EUROPEAN COMMISSION Brussels, 23.9.2022 SWD(2022) 307 final COMMISSION STAFF WORKING DOCUMENT Statistical evaluation of irregularities reported for 2021: own resources, agriculture, cohesion and fisheries policies, pre-accession and direct expenditure Accompanying the document COMMISSION REPORT TO THE COUNCIL AND THE EUROPEAN PARLIAMENT 33rd Annual Report on the protection of the European Union's financial interests and the fight against fraud - 2021 {COM(2022) 482 final} - {SWD(2022) 302 final} - {SWD(2022) 303 final} - {SWD(2022) 304 final} - {SWD(2022) 305 final} - {SWD(2022) 306 final}



Contents List of abbreviations 1.INTRODUCTION 1.1.Scope of the document 1.1.Structure of the document 2.TRADITIONAL OWN RESOURCES Executive summary 2.1.Introduction 2.2.General analysis –Trend analysis 2.2.1.Reporting years 2017-2021 2.2.2.OWNRES data vs TOR collection 2.2.3.Recovery 2.3.Specific analysis 2.3.1.Cases reported as fraudulent 2.3.2.Cases reported as non-fraudulent 2.3.3.Fraudulent and non-fraudulent cases and COVID-19 related goods 2.4.Member States’ activities 2.4.1.Classification of cases as fraudulent and non-fraudulent and related rates

2.4.2.Recovery rates 2.4.3.Commission’s monitoring 3.COMMON AGRICULTURAL POLICY Executive summary 3.1.Introduction 3.2.General analysis 3.2.1.Irregularities reported in the years 2017-2021 3.2.2.Irregularities reported as fraudulent 3.2.3.Irregularities not reported as fraudulent 3.3.Specific analysis 3.3.1.Modus operandi 3.3.2.Fraud and Irregularity Detection Rates (FDR and IDR) by CAP components 3.3.3.Market measures – fraudulent and non-fraudulent irregularities 3.3.4.Risk analysis and spontaneous reporting 3.4.Anti-fraud work carried out by the Member States 3.4.1.Duration of irregularities 3.4.2.Detection of irregularities reported as fraudulent by Member State 3.4.3.Fraud and Irregularity Detection by sector and Member State 3.4.4.Follow-up to suspected fraud 3.5.Recovery cases

Main findings 4.COHESION, FISHERIES AND OTHER INTERNAL POLICIES Executive summary 4.1.Introduction 4.2.General analysis 4.2.1.Irregularities reported as fraudulent 4.2.2.Irregularities not reported as fraudulent 4.2.3.Irregularities reported in relation to the PP 2014-2020: comparison with PP 2007-2013 4.3.Specific analysis 4.3.1.Irregularities by area of the cohesion policy 4.3.2.Irregularities by type 4.4.Risk analysis and spontaneous reporting 4.5.Antifraud and control activities by Member States 4.5.1.Duration of irregularities 4.5.2.Detection of irregularities reported as fraudulent by Member State 4.5.3.Fraud detection rate 4.5.4.Irregularity detection rate 4.5.5.Follow-up to suspected fraud (programming period 2007-2013) 4.6.Other internal policies Main Findings

5.PRE-ACCESSION POLICY Executive Summary 5.1.Introduction 5.2.Instruments for Pre-accession Assistance 5.2.1.Before 2007: Pre-accession Assistance (PAA) 5.2.2.2007-2013: The Instrument for Pre-accession Assistance (IPA I) 5.2.3.2014 – 2020: The Instrument for Pre-accession Assistance (IPA II) 5.2.4.2021 – 2027: The Instrument for Pre-accession Assistance (IPA III) 5.3.General analysis 5.4.Pre-accession Assistance (PAA 2000-2006) 5.4.1.Recent trends 5.4.2.Recent trends by component 5.4.3.Recent trends by beneficiary country 5.4.4.Trends since the start of PAA, by beneficiary country and component 5.5.Instrument for Pre-Accession Assistance (IPA I, 2007-2013) 5.5.1.Recent trends 5.5.2.Recent trends by component 5.5.3.Recent trends by beneficiary country 5.5.4.Trends since the start of IPA I, by beneficiary country and component 5.6.Instrument for Pre-accession Assistance II (IPA II 2014-2020)

5.6.1.Recent trends 5.6.2.Recent trends by component 5.6.3.Recent trends by beneficiary country 5.6.4.Trends since the start of IPA II, by beneficiary country and component 6.Direct Management 6.1.Introduction 6.2.General analysis 6.2.1.Five year analysis 2017-2021 6.3.Specific analysis 6.3.1.Recoveries according policy areas 6.3.2.Recoveries according to legal entity residence 6.3.3.Method of detection 6.3.4.Types of irregularity 6.3.5.Recovery COUNTRY FACTSHEETS Belgium - Belgique/België Bulgaria – България Czech Republic - Česká republika Denmark – Danmark Germany – Deutschland

Estonia – Eesti Ireland – Éire Greece – Ελλάδα Spain – España France Croatia – Hrvatska Italy – Italia Cyprus – Κύπρος Latvia – Latvija Lithuania – Lietuva Luxembourg Hungary - Magyarország Malta Netherlands - Nederland Austria – Österreich Poland – Polska Portugal Romania – România Slovenia – Slovenija Slovakia – Slovensko

Finland – Suomi-Finland Sweden – Sverige ANNEXES List of abbreviations AMIF Asylum, Migration and Integration Fund CAP Common Agricultural Policy CARDS Community Assistance for Reconstruction, Development and Stabilisation CBC Cross-Border Cooperation CF Cohesion Fund DA Direct payments to farmers EAFRD European Agricultural Fund for Rural Development EAGF European Agricultural Guarantee Fund EAGGF European Agricultural Guidance and Guarantee Fund EFF European Fisheries Fund EGF European Globalisation Adjustment Fund EMFF European Maritime and Fisheries Fund ERDF European Regional Development Fund ESF European Social Fund ESIF European Structural and Investment Funds FAL Fraud Amount Level FDR Fraud Detection Rate FEAD Fund for European Aid to the Most Deprived FFL Fraud Frequency Level GUID European Agricultural Guarantee and Guidance Fund – Section Guidance HRD Pre-accession, Human Resources Development component IDR Irregularities Detection Rate IMS Irregularity Management System IPA Instrument for Pre-accession Assistance IPARD Instrument for Pre-Accession Assistance for Rural Development ISF Internal Security Fund ISPA Instrument for Structural Policies for Pre-Accession MM Market Support Measures PAA Pre-Accession Assistance 2000-2006 PHARE Pre-accession assistance programme PP Programming period RD Rural Development REGD Pre-accession, Regional Development component SA Direct Support to Agriculture SAPARD Special Accession Programme for Agricultural and Rural Development TAIB Transition Assistance and Institution Building TIPAA Turkey Instrument for Pre-accession Assistance TOR Traditional Own Resources YEI Youth Employment Initiative 1.INTRODUCTION 1.1.Scope of the document This document presents a statistical evaluation of the irregularities and fraud detected by the Member States during 2021, in the context of past years and relevant programming periods (PP). It covers both the revenue and expenditure sides of the EU budget. This analysis is based on the notifications provided by national authorities of cases of irregularities and suspected or established fraud. Their reporting is performed in fulfilment of a legal obligation enshrined in sectoral European legislation. The document accompanies the Annual Report adopted on the basis of article 325(5) of the Treaty on the Functioning of the European Union (TFEU), according to which “The Commission, in cooperation with Member States, shall each year submit to the European Parliament and to the Council a report on the measures taken for the implementation of this article”. Therefore, this document should be regarded as an analysis of the achievements of the Member States, in terms of detection and reporting. The methodology (including the definition of terms and indicators), the data sources and the data capture systems are explained in detail in the Commission Staff Working Document – Methodology for the Statistical Evaluation of Irregularities accompanying the Annual Report on the Protection of the EU financial interests for the year 2015. 1.1.Structure of the document The present document includes an analysis of the irregularities reported in the area of traditional own resources (revenue), as well as an analysis of the irregularities reported for expenditure (Common Agricultural Policy, cohesion policy, fisheries and other internal policies; the pre-accession policy and direct management). The document is completed by 27 country factsheets, which summarise, for each Member State, the main indicators and information on the detection of irregularities and fraud. Several annexes complement the information and data, providing a global overview of the irregularities reported according to the relevant sector regulations. Annexes 1 to 11 concern Traditional Own Resources, Annexes 12 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. 2.TRADITIONAL OWN RESOURCES Executive summary In 2021, the COVID-19 pandemic continued to affect the lives of all individuals and businesses in the EU. Looking back, in 2020 the pandemic was experienced as an emergency, while in 2021 it became part and parcel of life. Import figures for 2021 are proof of this. After the sharp 11.6% decrease in EU-27 imports in 2020, they increased by 23% in 2021. In 2021, the number of fraudulent and non-fraudulent irregularities related to TOR remained quite stable, the related amount of TOR increased and was the highest amount detected during the last 5 years. For both fraudulent and non-fraudulent irregularities, the amount of TOR detected increased compared to the five-year average, by 32% and 13% respectively. In total, the TOR amount increased by 18% in 2021 compared to the average for 2017-2021. In comparison, the number of fraudulent and non-fraudulent irregularities related to TOR decreased by 3% compared to the five-year average. The number of fraudulent irregularities increased by 1 % and non-fraudulent irregularities decreased by 4%.

Of all fraudulent and non-fraudulent irregularities detected in 2021, 12% were classified as fraudulent. National anti-fraud services, together with customs release controls, played a key role in detecting fraudulent irregularities in 2021. Inspections by anti-fraud services, the most successful method way of detecting fraudulent irregularities, surpassed post-release controls and release controls in detecting fraudulent duty evasion. Non-fraudulent irregularities were primarily detected by means of post-release controls. Most cases reported in 2021 as fraudulent and non-fraudulent related to undervaluation, incorrect origin or classification/misdescription of goods. Smuggling remains one of the main fraudulent irregularities. Textiles, electrical machinery and equipment were the types of goods most affected by fraud and irregularities in number of cases and in monetary terms, followed by miscellaneous chemical products, footwear and tobacco most affected in terms of amounts and by vehicles and plastics in terms of number of cases. In 2021 China remained the most important country of origin of goods affected by irregularities reported as fraudulent or non-fraudulent. For COVID-19-related goods, in 2021, a notable increase in the amounts reported as irregular was observed for goods such as disinfectants and sterilisation products, protective garments and medical consumables. However, analysis shows that the impact of irregularities affecting COVID-19-related goods remained relatively low in 2021 (4% of the total number of irregularities reported in 2021 and 6% of the related amounts). In 2021, the Commission continued, on-the-spot or remotely, its monitoring and control visits to ensure the correct application of EU customs and TOR legislation. Where cooperation and progress made in tackling outstanding issues are considered insufficient, corrective measures are being applied. As the 2020 PIF report states, such corrective measures have already been applied by the Commission against the UK for undervalued textiles and footwear from China (Snapshot 1). On 8 March 2022, the CJEU issued its ruling in related Case C-213/19 against the UK. The Commission is in the process of analysing the implications of that CJEU ruling both for the UK (e.g. re-calculation of TOR losses) and for the Member States. The Commission also quantified potential TOR losses with regard to the evasion of anti-dumping duties for solar panels and informed the EU Member States concerned. 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’ . In summary, the statistics for the 2021 PIF report were prepared based on the total established and estimated amount of TOR as reported in OWNRES. Recovery figures are based only on established amounts. For comparability with previous years, the analysis for this report was carried out based on the figures obtained for the EU of 27 Member States . The UK figures can nevertheless be found in the annexes. The following analysis, based on the data available on the cut-off date (15 March 2022), aims to provide an overview of the reported cases of fraud and irregularities reported for 2021 together with their financial impact. 2.2.General analysis –Trend analysis 2.2.1.Reporting years 2017-2021 The number of cases reported in OWNRES for 2021 (3 988) is about 3 % lower than the average number of cases of irregularities reported for the 2017-2021 period (4 131). The total estimated and established amount of TOR involved (EUR 524 million) is about 18 % higher than the average estimated and established amount for the years 2017-2021 (EUR 443 million). In 2021, eight big cases for a total amount of about EUR 122 million were reported compared to 2020, when five big cases for a total amount of about EUR 67 million affected the total estimated and established amount. CHART TOR1: Total number of OWNRES cases and the related estimated and established amount (2017-2021) Annex 1 of the summary tables shows the situation on the cut-off date (15 March 2022) for the years 2017-2021.

2.2.1.1.Irregularities reported as fraudulent The number of cases reported as fraudulent registered in OWNRES for 2021 (482) is currently 1% higher than the average number of cases reported for the 2017-2021 period (478). The total estimated and established amount of TOR involved (EUR 157 million) represents an increase of 32% of the average estimated and established amount for the years 2017-2021- (EUR 119 million). For 2021, Luxemburg, Finland and Sweden 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 (2017-2021) On the cut-off date (15 March 2022), 12% of all cases detected in 2021 were classified as fraudulent. The percentage had remained stable since 2020 (12%). Annex 2 of the summary tables shows the situation on the cut-off date for the years 2017-2021. 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 2021 (3 506) was 4% lower than the average number reported for 2017-2021 (3 653). The total estimated and established amount of TOR (EUR 367 million) was 13% higher than the average estimated and established amount for the years 2017-2021 (EUR 324 million). Cyprus did not report any case of irregularity exceeding an amount of EUR 10 000 for 2021. CHART TOR3: OWNRES cases not reported as fraudulent and the related estimated and established amount (2017-2021) Annex 3 of the summary tables shows the situation on the cut-off date for years 2017-2021. 2.2.2.OWNRES data vs TOR collection In 2021, the total established amount of TOR (gross) was EUR 25.2 billion and about 98% was duly recovered and made available to the Commission through the A-account . According to the OWNRES data, around EUR 524 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 represents 2.11% of total collected TOR (gross) amount in 2021 . This detection rate has increased compared to 2020, when it was 1.95% . A percentage of 2.11 % indicates that of every EUR 100 of TOR (gross) established and collected, an amount of EUR 2.11 is registered as irregular (fraudulent or non-fraudulent) in OWNRES. There are differences among the Member States. In eight Member States , the percentage is above the average of 2.11 %. The highest percentages for 2021 can be seen in Finland, Latvia, Greece, the Netherlands and Belgium, with 5.38 %, 4.88 %, 4.38 %, 4.34 % and 3.8 % respectively. For the seven Member States that established and made available most TOR amounts, the average percentage of the estimated and established OWNRES amounts of TOR for 2021 was equal to 2.28%. Compared to the previous year (1.91%), this represents an increase of 0.37%. For the Netherlands, the proportion of estimated and established OWNRES amounts of TOR increased in 2021 from 0.79% to 4.34% compared to 2020, while for Belgium, Spain and Italy, it increased by 1.46%, 0.72% and 0.28% respectively. For the other three Member States , the average proportion of estimated and established OWNRES amounts of TOR decreased in 2021 (1.27 %) compared to the previous year (2.64%). TOR MAP1: Showing the percentage of estimated and established amount in OWNRES of established TOR for 2021

2.2.2.1. Detection rates in the COVID year 2021 Whereas the variation in the total number of cases reported as fraudulent or non-fraudulent in 2021 was within the usual range of the annual fluctuation, the related amounts increased considerably in 2021, leading to a higher overall detection rate in 2021 than in 2020. Chart TOR4 shows the variation in the annual detection rate for each Member State in 2017-2021. Bearing in mind that a number of variable factors can affect national detection rates and that customs controls had to be performed under pandemic conditions in many cases in 2021, the overall detection rate was still the second highest in 2021 during the last 5 years. The 2021 detection rates for Belgium, Greece, Spain, Latvia, Lithuania, the Netherlands, Austria and Finland were above the EU average. This makes it hard to say how much the detection rates are affected by the pandemic, changes in import volumes, fraud patterns or national customs control strategies. Chart TOR4: Detection rates 2017-2021 per Member State 2.2.3.Recovery The cases of fraud and irregularities detected in 2021 correspond to an established amount of EUR 479 million . Nearly EUR 216 million of this was recovered in cases where there was an irregularity and EUR 24 million in fraudulent cases . In total EUR 240 million was recovered by all Member States for all cases detected in 2021. In absolute figures, Germany recovered the highest amount in 2021 (EUR 74 million), followed by Spain (EUR 47 million) and the Netherlands (EUR 43 million). This is a starting point for 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 a huge financial impact. Member States also continued their recovery actions for the detected cases of previous years. 2.2.3.1. Recovery rates Over the past 5 years the annual recovery rate has varied between 50% and 77% (CHART TOR5). The recovery rate for cases reported in 2021 is currently 50% . In other words, out of every amount over EUR 10 000 of duties established and reported for 2021 in OWNRES as irregular/fraudulent, approximately EUR 5 000 has already been recovered. CHART TOR5: Annual recovery rates (2017-2021) 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 lengthy administrative and criminal procedures). Recovery rates vary among the Member States. In seven Member States, the entire established amount has already been recovered and in another four Member States the recovery rates are above 90%. In Czechia the recovery rate is 99%, in Denmark 99%, in Germany 96% and in Sweden 95%. Differences in recovery rates may be due to 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 2021 will also go up in the future. On the cut-off date (15 March 2022), the overall recovery rate for all years 1989-2021 was 64%. 2.3.Specific analysis 2.3.1.Cases reported as fraudulent 2.3.1.1. Modus operandi A breakdown by type of fraud shows that most fraudulent cases in 2021 relate to incorrect declarations (incorrect classification, value, country of origin or use of preferential arrangements) and formal shortcomings (e.g. failure to observe customs procedures). Smuggling as a fraud mechanism ranked second place in 2021.

In 2021, the customs procedure ‘release for free circulation’ remained the procedure most vulnerable to fraud (71% of the number of cases and 81% of the estimated and established amount) . A total of 10% of all cases reported as fraudulent and 12% of all estimated and established amounts in OWNRES cases registered as fraudulent for 2021 fall into the category ‘Other’ , whereas 14% of all cases reported as fraudulent and 4% of all estimated and established amounts involve the customs warehouse procedure. Of all cases reported as fraudulent, about 76% concern goods such as tobacco, vehicles, textiles, footwear, meat and meat products, articles of leather, iron, steel and aluminium. In monetary terms, these groups of goods represent about 93% of all amounts estimated and established for cases reported as fraudulent. China, Brazil, the United Arab Emirates, Belarus, Turkey, the United States and Russia are the main – in monetary terms – reported countries of origin of goods affected by fraud. 2.3.1.2. Method of detection of fraudulent cases In 2021 , inspections by anti-fraud services (38%) and customs controls carried out at the time of the release of goods (37%) were the most successful way of detecting fraudulent cases, followed by post-release controls (19%). CHART TOR6: Method of detection 2021 – Cases reported as fraudulent – by number of cases In monetary terms, of the fraudulent cases registered for 2021, involving EUR 157 million in estimated or established amounts, around 60% were detected during an inspection by anti-fraud services, 24% during a post-release control and 13 % during a control at the time of the release of the goods. CHART TOR6: Method of detection 2021 – Cases reported as fraudulent – by estimated and established amount In six 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 the release of goods were the method most used to detect fraud in Czechia, Denmark, Estonia, Greece, Croatia, Latvia, Austria, Poland, Slovenia and Slovakia, whereas post-release controls were the method most used in Bulgaria, Spain, Cyprus, Hungary, the Netherlands and Portugal. In Denmark, 48% of all estimated and established amounts in fraudulent cases were declared voluntarily. 2.3.1.3. Smuggled cigarettes In 2021, there were 115 cases of smuggled cigarettes registered (CN code 24 02 20 90) involving estimated TOR of around EUR 30 million. In 2020, the number of cases of smuggled cigarettes was 124, totalling around EUR 21 million of TOR. The highest number of cases was reported by Lithuania (46), Poland (18) Belgium (11), and France (10). The highest amount was reported by Greece (EUR 9 million) and Italy (EUR 8 million), followed by Belgium (EUR 5 million). No cases were reported by 14 Member States . Table TOR1: Cases of smuggled cigarettes in 2021 2.3.1.4. Textiles In 2021, textiles were the goods most vulnerable to fraudulent irregularities in monetary terms. In total 65 cases were reported, amounting to EUR 42 million. Undervaluation was the main type of irregularity. France, Bulgaria and Belgium were particularly affected by fraud, with five other Member States only marginally affected. Anti-fraud services detected most of the cases. 2.3.1.5. Cases reported as fraudulent by amount In 2021, the estimated and established amount was below EUR 100 000 in 345 cases reported as fraudulent (72% of all fraud cases), whereas it was above EUR 100 000 in 137 cases (28%).

The total estimated and established amount in cases reported as fraudulent, where the amount at stake was above EUR 100 000, was EUR 147 million (94% of the total estimated and established amount for cases reported as fraudulent). Table TOR2: Cases reported as fraudulent by amount category in 2021 2.3.2.Cases reported as non-fraudulent 2.3.2.1.Working method A breakdown of fraud by type shows that most cases of fraud relate to classification/misdescription. Incorrect value, incorrect use of preferential arrangements, and irregularities related to the transit procedure are also frequently mentioned. Not all customs procedures are equally vulnerable to irregularities; their vulnerability may change over time as certain economic sectors are briefly targeted. The customs procedure ‘release for free circulation’ is the customs procedure most affected by irregularities. This is because at the time of release for free circulation, non-compliance in the customs declaration may relate to a large number of irregularities, e.g. the tariff, the CN code, (preferential) origin, incorrect value, etc. On the other hand, in customs suspension procedures (such as warehousing, transit, inward processing, etc. – where the payment of duties is suspended) the sole irregularity that might occur is the subtraction of the goods in question from customs supervision. It is therefore normal, and to be expected, that most fraud and irregularities are reported in connection with the procedure ‘release for free circulation’. In 2021 most of the estimated and established amounts in OWNRES for cases reported as non-fraudulent related to the customs procedure ‘release for free circulation’ (84%) . A total of 6% of all estimated and established amounts in OWNRES registered as non-fraudulent for 2021 fall into the category ‘Other’ . Of all cases reported as non-fraudulent, about 60% concern textiles, electrical machinery and equipment, vehicles, plastics, textiles, mechanical machinery and appliances, articles of iron and steel, footwear, organic chemicals and chemical products. In monetary terms these groups of goods represent about 73% of all amounts estimated or established for cases reported as non-fraudulent. China, the United States, Japan, India, Russia, Turkey and Taiwan are – in monetary terms – the main reported countries of origin of goods affected by irregularities. 2.3.2.2. Method of detection of non-fraudulent cases In 2021, most non-fraudulent cases (55%) were detected during post-release customs controls. Other frequently used methods of detection of non-fraudulent cases were release controls (20%), voluntary admission (13%), inspections by anti-fraud services (5%) and tax audits (5%). CHART TOR8: Method of detection 2021 – Cases not reported as fraudulent – by number of cases As regards the estimated or established amounts, around 55% of all irregularities not reported as fraudulent registered for 2021 were detected during a post-release control, 19% during a control at the time of the release of the goods, 12% by voluntary admission, 9% during a tax audit and 5% during an inspection by anti-fraud services. CHART TOR9: Method of detection 2021 – Cases not reported as fraudulent – by estimated and established amounts In 13 Member States, more than 50% of all non-fraudulent cases — in amounts — were detected during post-release controls , whereas in Belgium, Denmark, Luxembourg and Slovakia they were detected during release controls. In Greece, Portugal and Romania more than 50% of the amounts relating to non-fraudulent cases were detected by anti-fraud services. In Finland, 69% of all amounts reported in non-fraudulent cases were reported as voluntary admission. In thirteen Member States voluntary admission was mentioned as a method of detection of cases reported as non-fraudulent , with the highest amounts reported by Germany (EUR 15 million), Finland (EUR 8 million) and Spain (EUR 7 million). 2.3.2.3. Electrical machinery and equipment vulnerable to irregularities In 2021, electrical machinery and equipment (mostly solar panels) were more vulnerable to non-fraudulent reported irregularities in monetary terms than other goods. About 18% (EUR 66 million) of the total amount established in non-fraudulent irregularities concerned this type of good. Of 18 Member States, the Netherlands reported the highest figure (63 cases totalling EUR 45 million). Incorrect classification/misdescription and incorrect value were the prevailing types of irregularity. Post-release controls were the most frequent type of check leading to the detection of irregularities in declarations of imported goods.

2.3.2.4. Cases not reported as fraudulent by amount In 2021, the estimated and established amount was below EUR 100 000 in 3 088 non-fraudulent cases (88%), whereas it was above EUR 100 000 in 418 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 286 million (78% of the total estimated and established amount for non-fraudulent cases). Table TOR3: Cases not reported as fraudulent by amount category in 2021 2.3.3.Fraudulent and non-fraudulent cases and COVID-19 related goods In 2021, imports of COVID-19-related goods continued to increase compared to 2019, but more slowly than in 2020. Analysis of the fraudulent and non-fraudulent irregularities detected in connection with COVID-19 related-goods over the 2017-2021 period shows that the total number of cases (191) detected in 2021 was only 6% higher than the average for the last 5 years (181). However, the related TOR amount (EUR 31 million) doubled in 2021 compared to the average for the years 2017-2021 (EUR 15 million). The impact of irregularities affecting COVID-19-related goods, typically low, remained relatively low in 2021 (5% of the total number of irregularities reported in 2021 and 6% of the related amounts). CHART TOR10: Cases related to COVID-19 goods reported as irregular and the related estimated and established amount (2017-2021) Germany reported the highest number of cases (77). Belgium and Finland reported related amounts of EUR 9.5 million and EUR 8 million respectively. Thirteen other Member States were concerned to a lesser extent. The predominant types of working method were incorrect value and classification/misdescription. Errors in estimating customs duties were also found. A notable increase in the amounts reported as irregular was observed in 2021, in particular for goods such as protective garments (gloves, boot covers, overshoes etc.), disinfectants and sterilisation products and medical consumables. CHART TOR11: Cases related to COVID-19 goods reported as irregular and the related estimated and established amount (2019-2021) 2.4.Member States’ activities 2.4.1.Classification of cases as fraudulent and non-fraudulent and related rates For 2021, Member States reported 482 cases as fraudulent out of a total of3 988 cases reported in OWNRES, indicating a fraud frequency level (FFL) of 12%. The differences between Member States are relatively large. In 2021, 11 Member States categorised between 10% and 50% of all cases reported as fraudulent. However, Luxembourg, Malta, Finland and Sweden 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 2021, the total estimated and established amount affected by fraud in the EU was EUR 157 million and the overall incidence of fraud was 0.63%. For 2021, the highest percentages are in Greece (3.5%), Belgium (3.3%) and Lithuania (2.34%) . The total estimated and established amount affected by cases not reported as fraudulent was nearly EUR 367 million, indicating a non-fraudulent irregularity incidence of 1.48%. The highest percentages are in Finland (5.85%), the Netherlands (3.98%), Latvia (3.56%) and Spain (2.15%) .

There are large differences between Member States’ classifications, partly due to their classification practices. This can affect 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 significantly affect annual rates. Factors such as the type of traffic, type of trade, economic operators’ level of compliance, and a Member State’s location can significantly affect the rates. Bearing these in mind these, the rates of incidence can also be affected by how a Member State’s customs control strategy is set up to target risky imports and detect TOR-related fraud and irregularities. 2.4.2.Recovery rates 2.4.2.1. Cases reported as fraudulent Over the 1989-2021 period, OWNRES shows that, on average, 22% of the initially established amount was corrected (cancelled). The recovery rate for all years (1989-2021) is 40% . The rate for cases reported as fraudulent and detected in 2021 is 20% . The rate for cases reported as fraudulent is in general much lower than 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 27% (1989-2021) of the initially established amount in relation to cases not reported as fraudulent has been corrected (cancelled) since 1989. The recovery rate for non-fraudulent cases reported for 2021 is 60% . On the cut-off date, the annual recovery rate for the last 5 years had varied between 60% and 88%. The overall recovery rate for all years (1989-2021) for all cases not reported as fraudulent is 76% . 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 (Table TOR4). Classification of a case as fraudulent is therefore a strong indicator for forecasting short- and long-term recovery rates. Table TOR4: Historical recovery rate (HRR) 2.4.3.Commission’s monitoring 2.4.3.1. Examination of the write-off reports In 2021, 26 new write-off reports were submitted to the Commission by 9 Member States. The Commission assessed 103 cases totalling EUR 54.8 million in 2021. In 65 of these cases, amounting to EUR 22.5 million , the Commission's view was that the Member States did not demonstrate satisfactorily that the TOR were lost for reasons not imputable to them, so they were considered financially responsible for the loss. Late payment interest totalling EUR 46 million is also due. Examination of Member States’ diligence in write-off cases is a very effective way of gauging their recovery activity. 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 focused on Member States’ customs control strategies. The Commission also closely monitors Member States’ actions and their follow-up on observations made during its inspections. In 2021, Commission services performed TOR inspections (on the spot in Member States or remotely) on: (i) the reliability of the TOR accounts and related statements; (ii) the follow-up on inspections of the customs value control strategy; (iii) the control strategy for anti-dumping and countervailing duties; (iv) the management of the separate account and the corrections of the normal account (refunds of customs duties). During the inspections carried out in 2021, the Commission identified certain shortcomings in national customs systems. These shortcomings, some of which have a potential financial impact, are being followed up and where the Commission considers that cooperation and progress in tackling outstanding issues are insufficient, it is applying corrective measures. As the 2020 PIF report states, such corrective measures have already been applied by the Commission against the UK for undervalued textiles and footwear from China (Snapshot 1). On 8 March 2022, the CJEU issued its ruling in related Case C-213/19 against the UK. The Commission is in the process of analysing the implications of that CJEU ruling both for the UK (e.g. re-calculation of TOR losses) and for the Member States. The Commission also quantified potential TOR losses with regard to the evasion of anti-dumping duties for solar panels and informed the EU Member States concerned.

One general conclusion the Commission has drawn from its inspections in Member States in recent years is that a timely and proactive approach to assessing and monitoring fraud risks is indispensable to effectively protect the EU’s financial interests. This includes using all available sources of information, exchanging information among the services involved and giving prompt feedback on actions taken. Such permanent assessment, exchange of information and monitoring of fraud risks and trends, as well as feedback, is required to fine-tune the measures to be taken and in this way to better protect the EU’s financial interests. 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, making individual Member States responsible for the error. Member States were held financially liable in 2021 for over EUR 86 million, and new cases are being followed up by the Commission. 3.COMMON AGRICULTURAL POLICY Executive summary Section 3 analyses fraudulent and non-fraudulent irregularities reported by the Member States to the Commission through the Irregularity Management System. It focuses on the irregularities related to the Common Agricultural Policy, covering support to agriculture (including direct payments to farmers and market measures) and rural development, during the period 2017-2021. Over the period 2017-2021, the reporting of fraudulent irregularities in relation to rural development increased by 23%. It decreased for the programming period 2007-2013, as expected, and had a slow start for the programming period 2014-2020, which might indicate insufficient detection work in the Member States. The level of fraud detected for support to agriculture was rather stable, even if in 2021 the number of fraudulent iregularities decreased by 17% with respect to 2020. Over the period 2017-2021, the rural development part of the budget was more affected by fraud than support to agriculture, as a proportion of the payments received by the Member States. However, the incidence of fraud for market measures was even higher than for rural development. Direct aid to farmers accounted for most payments, but the incidence of fraud was low, as it is entitlement-based and there are systems in place to support prevention. Similar patterns applied to non-fraudulent irregularities. Over the past years, the detection of fraud was concentrated in a few Member States and this was not substantiated by a similar level of concentration in related payments. Differences in the quality of prevention or detection work carried out or different approaches taken to criminal investigation may contribute to this. Over the period 2017-2021, fraud in support to agriculture most often concerned the documentary proof. Fraudulent irregularities concerning the request were also recurrent. In most cases, these irregularities concerning documentary proof or request were due to falsification. In the case of direct payments, most of these violations were concentrated in two Member States. A wide range of documents and information can be falsified, such as lease agreements, property documents, compliance with the conditionality requirements. Concerning fraud about ‘product, species or land’, over or fictitious declarations were frequently detected. When fraud in support to agriculture concerned the implementation of the action, it was related to market measures, often in combination with other violations. High financial amounts were recorded in several cases investigated by OLAF where conflict of interest was combined with other violations, in relation to the market measure ‘Promotion’. The creation of artificial conditions for the purpose of receiving financial support is a potential risk. For example, beneficiaries may artificially split agricultural holdings and request aid via several linked companies, to avoid degressive aid rates or limits in terms of area or animals. In terms of rural development fraud, fraudsters mainly used the practice of falsifying documents. For example, this may involve falsifying invoices, declarations of equipment as new while it is second-hand, bids in procurement procedures, or false information provided on compliance with the conditions for receiving the aid. A significant number of fraudulent irregularities concerned failure to fully implement the action. The creation of artificial conditions is a potential risk also for rural development funding. Concerning market measures, the highest number of fraudulent irregularities concerned national support programmes for the wine sector, in particular investment measures and the restructuring and conversion of vineyards. The highest total financial amounts involved in fraud were related to the fruits and vegetables sector, where fraud most often concerned aid to producer groups for preliminary recognition, both measures concerning formation/administrative operation and measures concerning investment, sometimes together in the same case. The financial amounts involved were high also for the market measure specifically related to the promotion of agricultural products. With reference to rural development and direct payments to farmers, risk analysis and spontaneous information from civil society, including from the media, have a marginal contribution in detecting fraudulent and non-fraudulent irregularities. In relation to market measures, risk analysis has a stronger role in detection, including because of the risk-based scrutiny of commercial documents of those entities receiving payments. After about 10 years from initial reporting, the share of cases of suspected fraud that have not led to conviction remains very high, while the share of cases in which fraud is established is low. This may signal the need to invest further in reporting suspected fraud and in the investigation/prosecution phase.



3.1.Introduction Section 3 presents a statistical evaluation of irregularities and fraud detected by the Member States in 2021 in expenditure under the common agricultural policy (CAP). It provides context to these detections by looking at past years and relevant programming periods (PP). The Member States reported these irregularities and cases of fraud to the Commission through the Irregularity Management System (IMS). Over the period 2017-2021, the CAP’s overarching objectives were (i) viable food production; (ii) sustainable management of natural resources and climate action; (iii) balanced territorial development. Over 99% of expenditure was disbursed by Member States under shared management.

For the purpose of this analysis, the CAP is split into two main parts: oSupport to agriculture (SA), by providing direct aid to farmers (DA) and measures to respond to market disturbances (MM), such as private or public storage and export refunds. The European Agricultural Guarantee Fund (EAGF) finances these actions. oRural development (RD) programmes run by the Member States. The European Agricultural Fund for Rural Development (EAFRD) finances these programmes. The European Maritime and Fisheries Fund (EMFF) provides funding and technical support to make the fishery industry more sustainable. However, EMFF is analysed together with the other structural funds, as it belongs to the ESIF (European Structural and Investment Funds) family of funding (see Section 4). Table NR1 below shows the 2021 budget for the CAP, which represents about 33% of the EU budget. Graph NR1 below shows the relative weight of different components of the CAP on payments and on the financial amounts involved in all CAP irregularities. In 2021, rural development represented 26% of CAP payments, but 48% of the financial amounts involved in CAP irregularities. This difference in the percentage of payments and the percentage of irregular amounts was even more pronounced for market measures, which accounted for just 5% of payments and 42% of irregularities in terms of financial amounts. Instead, direct aid absorbed most of the CAP payments (70%), but accounted for less than 10% of the irregularities in terms of the financial amounts involved. The European Commission is responsible for managing the EAGF and the EAFRD. However, the Commission does not pay the beneficiaries itself. Under the principle of shared management, this task is delegated to the Member States, who make the payments via national or regional paying agencies. Before these paying agencies can claim any expenditure from the EU budget, they must be accredited on the basis of a set of criteria laid down by the Commission. Before making payments, these paying agencies must also, either directly or via delegated bodies, ensure that the aid applications are eligible. The checks they must carry out are laid down in the CAP sectorial regulations and vary from one sector to another. Specific national authorities are competent for rural development operations. The Commission reimburses the Member States the expenditure made by the paying agencies. EAGF reimbursements are made on a monthly basis and EAFRD on a quarterly basis. Though entitlements and measures supported under the EAGF follow a yearly flow, those under the EAFRD are implemented through multiannual programmes, as action financed by other ESI Funds. In general, reimbursements are subject to possible financial corrections by the Commission, under the clearance of accounts procedures. This report is structured as follows. Section 3.2 elaborates on general trends, broken down by fraudulent and non-fraudulent irregularities. Section 3.3 details more specific analyses (i) on the types of irregularities; (ii) on the detection rates by CAP component; (iii) on the irregularities affecting market measures; (iv) on risk analysis and spontaneous reporting. Section 3.4 focuses on the anti-fraud activities carried out and results obtained by the Member States, including analysing the fraud and irregularity detection rates (the ratio between the amounts involved in cases reported as fraudulent (FDR) or not reported as fraudulent (IDR) and the payments made during the same period of time). 3.2.General analysis 3.2.1.Irregularities reported in the years 2017-2021 The analysis in Section 3 refers to the EU-27, unless specified otherwise. UK data is added in the tables, as specified, to give a complete picture. However, the accompanying analysis focuses on the current Member States and EU-27 in aggregate. In the whole section, when reference is made to ‘fraudulent’ or ‘fraud’, this includes both ‘suspected fraud’ and ‘established fraud’. Member States are requested to communicate: ·non-fraudulent irregularities only when they are detected after the expenditure has been introduced in a statement submitted to the Commission. This derogation does not apply to fraudulent irregularities: Member States must always report them. ·fraudulent and non-fraudulent irregularities involving financial amounts above EUR 10 000. From 2017-2021, several Member States also reported several irregularities under this threshold. However, these cases represented only about 1% and 3% of the number of irregularities reported as non-fraudulent and fraudulent, respectively. To use all information reported by the Member States, they are included in the analysis for this section.

3.2.2.Irregularities reported as fraudulent Table NR2 below provides an overview of the number of irregularities reported as fraudulent by the Member States, broken down by the type of support, from 2017-2021. The number of irregularities found in rural development spending decreased during 2018 and 2019 (by 25%) and then bounced back during 2020 and 2021. As a result, during the overall period 2017-2021, fraudulent irregularities detected and reported for rural development increased by 23%. The irregularities found under support to agriculture were rather stable during 2018-2020. In 2021, there was a decrease of about 17% with respect to the previous year. This pattern resulted in an overall decrease of about 30% for irregularities detected and reported for support to agriculture, during the 5-year period. The irregularities in rural development expenditure reported for 2017-2021 concerned both PP 2007-2013 and PP 2014-2020. The number of rural development cases related to PP 2007-2013 fell sharply in 2017, which was to be expected, given that the PP closed in 2015. Since then, the number of PP 2007-2013 cases has been rather stable, but still higher than the number of PP 2014-2020 cases. The start of detections related to PP 2014-2020 has been rather slow. For PP 2014-2020, the slow start of reporting should be closely monitored to ensure it is not due to less of a focus on fraud detection. Graph NR2 below compares the first eight years of PP 2007-2013 (2007-2014) with the first eight years of PP 2014-2020 (2014-2021), in terms of number of non-fraudulent irregularities detected and reported by the Member States. Graph NR3 below extends the comparison to the financial amounts involved. The gap between the two programming periods is clear since the beginning and is significantly increasing. As shown in Table NR2 above, several irregularities were classified SA/RD, meaning that they were related to both components of the CAP. Basically, in all of these irregularities, irregularities in rural development expenditure were found in combination with irregularities in direct aid to farmers. The detection of fraudulent irregularities was concentrated in a few Member States. From 2017-2021, the irregularities notified by the top five Member States in terms of cases reported represented about 70% of all irregularities reported as fraudulent (85% of financial amounts). In 2021, this rose to 85%, in terms of number of irregularities and more than 95%, in terms of financial amounts involved. A deeper analysis of concentration was included in the 2018 PIF Report. That analysis found that the concentration of detections went beyond what could be expected given the level of concentration of payments. This could be due to many different factors, including different underlying levels of irregularities and fraud, differences in the quality of the prevention or detection work or different practices concerning the stage of the procedure when potentially fraudulent irregularities are reported. The concentration of detections was more accentuated for fraudulent rather than for non-fraudulent irregularities. This suggests that different approaches to criminal investigation and prosecution could be an additional and significant factor giving rise to these different levels of detection across the Member States. The graph attached to Table NR3 below shows the trend of financial amounts involved in irregularities reported as fraudulent. For rural development irregularities, similar to the trend in terms of number of detections, the financial amounts involved fell in 2017. Since then, these financial amounts have been fluctuating around a 5-year average of about EUR 17 million. The trend in the financial amounts involved in support to agriculture was heavily influenced by two cases concerning market measures, worth between EUR 20 and 30 million each, which Poland detected in 2017 and 2018. This is the reason for the much higher financial amounts found over these two years. Excluding these two irregularities, the irregular financial amounts detected in relation to support to agriculture were rather stable, reaching a record low in 2020, but bouncing back to the 5-year average (about EUR 13 million) in 2021. Over the period 2017-2021, 55% of the irregular financial amounts involved were in support to agriculture irregularities, and 42% were for rural development irregularities. However, over the same period, rural development payments represented just 26% of the CAP budget. Therefore, rural development expenditure was more affected by fraud than support to agriculture expenditure. This is analysed further in Section 3.3.2., through the fraud detection rate, distinguishing between direct aid to farmers and market measures. An analysis covering the period 2015-2019, included in the 2019 PIF Report, shows that in most fraudulent irregularities, the ‘persons involved’ were legal entities. Most of them were private companies, followed by non-profit organisations, in particular associations. For a significant one third of cases, the ‘persons involved’ were natural persons. Most of the fraudulent irregularities involved a single entity. 3.2.3. Irregularities not reported as fraudulent Table NR4 below provides an overview of the number of irregularities not reported as fraudulent by the Member States, broken down by the type of support, from 2017-2021. The number of rural development irregularities not reported as fraudulent increased constantly until 2015, in line with implementation of the programmes, while the number of irregularities related to support to agriculture remained stable. Since then, non-fraudulent irregularites in rural development fell sharply until 2017, were rather stable in 2018-2019, and started increasing again in 2020-2021, in line with progress in the implemention of PP 2014‑2020.

Table NR5 below focuses on the financial amounts involved in these irregularities. The irregular financial amounts in rural development also peaked in 2015, then started to fall. This trend reversed in 2020, in line with the increase in the number of detected and reported irregularities during 2020-2021. The irregular financial amounts in support to agriculture fluctuated strongly around an annual average of about EUR 77 million. This was mainly due to the fact that cases involving over EUR 15 million each were reported in 2017 (one case in Romania), 2019 (two cases in Poland) and 2021 (one case in Poland, accounting for nearly EUR 40 million) but none were detected in 2018 and 2020. All of these irregularities were related to interventions in the agricultural markets. The number of non-fraudulent irregularities in spending on rural development regularly and significantly exceeded the number on support to agriculture, over the entire 2017-2021 period. As a result, the number of irregularities in rural development were over double the number affecting support to agriculture. Non-fradulent irregularities in rural development also exceeded those in support to agriculture in terms of the financial amounts involved, but only by 16%. Irregularities in rural development spending were found in both PP 2007-2013 and PP 2014-2020. On the one hand, the number of rural development cases related to PP 2007-2013 fell sharply during 2017-2019, which was to be expected, considering that this programming period closed in 2015. Since then, there were still detections of PP 2007-2013 cases and they have been following a stable trend. On the other hand, the Member States started reporting detections related to PP 2014-2020, following an accelerating trend, reflecting progress in the implementation under this programming period. For PP 2014-2020, the reporting dynamics are broadly in line with those at the start of the previous programming period. Graph NR4 below compares the first eight years of PP 2007-2013 (2007-2014) with the first eight years of PP 2014-2020 (2014-2021), in terms of number of non-fraudulent irregularities detected and reported by the Member States. Graph NR5 below extends the comparison to the financial amounts involved. There is a gap between the two programming periods, but it is much narrower than that related to fraudulent irregularities. As shown in Table NR4 above, several irregularities were classified as SA/RD, meaning that they were related to both components of the CAP. Basically, in all these cases, irregularities in rural development spending were combined with infringements concerning direct aid to farmers. 3.3.Specific analysis 3.3.1.Modus operandi 3.3.1.1. Support to agriculture Table NR6 below provides an overview of the most frequent categories (or combinations of categories) of irregularities linked to cases reported as fraudulent in relation to support to agriculture in 2021 and the financial amounts involved. It also gives the figures over the period 2017-2021. In the following paragraphs, the adjective ‘pure’ is used to refer to cases where a specific category of irregularity is not combined with other categories. The irregularities reported in 2021 mainly concerned the documentary proof. Over the whole period 2017-2021, irregularities concerning the request were also recurrent. Both in relation to direct payments to farmers and market measures, most of these violations concerned falsification. In the case of direct payments, most of these violations were concentrated in two Member States (Romania, for violations concerning the documentary proof, and Italy, for violations concerning the request). A wide range of documents and information can be falsified, such as lease agreements, property documents, compliance with the conditionality requirements. Over the period 2017-2021, the Member States detected few fraudulent cases of ‘pure’ ‘(non) action’. These cases accounted for the second highest financial amount involved, but this was influenced by one irregularity related to market measures that accounted for more than EUR 20 million (out of EUR 26 million). Nearly all of these ‘pure’ ‘non-action’ violations concerned market measures. In addition, ‘(non-)action’ had a tendency to take place in combination with other violations, concerning for example the documentary proof, the request, ethics and integrity. Also all of these irregularities concerned market measures. Examples of fraudulent irregularities reported as ‘(non-action)’ in relation to market measures Example 1: The beneficiary submitted an application for support concerning the withdrawal from the market of a specified quantity of a specific agricultural product. These agricultural products should have been transferred to a charitable organisation, but this never took place. Example 2: The beneficiary received aid for the reduction of milk production, following false declarations about the leasing/sale of part of the cows to other farmers. Actually, there was no reduction in the milk deliveries by the beneficiary. In another case, despite the declaration of reduction of milk production, the milk was still produced on the beneficiary’s farm and delivered to the first purchaser through another person linked to the beneficiary. In another case, there was only a formal relocation of part of the production among members of the same producer group. Irregularities in the category ‘pure’ 'product, species and/or land' were more frequently detected, mostly in relation to direct aid to farmers. The majority of these violations concerned 'overdeclaration and/or declaration of fictitious product, species and/or land'.

Examples of fraudulent irregularities reported as ‘overdeclaration and/or declaration of fictitious product, species and/or land’ in relation to direct aid to farmers Example 1: The beneficiary declared ownership of a plot of land. However, this plot was owned by a public agency. Example 2: The beneficiary requested direct payments in relation to the use of a number of plots of land. Cross-checks revealed that these plots were declared for payment also by other beneficiaries. In another case, the beneficiary requested aid for plots of land that he had leased to another person. In another case, the beneficiary requested aid in relation to land he was not using. The lease agreement submitted with the application did not match with the contract submitted by the lessor at the request of the paying agency. In another case, the leasee did not carry out the agricultural activities he was supposed to carry out on the declared land. The application had been made just to obtain the subsidies, which were transferred to the lessor, who was the legal representative of the leasee. Over the whole period 2017-2021, 22 irregularities were reported in the category ‘pure’ 'ethics and integrity'. All of these irregularities were communicated by Poland and were not reported under the types 'conflict of interest', 'bribery' or 'corruption', but as 'other irregularities concerning ethics and integrity'. Most concerned the creation of artificial conditions for receiving financial support and direct aid to farmers. For example, beneficiaries may artificially split agricultural holdings and request aid through several linked companies, to avoid degressive aid rates or limits in terms of area or animals. Other Member States may have reported this type of infringement under other categories. Two irregularities concerned instead market measures and they involved the highest financial amounts. One of these irregularities included overstating costs for assets transferred among members of the same group of producers. Examples of fraudulent irregularities related to the creation of artificial conditions Example 1: The beneficiary submitted several applications as a natural person and as manager of a number of companies. There were personal and family links between the beneficiary and the other entities applying for payments. This was meant to circumvent rules about degressive rates of support. Example 2: The beneficiary established legal entities with personal, capital, family and business links, to obtain direct payments exceeding the maximum ceilings per beneficiary. High average financial amounts (about EUR 1.8 million) were recorded in several cases of conflict of interests combined with other violations (8 irregularities). In 2019, Czechia reported two irregularities related to corruption, in combination with public procurement infringements (conflict of interests) and failure to implement the action. In five irregularities reported by Bulgaria in 2018, conflict of interests was combined with violations concerning the ‘beneficiary’ (mostly not having the required quality) and ‘(non) action’ (infringements relating to the cofinancing system). In another case detected in Bulgaria, a conflict of interests was combined with violations concerning the ‘beneficiary’ (not having the required quality) and ‘accounts & records’ (revenues not declared). All of these eight irregularities were related to the market measure ‘promotion’ (see Section 3.3.3) and were investigated by OLAF. The investigations uncovered complex fraudulent schemes, mainly based on price inflation, kickback payments and money laundering. The public procurement procedures were breached through a solid network of companies based in different countries. In some cases, the manipulation was possible also due to the collusion of the beneficiaries. Table NR7 below provides an overview of the most frequent categories (or combinations of categories) of irregularities linked to cases not reported as fraudulent in support to agriculture expenditure in 2021 and the financial amounts involved. It also gives the total for these categories (or combinations of categories) for the period 2017-2021. Irregularities due only to the 'request' (pure) were by far the most recurrent category during 2017-2021, most of the times related to direct payments to farmes. However, during the last year, violations concerning the category 'documentary proof' were the most frequent, with a significant increase compared with the previous four years. Concerning the category ‘request’ in relation to direct payments to farmers, during 2017-2021, the most recurrent type of violation by far was 'false or falsified request for aid', followed by 'incorrect or incomplete request for aid'. This rate of irregularities related to falsification would not be expected for non-fraudulent irregularities. During 2021, about one third of the violations concernig the request in support to agriculture were related to market measures, which was much more than before. In general, when violations concerning the request concerned market measure, the specific infringement was about 'product, species, project and/or activity not eligible for aid'. Concerning the category ‘documentary proof’, more than half of this type of violations reported during the past five years have been detected in 2021, with a three-fold increase compared to 2020, which had already doubled the detections from 2019. The vast majority of these infrigements reported in 2021 were detected in Greece in relation to direct payments to farmers and concerned documents that were incomplete or incorrect. During 2017-2021, the violations related to direct payments to farmers were still the majority, but the infringement related to market measures were more recurrent than during 2021. In general, during 2017-2021, there were a few cases related to false or falsified documents, which would not be expected for non-fraudulent irregularities. During 2017-2021, the highest irregular financial amounts were due to infringements concerning ‘(non) action’. The vast majority of these irregularities were related to market measures. About 27% of the irregular financial amounts reported over the past five years for ‘(non) action’ were due to two irregularities related to market measures, totalling about EUR 36 million. Focusing on the irregularities related to market measures, the highest financial amounts were involved in cases where the action was not implemented and in cases where the beneficiary carried out an operation that was prohibited during the measure. The most reported violations were about actions not implemented or not completed. Focusing on the irregularities related to direct payments to farmers, the financial amounts involved were low and most of the violation concerned the action not implemented or not completed. During the last year, the financial amounts related to violations concerning the category 'beneficiary' were the highest, with a significant increase compared with the previous four years. The high financial amounts concerned irregularities related to market measures. The vast majority of violations were instead related to direct payments to farmers and were about 'operator/beneficiary not having the required quality'. However, this prevalence in terms of numbers is less significant if also irregularities are considered where these violations were combined with other infringements, especially concerning ‘(non‑)action’, which were basically always related to market measures. Concerning irregularities related to market measures, half of the ‘pure’ ‘beneficiary’ cases and basically all of the cases where there is a combination of other types of infringements concerned 'operator/beneficiary not having the required quality'. Other recurrent categories of irregularities in support to agriculture expenditure not reported as fraudulent were related to 'product, species and/or land', or 'ethics and integrity' (not combined with other categories of irregularity). The majority of the violations concerning 'product, species and/or land' were related to direct payments to farmers. In this case, the most reported violation was 'overdeclaration and/or declaration of fictitious product, species and/or land' When these irregularities concerned market measures, the most reported violation was ‘inexact quantity’. Concerning 'ethics and integrity', 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 Table NR8 below provides an overview of the most frequent categories of irregularities reported as fraudulent in rural development expenditure in 2021 and the corresponding financial amounts. It also gives the total for these categories over the period 2017-2021. Similar to the findings for support to agriculture, there were mainly cases of ‘pure’ falsification of the documentary proof or, to a lesser extent, of requests for aid. Falsification may concern, for example, invoices, declarations of equipment as new while it is second-hand, bids in the context of procurement, and information on compliance with conditions for receiving the aid. The pure category 'documentary proof' was by far the most reported, most often because of false or falsified documents. The category pure 'request' was another frequent category, most often in relation to false or falsified requests of aid. Examples of fraudulent irregularities related to the documentary proof Example 1: The beneficiary simulated a procurement procedure in relation to the purchase of agricultural equipment. In reality, the beneficiary directly bought the equipment and the company selected through the simulated procurement procedure issued a false invoice for the same equipment. In addition, the equipment was supposed to be new, while it was second-hand. To hide this, false manufacturer labels were attached to the equipment. Example 2: To get the reimbursement of expenditure under the EU funded project, the beneficiary had to attach two offers for the same item, to evidence that the price was reasonable. For many items, offers were received from company A and company B, always in competition among each other. However, company A did not exist; business information and employees from company B were used in the false offers of the inexistent company A. Example 3: To receive an advanced payment, the beneficiary had to attach a guarantee from a financial institution. Checks with the financial institution ascertained that the financial institution had never issued that guarantee, which was therefore false. Example 4: The beneficiary declared that a building funded by the EU was used for the sale of agricultural products, while it was used as home by the beneficiary. A significant number of detections and irregular financial amounts were related to pure '(non) action'. Under this category, from 2017-2021, the most reported type of violation was about actions not implemented. Examples of fraudulent irregularities related to the implementation of the action Example 1: The beneficiary did not fully implement the construction works envisaged in the business plan and did not increase to number of jobs. Example 2: The beneficiary did not use the accomodation built with the support of the EU fund for renting to the public. The beneficiary used it for private purposes, without advertising the availability of the accomodation. Example 3: The beneficiary re-sold the agricultural vehicle bought with the support of EU funds, instead of using it during the operating period. The category pure ‘ethics and integrity’ accounted for 34 irregularities found during 2017-2021.Similar to support to agriculture cases, Poland communicated most of these violations and they were not reported under the types 'conflict of interest', 'bribery' or 'corruption', but as 'other irregularities concerning ethics and integrity'. Most of these violations concerned the creation of artificial conditions for receiving financial support. Other Member States may have reported this type of infringement under other categories of irregularity, such as the one referring to the beneficiary (for example, using the the type of violation 'operator/beneficiary not having the required quality' or ‘other’). Example of fraudulent irregularities related to the creation of artificial conditions The beneficiary created false information about having had revenue from the sale of self-produced agricultural products or products resulting from their processing in the period prior to the application. This was needed to qualify for the support.

Table NR9 below provides an overview of the most frequent categories of irregularities not reported as fraudulent in rural development expenditure in 2021 and the corresponding financial amounts. It also gives the total for these categories over the period 2017-2021. The highest number of detections and irregular financial amounts were related to pure '(non) action', in particular action not completed, action not implemented, or failure to respect deadlines. Violations concerning 'documentary proof' alone (pure) or the ‘beneficiary’ were also recurrent. They were also often combined with the category ‘(non) action’ and with each other. Over the period 2017-2021, the number of infringements related to 'documentary proof' followed that of infringements concerning ‘(non) action', most often because of missing documents. However, during 2017-2021, false and/or falsified documents were reported in a number of cases (about 50, including where combined with other violations), which would not be expected for non-fraudulent irregularities. The same applies to the category 'request', with a number of cases of falsification (about 20). The category pure ‘beneficiary’ was the third most frequent during 2017-2021 and the second in 2021, most often because of the beneficiary not having the required quality. Most of the violations concerning product, species and/or land were due to over or fictitious declarations. There were just a few reported cases of conflict of interest. There was one pure case of conflict of interest. In addition, there were eight other cases of conflict of interest in procurement. In 2020, one Member State reported a multi-million irregularity in rural development expenditure related to conflict of interest, corruption, use of false documents and accounts. Reporting as non-fraudulent would not be expected, but the Member State also communicated that penal proceedings were ongoing. Apart from these cases, infringements related to 'ethics and integrity' were reported as 'other'. 3.3.2.Fraud and Irregularity Detection Rates (FDR and IDR) by CAP components Table NR10 below shows the FDR and IDR per type of policy measure. Detection rates for support to agriculture were much lower than for rural development. However, one part of support to agriculture, interventions in agricultural markets (market measures), accounted for the highest FDR and IDR. It could be argued that this comparison is biased by a few cases related to market measures (two fraudulent and three non-fraudulent) involving exceptionally high financial amounts (more than EUR 10 million each). However, even excluding these irregularities from the calculation, the FDR and IDR for market measures were the highest, at 0.34% and 1.46%, respectively. The detection rates for direct payments to farmers were much lower. 3.3.3.Market measures – fraudulent and non-fraudulent irregularities As shown in Table NR10 above, the FDR and IDR of market measures are high. Table NR11 below shows the number and financial amounts of irregularities reported as fraudulent in relation to market measures for the period 2017-2021, while Table NR12 below shows the same data on irregularities that were not reported as fraudulent. Fraudulent and non-fraudulent irregularities involving the highest financial amounts are often related to market measures. From 2017-2021, Poland reported two fraudulent irregularities related to aid to producer groups for preliminary recognition in the ‘fruits and vegetables’ sector, accounting for over EUR 20 million each. This type of aid was also subject to three non-fraudulent irregularities, accounting together for over EUR 75 million (all reported by Poland). Another non-fraudulent irregularity involving about EUR 19 million affected a food programme for deprived persons. The highest number of irregularities reported as fraudulent were related to national support programmes for the wine sector. Irregularities affected in particular investment measures and the restructuring and conversion of vineyards. However, fraud hit also promotion measures, including in non-EU markets. The highest financial amounts were involved in fraudulent irregularities related to ‘fruits and vegetables’. In this domain, the two above-mentioned cases reported by Poland contributed to the high financial amounts related to aid for producer groups for preliminary recognition. One of these cases concerned expenditure for investment, but also the budget for formation and administrative operation was affected. In general, fraud touched both measures concerning formation/administrative operation and measures concerning investment, sometimes together in the same case.

The financial amounts involved were high also for the market measure specifically related to the promotion of agricultural products. Fraud affected both promotion in the EU markets and in third countries, with higher irregular financial amounts involved in the latter. Fraud affected also the school schemes and market measures related to milk and milk products. For irregularities not reported as fraudulent, the category 'products of the wine-growing sector' was the most frequently reported. Most of the times, non-fraudulent irregularities concerned the restructuring and conversion of vineyards. Also irregularities related to investments were frequently reported. When promotion measures were concerned, the majority of cases were related to promotion in third countries. Promotion of agricultural products was affected by non-fraudulent irregularities also when not related to the wine sector. In this case, the majority of irregularities concerned promotion within the EU. The highest financial amounts were involved in non-fraudultent irregularities related to 'fruit and vegetables'. In particular, this was due to irregularities related to aid to producer groups for preliminary recognition. They concerned both investments and formation/administrative operation, sometimes together in the same irregularity. Even more frequent than irregularities related to aid for preliminary recognition were irregularities concerning operational funds for producers organisations. Programmes of Option Specifically Relating to Remoteness and Insularity (POSEI) were often affected by non-fraudulent irregularities. Most of the times, this was linked to supply arrangement or other measures. The school schemes were also not free from non-fraudulent irregularities, in particular concerning the supply and distribution of the products. The majority of cases were related to fruit and vegetables. The category 'Food programmes' was impacted by few irregularities, but high financial amounts. As mentioned, one single non-fraudulent irregularity accounted for EUR 19 million. 3.3.4.Risk analysis and spontaneous reporting Detection capability is a key feature of the anti-fraud cycle, which contributes to the effectiveness and efficiency of the system for the protection of the EU budget. In the 2017 PIF Report, to boost the capability to detect irregularities, the Commission recommended to the Member States to improve risk analysis and the use of spontaneous reporting of potential irregularities and strengthening the protection of whistle blowers that are also a crucial source for investigative journalism. With a focus on checks that led to discovering reported irregularities, Tables NR13-NR18 below provide information on the number of checks that were carried out due to reasons that can be linked to these recommendations. So far, there has been little improvement on the ground (see Tables NR13-NR18 below). It may take time to evolve effectively from reactive to proactive detections based on risk analyses. It should also be considered that non-fraudulent irregularities that are detected and corrected at the national level before including the expenditure in a statement submitted to the Commission for reimbursement do not have to be reported. Therefore, if risk analyses have a higher impact in terms of ‘early’ detection of these irregularities, it would not be captured by Tables NR13-NR18 below. By contrast, this exception does not apply to fraudulent irregularities, which should always be reported, even when detected before expenditure is submitted to the Commission. 3.3.4.1.Irregularities in relation to rural development With reference to rural development, risk analysis has still a marginal contribution to detecting fraud. In addition, during the past five years, just 5% of the fraudulent irregularities were detected following tips (e.g. from whistle blowers) or information published in the media (see Table NR13 below). Table NR14 below focuses on irregularities not reported as fraudulent in rural development. Risk analysis contribute to a higher share of detections than for fraudulent irregularities, but this share is still very low. Also the share of non-fraudulent irregularities detected following tips or information published in the media is negligible. 3.3.4.2. Irregularities in relation to market measures

In relation to market measures, risk analysis has a stronger role in detecting fraudulent irregularities than in other CAP sectors. This is influenced the overall low number of cases. However, about 11% of fraudulent irregularities were detected because of risk analysis. In addition, the categories 'scrutiny 4045', ‘scrutiny 485' and ‘scrutiny 1306’ refer to Regulation No 4045/1989, Regulation No 485/2008 and Regulation No 1306/2013, respectively. These deal with the scrutiny of commercial documents of those entities receiving payments from the Guarantee section of the EAGGF (Reg. No 4045/1989) or from the EAGF (Reg. No 485/2008 and Reg. No 1306/2013). These regulations provide for checks based on the assessment of the risks. Regulation No 4045/1989 already required the Member States to consider risk factors and concentrate on sectors or undertakings where the risk of fraud is high. Taken together, these scrutinies accounted for more than 25% of detections. About 7% of the fraudulent irregularities were detected following tips, which is similar to other CAP sectors. The contribution of information published in the media was nil. Also for non-fraudulent irregularities, risk analysis seem to play a more important role in detection than in other CAP sectors. Risk analysis and risk-based scrutiny accounted for about 25% of cases. The share of irregularities detected following tips or information published in the media was negligible, as in other CAP sectors. 3.3.4.3. Irregularities in relation to direct payments With reference to direct payments to farmers, risk analysis has still a marginal contribution in detecting fraud and non-fraudulent irregularities. In addition, during the past five years, just 2-3% of the fraudulent and non-fraudulent irregularities were detected following tips (e.g. from whistle blowers) (see Tables NR17 and NR18 below) and never following information from media. 3.4.Anti-fraud work carried out by the Member States Previous sections have examined the trend and main features and characteristics of the irregularities reported as fraudulent. This section focuses on some aspects linked to the anti-fraud work carried out and results obtained by the Member States in particular. It analyses four aspects: (1)Duration of irregularities (fraudulent and non-fraudulent). No analysis by Member State is presented in this section. (2)The number of irregularities reported as fraudulent by each Member State (in 2021 and over the past five years). (3)the FDR (the ratio between the amounts involved in cases reported as fraudulent and the payments made over the same period) and the IDR (the ratio between the amounts involved in cases not reported as fraudulent and the payments made over same period) over the past five years; (4)the follow-up to suspected fraud. 3.4.1.Duration of irregularities The Member States are requested to indicate the date or period when the irregularity was committed. Of the 15 549 irregularities (fraudulent and non-fraudulent) reported by Member States in 2017-2021 in relation to the CAP, 9 057 (58% of the total) involved irregularities that were protracted over a span of time. For the 1 233 irregularities reported as fraudulent, this rises to 76%. About 41% of the irregularities consisted of a single act identifiable on a precise date (about and 24% of the fraudulent irregularities). The average duration of the irregularities that were protracted over time was 26 months (two years and two months). For the irregularities reported as fraudulent, the average was one month less: 25 months.

3.4.2.Detection of irregularities reported as fraudulent by Member State 3.4.2.1. Reported over the period 2017-2021 Table NR19 below gives an overview of the irregularities reported as fraudulent by the Member States over the period 2017-2021. It also shows the related amounts, overall payments under the agricultural policy and the FDR. Belgium, Cyprus and Malta have notified no irregularities as fraudulent. 15 other Member States reported fewer than 30 potentially fraudulent irregularities; six Member States reported between 30 and 60; and three Member States reported over 60. The FDRs exceeded 0.5% in Estonia and 0.30% in Romania and Bulgaria. Romania was the Member State that accounted for the highest number of irregularities, and Poland reported the highest financial amounts involved. 3.4.2.2.Reported in 2021 Table NR20 below gives an overview of the irregularities reported as fraudulent in 2021, broken down by Member State. It also shows the related amounts, overall payments for the common agricultural policy and the FDR. Nine Member States reported no irregularities as fraudulent. Most Member States reported fewer than 30 fraudulent irregularities; only Romania reported over 30 fraudulent irregularities. The highest FDR was recorded in Estonia. Romania reported the highest number of irregularities and related financial amounts. 3.4.3.Fraud and Irregularity Detection by sector and Member State 3.4.3.1. Rural development Table NR21 and Map NR1 below provide an overview of the irregularities reported as fraudulent by the Member States over the period 2017-2021 for rural development expenditure. It also shows the total payments made for rural development and the FDR. As mentioned, the irregularities refer exclusively to the rural development component.

Estonia, Denmark and Romania recorded the highest FDR. The FDR was higher than the EU average also in Lithuania and Italy. 23 Member States reported fraudulent cases concerning rural development spending over the period 2017-2021. Romania and Poland reported the highest number of cases, and Romania reported the highest financial amounts involved. In this map, the FDR ‘0.00’ indicates low financial amounts involved in the irregularities, in proportion to the payments received. If no relevant irregularities were reported, no FDR is mentioned in the map for the relevant Member State. See Table NR21. UK is not included. Table NR22 and Map NR2 below provide an overview of the irregularities not reported as fraudulent by the Member States over the period 2017-2021 concerning rural development expenditure. Table NR22 below also shows the total payments for rural development and the IDR. Bulgaria, Portugal and and Malta recorded the highest IDR. The IDR was higher than the EU average also in Romania, Lithuania, Estonia, Slovakia, Italy and Hungary. Portugal and Romania reported the highest number of cases, and Romania, Portugal, Italy and Bulgaria reported the highest financial amounts involved. If no relevant irregularities were reported, no IDR is mentioned in the map for the relevant Member State. See Table NR22. UK is not included. Tables NR21 and NR22 above indicate that the reporting of irregularities was concentrated in a few Member States. The top two Member States in terms of number of detections (Romania and Poland) reported 51% of all fraudulent irregularities related to rural development (57% in terms of the financial amounts involved), while they received about 18% of payments. For non-fraudulent irregularities, the top two Member States (Romania and Portugal) reported 30% of cases and 37% of the financial amounts involved, but received about 14% of payments. The concentration of detections was analysed in detail in the 2018 PIF Report for the period 2014-2018. The analysis suggests that the concentration of detections went beyond what could be expected from the concentration of payments related to rural development among Member States. This could be due to many different factors, including different underlying levels of irregularities and fraud, differences in the quality of prevention or detection work or different practices concerning the stage of the procedure when potentially fraudulent irregularities were reported. This difference in concentration between detections and payments was less pronounced for non-fraudulent irregularities, which could be taken as an indication of more uniform approaches to management and administrative checks, although data on individual Member States highlighted significant discrepancies. The concentration of detections was instead more accentuated for fraudulent irregularities, suggesting that different approaches to criminal investigation and prosecution could be an additional and significant factor explaining the different levels of detection among Member States. 3.4.3.2. Market measures Table NR23 and Map NR3 below provide an overview of the irregularities reported as fraudulent by the Member States over the period 2017-2021 for market measures expenditure. The table also gives the total payments for market measures and the FDR.

FDR was the highest in Poland and Bulgaria, but significantly higher than the EU average also in Czechia. Sixteen Member States reported fraudulent cases in this area. Poland and France reported the highest number of cases and Poland and Bulgaria reported the highest financial amounts involved. If no relevant irregularities were reported, no FDR is mentioned in the map for the relevant Member State. See Table NR23. UK is not included in the map. Table NR24 and Map NR4 below provide an overview of the irregularities not reported as fraudulent by the Member States over the period 2017-2021 in relation to market measures. It also gives the total payments for expenditure under market measures and the IDR. The IDR exceeded 58% in Poland, 21% in Malta and 16% in Romania. It was higher than the EU average also in Hungary, Sweden, Croatia and Bulgaria. The huge IDR in Poland is due to three cases, accounting together EUR 75 million, which refer to multiple budget years. The IDR of Malta is due to the low overall expenditure in this CAP sector. The IDR of Romania is influenced by one irregularity accounting for EUR 20 million. 22 Member States reported non-fraudulent cases concerning market measures. Spain, France and Italy reported the highest number of cases and Poland, Romania, Spain and France reported the highest financial amounts involved. If no relevant irregularities were reported, no IDR is mentioned in the map for the relevant Member State. See Table NR24. UK is not included in the map. Tables NR23 and NR24 above indicate that the reporting of irregularities was concentrated in a few Member States. The top two Member States in terms of number of detections (France and Poland) reported about 50% of all fraudulent irregularities (68% of irregular financial amounts) related to market measures, while they received about 24% of payments. For non-fraudulent irregularities, the top two Member States in terms of number of detections (Spain and France) did not overlap with the highest ranking Member States in terms of the financial amounts involved (Poland and Romania). Poland and Romania reported about 72% of the irregular financial amounts and received about 4% of payments. As mentioned in Section 3.4.3.1, the concentration of detections was analysed in detail in the 2018 PIF Report, covering the period 2014-2018. The analysis suggests that the level of concentration of detections went beyond what could be expected given the concentration of payments related to market measures among Member States, especially for fraudulent irregularities. This suggests the need for more uniform practice in criminal investigation and prosecution to protect the EU budget. 3.4.3.3. Direct payments to farmers Table NR25 and Map NR5 below provide an overview of the irregularities reported as fraudulent by the Member States over the period 2017-2021 in relation to direct payments to farmers. It also shows the total payments for direct payments and the FDR. Romania recorded the highest FDR, at 0.12%. Twelve Member States have reported fraudulent cases in this area. Romania and Italy reported the highest number of cases and financial amounts involved. In this map, FDR ‘0.00’ indicates low financial amounts involved in the irregularities, in proportion to the payments received. If no relevant irregularities were reported, no FDR is mentioned in the map for the relevant Member State.See Table NR25. UK is not included in the map.

Table NR26 and Map NR6 below provide an overview of the irregularities not reported as fraudulent by the Member States over the period 2017-2021 in relation to direct payments. It also shows the total payments for direct aid and the IDR. The IDR was the highest in Italy, more than double the rate for Romania, which ranked second. 22 Member States have reported non-fraudulent cases in direct aid. In this map, IDR ‘0.00’ indicates low financial amounts involved in the irregularities, in proportion to the payments received. If no relevant irregularities were reported, no IDR is mentioned in the map for the relevant Member State. See Table NR26. UK is not included in the map. Tables NR25 and NR26 above suggest that the reporting of irregularities was concentrated in a few Member States. The top two Member States in terms of number of detections (Romania and Italy) reported 80% of all fraudulent irregularities (and 79% of irregular financial amounts) related to direct aid, while they received about 14% of payments. With reference to non-fraudulent irregularities, the top two Member States in terms of number of detections (Italy and Romania) reported about 51% of such irregularities (and 69% of irregular financial amounts), while they received about 14% of payments. The concentration of detections in relation to direct payments to farmers was analysed in detail in the 2018 PIF Report, covering the period 2014-2018. The analysis suggests that the concentration of detections went beyond what could be expected given the level of concentration of payments related to direct aid to farmers among Member States. This may be due to different factors, including no uniform management and control systems and, for the fraudulent irregularities, different approaches to criminal investigation and prosecution to protect the EU financial interests. 3.4.4.Follow-up to suspected fraud In the 2019 PIF Report, a new analysis of the follow-up Member States give to suspected fraud has been introduced. This analysis considers the irregularities that have been reported as suspected fraud from 2007 to 2013 and look at whether these irregularities have been dismissed (meaning whether they have been de-classified to administrative irregularities), they are still pending as suspected fraud or they have been confirmed as established fraud (following a final verdict). The details about the methodology for this analysis can be found in the 2019 PIF. Table NR27 includes the update of the dismissal ratio, established fraud ratio and pending ratio. The dismissal ratio gives the percentage of fraudulent irregularites that have been reclassified as non-fraudulent during their lifetime, until end of 2021. The established fraud ratio gives the percentage of fraudulent irregularites that were classified as established fraud by the end of 2021. The pending ratio gives the percentage of fraudulent irregularities that were still classified as suspected fraud at the end of 2021. These three percentages sum to 100%. Similar to the situation up to 2019, about 23% of the irregularities reported as fraudulent were dismissed and reclassified as non-fraudulent by the end of 2021. Another 62% of these irregularities were still pending. This may point to a significant underestimation of the dismissal ratio, because part of these cases that are still classified as suspected fraud are already closed. In any case, between 8 and 15 years have already passed since the detection of the irregularity and the more time passes the less it can be expected that fraud will actually be established. The dismissal ratio varied across the Member States. High dismissal ratios, especially when associated with high pending ratios, may be due either to the detection phase or to the investigation/prosecution phase. Low dismissal ratios may be positive, but they may also be the result of many irregularities still pending. After eight years following the end of the period under consideration, the dismissal ratio was zero or very low in many Member States. This indicator must be read in combination with the pending ratio. The latter points to the possibility that the dismissal ratio increases in the future (depending on the number of cases that are still open) or to an underestimation of the dismissal ratio (depending on the number of cases that are already closed). High dismissal ratios, especially when associated with a high number of still pending cases, may be due to (i) a detection phase that leads to report to the judicial authority cases that were not fraudulent; (ii) an investigation/prosecution phase that gives low priority or does not have enough resources to properly address the case; (iii) the stage of the procedure when an irregularity is classified as suspected fraud. The cases of established fraud were few. This may point to the need to invest further in the investigation/prosecution phase. At EU-27 level, established fraud ratio was 15%. It was zero or very low in many Member States. In general, the established fraud ratio is not likely to increase significantly because, while 62% of cases are still classified as suspected fraud (pending ratio), part of them are already closed and, in any case, between 8 and 15 years have already passed since the detection of the irregularity. Similarly to the dismissal ratio, also the established fraud ratio depends on the stage of the procedure when an irregularity is classified as suspected fraud (see above). 3.5.Recovery cases For an in-depth analysis of recovery and financial corrections in the CAP, see the DG AGRI’s 2021 Annual Activity Report and the 2021 Annual Management and Performance Report for the EU Budget. Main findings Fraudulent irregularities

Over the period 2017-2020, the number of fraudulent irregularities in support to agriculture expenditure and the financial amounts involved were rather stable, apart from a significant increase of the financial amounts in 2017-2018, caused by just two cases related to market measures. In 2021, the number of fraudulent irregularities decreased by 17% with respect to 2020 and th