.648
|
790.391
|
|
EE
|
677.107
|
568.102
|
568.102
|
|
|
|
|
|
109.005
|
|
79.500
|
29.506
|
|
|
|
|
IE
|
4.615.501
|
1.497.154
|
|
|
1.497.154
|
|
|
|
3.118.347
|
1.117.561
|
213.138
|
61.195
|
193.605
|
25.777
|
1.507.071
|
|
EL
|
6.480.744
|
5.205.677
|
1.488.575
|
102.060
|
3.269.315
|
|
|
345.727
|
1.275.067
|
|
1.017.585
|
257.482
|
|
|
|
|
ES
|
33.934.611
|
3.906.486
|
773.130
|
305.523
|
2.221.349
|
546.423
|
|
60.061
|
30.028.125
|
6.350.998
|
7.694.292
|
347.996
|
12.140.670
|
3.389.466
|
104.703
|
|
FR
|
96.151.343
|
80.276.451
|
1.739.393
|
76.410.491
|
2.126.567
|
|
|
|
15.874.892
|
1.991.353
|
6.942.752
|
6.424.857
|
|
515.930
|
|
|
HR
|
1.102.842
|
1.028.297
|
524.748
|
75.358
|
428.190
|
|
|
|
74.545
|
15.492
|
59.053
|
|
|
|
|
|
IT
|
9.827.329
|
5.800.213
|
1.032.630
|
117.613
|
434.814
|
3.918.076
|
297.080
|
|
4.027.116
|
407.879
|
2.632.038
|
540.288
|
|
367.481
|
79.429
|
|
CY
|
70.088
|
12.878
|
|
|
|
|
|
12.878
|
57.210
|
|
57.210
|
|
|
|
|
|
LV
|
1.072.073
|
779.838
|
779.838
|
|
|
|
|
|
292.235
|
1.032
|
261.033
|
|
19.790
|
10.381
|
|
|
LT
|
5.125.206
|
1.900.284
|
|
150.623
|
1.749.661
|
|
|
|
3.224.922
|
|
3.201.408
|
23.514
|
|
|
|
|
LU
|
|
0
|
|
|
|
|
|
|
0
|
|
|
|
|
|
|
|
HU
|
1.238.194
|
771.268
|
|
771.268
|
|
|
|
|
466.926
|
180.001
|
286.925
|
|
|
|
|
|
MT
|
|
0
|
|
|
|
|
|
|
0
|
|
|
|
|
|
|
|
NL
|
130.744.804
|
2.365.801
|
63.852
|
1.990.760
|
|
|
199.770
|
111.419
|
128.379.003
|
10.093.459
|
112.580.145
|
|
|
5.705.399
|
|
|
AT
|
2.184.744
|
87.272
|
21.583
|
35.046
|
30.643
|
|
|
|
2.097.472
|
44.661
|
1.280.611
|
|
|
566.508
|
205.693
|
|
PL
|
8.193.145
|
2.239.388
|
1.351.516
|
812.583
|
29.293
|
|
|
45.995
|
5.953.757
|
1.922.496
|
2.965.613
|
853.102
|
|
212.546
|
|
|
PT
|
9.398.614
|
1.604.104
|
|
1.287.255
|
316.848
|
|
|
|
7.794.511
|
125.620
|
131.245
|
7.537.646
|
|
|
|
|
RO
|
2.425.741
|
50.386
|
9.851
|
|
40.535
|
|
|
|
2.375.356
|
|
|
2.375.356
|
|
|
|
|
SI
|
969.765
|
405.956
|
307.307
|
|
98.649
|
|
|
|
563.809
|
528.329
|
35.479
|
|
|
|
|
|
SK
|
550.903
|
115.016
|
57.532
|
|
38.821
|
|
18.664
|
|
435.887
|
10.020
|
27.950
|
397.916
|
|
|
|
|
FI
|
2.945.510
|
267.571
|
267.571
|
|
|
|
|
|
2.677.938
|
2.544.674
|
10.365
|
|
|
122.899
|
|
|
SE
|
5.963.715
|
33.964
|
33.964
|
|
|
|
|
|
5.929.751
|
30.037
|
4.889.122
|
9.966
|
|
1.000.626
|
|
|
UK
|
127.971.890
|
937.725
|
917.423
|
20.302
|
|
|
|
|
127.034.165
|
211.156
|
97.694.544
|
16.171
|
|
29.112.293
|
|
|
Total
|
614.941.111
|
165.234.661
|
10.206.818
|
83.501.694
|
64.957.210
|
4.491.756
|
515.514
|
1.561.670
|
449.706.450
|
31.356.019
|
303.882.729
|
20.163.986
|
26.723.146
|
59.725.134
|
7.855.435
|
Annex 9
|
|
TOR: Recovery rates (RR) per Member State 2018
|
|
MS
|
Fraudulent
|
Non-fraudulent
|
|
|
Established amount
|
Recovered amount
|
RR
|
Established amount
|
Recovered amount
|
RR
|
|
|
EUR
|
EUR
|
%
|
EUR
|
EUR
|
%
|
|
BE
|
15.655.295
|
6.217.864
|
40%
|
6.388.963
|
5.082.783
|
80%
|
|
BG
|
542.270
|
37.982
|
7%
|
59.220
|
59.220
|
100%
|
|
CZ
|
0
|
0
|
0%
|
4.696.506
|
4.467.278
|
95%
|
|
DK
|
167.285
|
167.285
|
100%
|
7.234.128
|
5.963.882
|
82%
|
|
DE
|
18.731.575
|
7.384.649
|
39%
|
89.095.658
|
77.552.906
|
87%
|
|
EE
|
568.102
|
0
|
0%
|
109.005
|
89.986
|
83%
|
|
IE
|
0
|
0
|
0%
|
3.118.347
|
1.933.034
|
62%
|
|
EL
|
3.158.656
|
19.839
|
1%
|
1.275.067
|
258.493
|
20%
|
|
ES
|
1.734.150
|
307.085
|
18%
|
30.028.125
|
22.104.520
|
74%
|
|
FR
|
78.879.029
|
77.202.388
|
98%
|
15.874.892
|
6.757.214
|
43%
|
|
HR
|
1.028.297
|
455.642
|
44%
|
74.545
|
74.545
|
100%
|
|
IT
|
4.760.274
|
489.595
|
10%
|
4.027.116
|
2.512.032
|
62%
|
|
CY
|
12.878
|
0
|
0%
|
57.210
|
57.210
|
100%
|
|
LV
|
779.838
|
0
|
0%
|
292.235
|
260.684
|
89%
|
|
LT
|
1.900.284
|
75.913
|
4%
|
3.224.922
|
3.105.468
|
96%
|
|
LU
|
0
|
0
|
0%
|
0
|
0
|
0%
|
|
HU
|
771.268
|
771.268
|
100%
|
466.926
|
353.390
|
76%
|
|
MT
|
0
|
0
|
0%
|
0
|
0
|
0%
|
|
NL
|
1.708.686
|
617.171
|
36%
|
128.285.374
|
31.934.457
|
25%
|
|
AT
|
87.272
|
21.583
|
25%
|
2.097.472
|
1.823.922
|
87%
|
|
PL
|
2.239.388
|
253.189
|
11%
|
5.920.272
|
3.794.754
|
64%
|
|
PT
|
1.552.960
|
265.705
|
17%
|
7.794.511
|
3.453.500
|
44%
|
|
RO
|
21.251
|
21.251
|
100%
|
2.375.356
|
767.342
|
32%
|
|
SI
|
405.956
|
405.956
|
100%
|
563.809
|
563.809
|
100%
|
|
SK
|
115.016
|
57.484
|
50%
|
435.887
|
261.647
|
60%
|
|
FI
|
267.571
|
231.403
|
86%
|
2.677.938
|
2.509.783
|
94%
|
|
SE
|
0
|
0
|
0%
|
5.929.751
|
5.735.508
|
97%
|
|
UK
|
127.163
|
0
|
0%
|
127.020.827
|
43.347.909
|
34%
|
|
Total
|
135.214.464
|
95.003.251
|
70%
|
449.124.059
|
224.825.275
|
50%
|
Annex 10
|
|
TOR: Examination of write-off cases in 2018
|
|
MS
|
Acceptance
|
Reference to Article 17.2 rejected
|
Additional information request (AI)
|
Not appropriate
|
Total cases*
|
Cases assessed twice (AI)
|
Total (amounts not counted twice)
|
|
|
N
|
EUR
|
N
|
EUR
|
N
|
EUR
|
N
|
EUR
|
N
|
N
|
EUR
|
|
AT
|
1
|
441.832
|
1
|
373.654
|
1
|
1.305.392
|
1
|
420.656
|
4
|
1
|
2.541.534
|
|
BE
|
|
|
1
|
4.109.417
|
|
|
|
|
1
|
|
4.109.417
|
|
CZ
|
1
|
55.146
|
|
|
|
|
|
|
1
|
|
55.146
|
|
DE
|
23
|
8.533.751
|
19
|
9.641.035
|
42
|
17.922.559
|
|
|
84
|
24
|
36.097.345
|
|
DK
|
|
12.775
|
1
|
147.221
|
|
|
|
|
1
|
|
159.996
|
|
ES
|
3
|
391.116
|
6
|
1.847.299
|
8
|
6.483.993
|
|
|
17
|
|
8.722.407
|
|
FI
|
|
|
|
237
|
3
|
436.434
|
|
|
3
|
|
436.671
|
|
FR
|
|
|
|
|
3
|
277.121
|
|
|
3
|
|
277.121
|
|
GR
|
1
|
2.003.201
|
1
|
301.349
|
3
|
10.300.535
|
|
|
5
|
2
|
12.605.085
|
|
HU
|
|
|
1
|
3.394.774
|
1
|
547.704
|
|
|
2
|
1
|
3.942.477
|
|
IT
|
4
|
940.198
|
2
|
414.685
|
12
|
19.441.590
|
|
|
18
|
9
|
20.796.473
|
|
LT
|
|
|
|
|
1
|
973.491
|
|
|
1
|
|
973.491
|
|
LV
|
|
|
1
|
95.760
|
3
|
765.352
|
|
|
4
|
|
861.112
|
|
NL
|
|
|
|
|
19
|
12.680.515
|
|
|
19
|
|
12.680.515
|
|
PL
|
1
|
116.628
|
|
|
4
|
1.414.678
|
|
|
5
|
1
|
1.531.306
|
|
PT
|
|
|
|
|
|
|
1
|
622.955
|
1
|
1
|
622.955
|
|
RO
|
4
|
2.425.052
|
|
665
|
15
|
4.345.860
|
|
|
19
|
7
|
6.771.578
|
|
Total
|
38
|
14.919.700
|
33
|
20.326.096
|
115
|
76.895.224
|
2
|
1.043.611
|
188
|
46
|
113.184.631
|
ANNEX 11
Classification of cases in relation to CAP expenditure
The analysis of irregularities in Section 3 'Common Agricultural Policy' separately focuses on 'rural development' (RD) and direct 'support to agriculture' (SA).
To this purpose, cases are classified as:
·RD, where they concern only expenditure on budget lines/posts that contain the codes '0504', 'B01-4' or 'B01-50' (RD budget codes).In addition, it has been considered that there are 168 irregularities where the field 'Fund' makes reference to the EARDF (European Agriculture Rural Development Fund), even if the budget line/post is not specified.
·SA, where the budget line/post does not contain RD budget codes, but only SA budget codes (all the others). In addition, it has been considered that there are 112 irregularities where the field 'Fund' makes reference to the EAGF (European Agriculture Guarantee Fund) and the budget line/post is not specified. For these cases, it is not clear whether this expenditure financed rural development (from the EAGGF – guarantee section) or SA. In order to find the best possible classification for these cases, the following hypothesis has been made. As from 2007, the EARDF has been created to finance all measures concerning rural development. Consequently, if the budget years associated to an irregularity are from 2007 onwards, it seems to be unlikely that this irregularity is related to rural development, so it has been considered SA (80 cases). In case also the budget year is not mentioned, but the programming period mentioned in the relevant field is 2007-2013 or 2014-2020, the irregularity has also been considered SA (2 cases). The other irregularities (30 cases) have been classified as UNCLEAR.
SA includes expenditure in relation to intervention in agricultural markets and direct payments to farmers.
·'SA/RD', where they concern both types of expenditure (RD and SA budget codes). In addition, it has been considered that there are 116 irregularities where the field 'Fund' makes reference to 'EAGF/EARDF', but the budget line/post is not specified. For these cases, it is not clear whether this expenditure financed only rural development (before from the EAGGF – guarantee section and then from EARDF) or both rural development (EARDF) and SA (EAGF). In order to find the best possible classification for these cases, the following hypothesis has been made. As from 2007, the EARDF has been created to finance all measures concerning rural development. Consequently, if the budget years associated to an irregularity are from 2007 onwards only , it seems to be likely that there is also an SA component in the expenditure related to the irregularity (because EAGF is more likely to point to an SA item of expenditure) so the irregularity has been considered SA/RD (66 cases). In case also the budget year is not mentioned, but the programming period is 2007-2013 or 2014-2020, the irregularity has also been considered SA/RD (36 cases). The other irregularities (14 cases) have been classified as UNCLEAR.
·'UNCLEAR', where information has not been considered enough to assign the case to RD, SA or SA/RD (see above).
Some parts of the analysis in Section 3 'Common Agricultural Policy' separately focus on 'Interventions in agricultural markets' (or 'Market measures') and 'Direct payments'.
In fact, as from 2006, support to agriculture is structured in the EU Budget along 2 main chapters:
·Chapter 0502 'Interventions in agricultural markets';
·Chapter 0503 'Direct aids'.
To the purpose of the analysis in Section 3 'Common Agricultural Policy', cases are classified:
·'Market measures', where they concern expenditure on Budget lines/posts which contain the code '502', as from the 2006 EU Budget (the same case may concern also other areas, including rural development or direct payments);
·'Direct payments', where they concern expenditure on Budget lines/posts which contain the code '503', as from the 2006 EU Budget (the same case may concern also other areas, including rural development or market measures).
Cases concerning only expenditure in 2005 or before are not considered 'Market measures' or 'direct payments'. Before 2006, the EU Budget had a different structure:
·In 2004 and 2005, the chapters 0502 and 0503 referred respectively to 'Plant products' and 'Animal products';
·Before 2004, subsection B01 covered the Guarantee section of the EAGG fund and was split, among others, in:
oB01-1 'Plant products';
oB01-2 'Animal products'.
ANNEX 12
Categories of irregularities and related types
Tables NR9-NR12
The categories used in Tables NR9-NR12 are as follows:
|
Code
|
Category
|
Type
|
|
T11
|
Request
|
T11/00: Incorrect or incomplete request for aid
|
|
|
|
T11/01: False or falsified request for aid
|
|
|
|
T11/02:Product, species, project and/or activity not eligible for aid
|
|
|
|
T11/03: Incompatible cumulation of aid
|
|
|
|
T11/04: Several requests for the same product, species, project and/or activity
|
|
|
|
T11/99: Other
|
|
T12
|
Beneficiary
|
T12/00: Incorrect identity operator/beneficiary
|
|
|
|
T12/01: Non-existent operator/beneficiary
|
|
|
|
T12/02: Misdescription of the holding
|
|
|
|
T12/03: Operator/beneficiary not having the required quality
|
|
|
|
T12/99: Other
|
|
T13
|
Accounts and records
|
T13/00: Incomplete accounts
|
|
|
|
T13/01: Incorrect accounts
|
|
|
|
T13/02: Falsified accounts
|
|
|
|
T13/03: Accounts not presented
|
|
|
|
T13/04: Absence of accounts
|
|
|
|
T13/05: Calculation errors
|
|
|
|
T13/06: Revenues not declared
|
|
|
|
T13/99: Other
|
|
T14
|
Documentary proof
|
T14/00: Documents missing and/or not provided
|
|
|
|
T14/01: Documents incomplete
|
|
|
|
T14/02: Documents incorrect
|
|
|
|
T14/03: Documents provided too late
|
|
|
|
T14/04: Documents false and/or falsified
|
|
|
|
T14/99: Other
|
|
T15
|
Product, species and/or land
|
T15/00: Over or under production
|
|
|
|
T15/01: Inexact composition
|
|
|
|
T15/02: Inexact origin
|
|
|
|
T15/03: Inaccurate value
|
|
|
|
T15/04: Inexact quantity
|
|
|
|
T15/05: Variation in quality or content
|
|
|
|
T15/06: Quantities outside permitted limits, quotas, thresholds
|
|
|
|
T15/07: Unauthorised substitution or exchange
|
|
|
|
T15/08: Unauthorised addition or mixture
|
|
|
|
T15/09: Unauthorised use
|
|
|
|
T15/10: Falsification of the product
|
|
|
|
T15/11: Incorrect storage or handling
|
|
|
|
T15/12: Fictitious use or processing
|
|
|
|
T15/13: Incorrect classification (incl. incorrect tariff heading)
|
|
|
|
T15/14: Overdeclaration and/or declaration of ficticious product, species and/or land
|
|
|
|
T15/99: Other
|
|
T16
|
(Non-)action
|
T16/00: Action not implemented
|
|
|
|
T16/01: Action not completed
|
|
|
|
T16/02: Operation prohibited during the measure
|
|
|
|
T16/03: Failure to respect deadlines
|
|
|
|
T16/04: Irregular termination, sale or reduction
|
|
|
|
T16/05: Absence of identification, marking, etc.
|
|
|
|
T16/06: Refusal of control, audit, scrutiny etc.
|
|
|
|
T16/07: Control, audit, scrutiny etc. not carried out in accordance with regulations, rules, plan etc.
|
|
|
|
T16/08: Infringement of rules concerned with public procurement
|
|
|
|
T16/09: Infringements with regard to the cofinancing system
|
|
|
|
T16/10: Refusal to repay not spent or unduly paid amount
|
|
|
|
T165/99: Other
|
|
T17
|
Movement
|
T17/00: Irregularities in connection with final destination (change of, non arrival at, etc.)
|
|
|
|
T17/01: Fictitious movement
|
|
|
|
T17/99: Other
|
|
T18
|
Bankruptcy
|
T18/00: Legal persons - liquidation
|
|
|
|
T18/01: Legal persons - reorganisation to structure debt
|
|
|
|
T18/02: Natural persons - repayment plan
|
|
|
|
T18/03: Natural persons - repayment plan not possible
|
|
|
|
T18/99: Other
|
|
T19
|
Ethics and integrity
|
T19/00: Conflict of interest
|
|
|
|
T19/01: Bribery - passive
|
|
|
|
T19/02: Bribery - active
|
|
|
|
T19/03: Corruption
|
|
|
|
T19/04: Corruption - passive
|
|
|
|
T19/05: Corruption - active
|
|
|
|
T19/99: Other irregularities concerning integrity and ethics
|
|
T40
|
Public procurement (see annex Commission Decision C(2013)9527)
|
T40/01: Lack of publication of contract notice
|
|
|
|
T40/02: Artificial splitting of works/services/supplies contracts
|
|
|
|
T40/03: Non-compliance with - time limits for receipt of tenders; or - time limits for receipt of requests to participate
|
|
|
|
T40/04: Insufficient time for potential tenderers/candidates to obtain tender documentation
|
|
|
|
T40/05: Lack of publication of -extended time limits for receipt of tenders; or - extended time limits for receipt of requests to participate
|
|
|
|
T40/06: Cases not justifying the use of the negotiated procedure with prior publication of a contract notice
|
|
|
|
T40/07: For the award of contracts in the field of defence and security falling under directive 2009/81/EC specifically, inadequate justification for the lack of publication of a contract notice
|
|
|
|
T40/08: Failure to state: - the selection criteria in the contract notice; and/or - the award criteria (and their weighting) in the contract notice or in the tender specifications
|
|
|
|
T40/09: Unlawful and/or discriminatory selection and/or award criteria laid down in the contract notice or tender documents
|
|
|
|
T40/10: Selection criteria not related and proportionate to the subjectmatter of the contract
|
|
|
|
T40/11: Discriminatory technical specifications
|
|
|
|
T40/12: Insufficient definition of the subject-matter of the contract
|
|
|
|
T40/13: Modification of selection criteria after opening of tenders, resulting in incorrect acceptance of tenderers
|
|
|
|
T40/14: Modification of selection criteria after opening of tenders, resulting in incorrect rejection of tenderers
|
|
|
|
T40/15: Evaluation of tenderers/candidates using unlawful selection or award criteria
|
|
|
|
T40/16: Lack of transparency and/or equal treatment during evaluation
|
|
|
|
T40/17: Modification of a tender during evaluation
|
|
|
|
T40/18: Negotiation during the award procedure
|
|
|
|
T40/19: Negotiated procedure with prior publication of a contract notice with substantial modification of the conditions set out in the contract notice or tender specifications
|
|
|
|
T40/20: Rejection of abnormally low tenders
|
|
|
|
T40/21: Conflict of interest
|
|
|
|
T40/22: Substantial modification of the contract elements set out in the contract notice or tender specifications
|
|
|
|
T40/23: Reduction in the scope of the contract
|
|
|
|
T40/24: Award of additional works/services/supplies contracts (if such award constitutes a substantial modification of the original terms of the contract) without competition in the absence of the applicable conditions (extreme urgency brought about by unforeseeable events; an unforeseen circumstance for complementary works, services, supplies)
|
|
|
|
T40/25: Additional works or services exceeding the limit laid down in the relevant provisions
|
|
|
|
T40/99: Other
|
|
T50
|
State aid
|
T50/01: Failure to notify State Aid
|
|
|
|
T50/02:Wrong aid scheme applied
|
|
|
|
T50/03:Misapplication of the aid scheme
|
|
|
|
T50/04:Monitoring requirements not fulfilled
|
|
|
|
T50/05:Reference investment not taken into account in the applicable aid scheme
|
|
|
|
T50/06:No consideration of revenue in the applicable aid scheme
|
|
|
|
T50/07:No respect of the incentive effect of the aid
|
|
|
|
T50/08:Aid intensity not respected
|
|
|
|
T50/09:De Minimis threshold exceeded
|
|
|
|
T50/99:Other State aid
|
|
T90
|
Other
|
T90/99: Other irregularities
|
Tables CP23 and CP24
The categories used in Tables CP23 and CP24 are built as follows:
·Infringements concerning the request: T11/00, T11/01, T11/99
·Eligibility / Legitimacy of expenditure/measure: T11/02
·Multiple financing: T11/03, T11/04
·Violations/breaches by the operator: T12
·Incorrect, absent, falsified accounts: T13
·Incorrect, missing, false or falsified supporting documents: T14
·Product, species and/or land: T15
·Infringement of contract provisions/rules: T16/00, T16/01, T16/02, T16/03, T16/04, T16/05, T16/06, T16/07, T16/09, T16/10, T16/99
·Movement: T17
·Bankruptcy: T18
·Ethics and integrity: T19
·Infringement of public procurement rules: T40, T16/08
·State aid: T50
ANNEX 13
Analysis of the sensitivity of FDR and IDR
Intervention in agricultural markets and direct payments
In the main body of this Report reference is made to the FDR (Fraud Detection Rate) and the IDR (Irregularity Detection Rate) in relation to 'Intervention in agricultural markets' and 'direct payments'.
A part of the irregularities used for these calculations are not referred exclusively to a specific policy measure, because the same case may cover several budget posts referring to different measures. These 'mixed' cases have been included in their full financial amount in all policy measures affected.
FDR and IDR for 'Intervention in agricultural markets' in Table NR14_a below is calculated on the basis of the amounts of all the irregularities (fraudulent and non fraudulent) where this type of expenditure is involved (considering in full the 'mixed' cases, as explained above). The same applies with reference to FDR and IDR for 'direct payments'. Table NR14_a shows the outcome of these calculations.
As there are a number of 'intervention of agricultural markets' cases that concern, at the same time, this type of expenditure and other measures, the total amounts (and the corresponding FDR and IDR) associated to 'intervention in agricultural markets' are somehow inflated. The same applies with reference to 'direct payments'.
An analysis is then warranted of how sensitive FDR and IDR are to the presence of these 'mixed' cases. As a first step, an assessment is required of the number of these 'mixed' cases, the nature of the related overlaps and the amounts involved. Fig. NR1-NR3 show the outcome of this assessment, respectively for cases reported as fraudulent, not reported as fraudulent and for all cases together.
Table NR14_b shows FDR and IDR where, for 'intervention in agricultural markets', only the amounts related to cases that do not overlap with rural development or direct payments are included in the calculation (i.e.147 346 967, for the FDR). The same applies to 'direct payments'.
Figures in Table NR14_a represent the upper limit of FDR and IDR for 'intervention in agricultural markets' or 'direct payments', as they include amounts that are linked to irregularities or fraud related also to other types of expenditure.
Figures in Table NR14_b represent the lower limit of FDR and IDR for 'intervention in agricultural markets' or 'direct payments', as they exclude part of the amounts of the 'mixed' cases that could be related to the relevant types of expenditure.
As FDR and IDR in Tables NR14_a and NR14_b are similar, it can be concluded that they are not significantly sensitive to this 'mixed' cases issue.
Rural development (RD) and support to agriculture (SA)
FDR and IDR for 'Support to agriculture' ('SA') is calculated on the basis of the amounts (of the irregularities or fraud) related to cases where only this type of expenditure is involved. The same applies with reference to FDR and IDR for 'Rural development' ('RD'). Table NR14_c shows the outcome of this calculation.
There are a number of cases that have not been classified as 'pure' 'RD' or 'SA' cases. They are reported as 'mixed' cases (RD/SA) or unclear cases. This implies that the total amounts (and the corresponding FDR and IDR) associated to 'RD' are somehow underestimated. The same applies with reference to 'SA'.
An analysis is then warranted of how sensitive FDR and IDR are to the presence of these RD/SA 'mixed' cases and of unclear cases. As a first step, an assessment is required of the number of these 'mixed' or unclear cases and the amounts involved. Fig. NR4-NR6 show the outcome of this assessment, respectively for cases reported as fraudulent, not reported as fraudulent and for all cases together.
Fig. NR4: Irregularities and amounts reported as fraudulent by type of expenditure – 2014-2018
Support to agriculture
689
171 223 296
Rural development
1,049
131 512 211
Rural development
10 871
632 774 038
Support to agriculture
4 971
369 218 992
Fig. NR6: Irregularities and amounts reported by type of expenditure – 2014-2018
Rural development
11 920
764 286 249
Support to agriculture
5 660
540 442 288
Table NR14_d shows FDR and IDR where 'mixed' and unclear cases are added both for 'rural development' and 'support to agriculture'. In practice, for 'rural development', also all the amounts related to 'mixed' and unclear cases are added to the amounts related to the 'pure' rural development cases (i.e. 5 385 350+12 492 for the FDR). The same applies to 'support to agriculture'. Therefore, FDR and IDR in Table NR13_d are somehow inflated and represent the upper limit.
As FDR and IDR in Tables NR14_c and NR14_d are similar, it can be concluded that they are not significantly sensitive to this 'mixed' cases issue.
ANNEX 14
Full description of the Themes in Figures CP1-CP4
Priority 'Tourism'
Promotion of natural assets
Protection and development of natural heritage
Other assistance to improve tourist services
Priority 'Environmental protection and risk prevention'
Management of household and industrial waste
Management and distribution of water (drinking water)
Water treatment (waste water)
Air quality
Integrated prevention and pollution control
Mitigation and adaptation to climate change
Rehabilitation of industrial sites and contaminated land
Promotion of biodiversity and nature protection (including Natura 2000)
Risk prevention (including the drafting and implementation of plans and measures to prevent and manage natural and technological risks)
Other measures to preserve the environment and prevent risks
ANNEX 15
Legenda
SA: Support to Agriculture
RD: Rural Development
SA/RD: Support to Agriculture/ Rural Development
GUID: European Agricultural Guarantee and Guidance Fund – Section Guidance
EFF: European Fisheries Fund
EMFF: European Maritime and Fisheries Fund
CF: Cohesion Fund
ERDF: European Regional and Development Fund
ESF: European Social Fund
AMIF: Asylum, Migration and Integration Fund
YEI: Youth Employment Initiative
HRD: pre-accession, Human Resources Development component
IPARD: Instrument for Pre-Accession for Rural Development
PHARE: Pre-accession assistance programme
REGD: pre-accession, Regional Development component
TAIB: Transition Assistance and Institution Building
TIPAA: Turkey Instrument for Pre-accession Assistance
CBC: pre-accession, Cross-Border Cooperation component
