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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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

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

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

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

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.

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

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

(3)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;

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The category pure ‘ethics and integrity’ ranked high, with 83 irregularities found, but none reported in 2019 or 2020.Only one irregularity was reported as corruption. 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’).

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

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

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

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

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

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

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

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

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

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

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

Table NR10 provides an overview of the most frequent categories (or combinations of categories) of irregularities linked to cases reported as fraudulent in relation to support to agriculture in 2020 and the financial amounts involved. It also gives the figures for these categories (or combinations of categories) over the period 2016-2020. 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.

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

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

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

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

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

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

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.

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

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

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 at the stage of the procedure when potentially fraudulent irregularities are reported. The concentration of detections was more accentuated for fraudulent rather than for non-fraudulent irregularities. This suggests that different approaches to criminal investigation and prosecution could be an additional and significant factor giving rise to these different levels of detection across the Member States.

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

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

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

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

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

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

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

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

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 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.

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

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

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

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).

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.

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

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

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

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

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

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

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

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

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

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

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 have been held financially liable in 2020 for over EUR 109 million, and new cases are being appropriately followed-up.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 following statistics are prepared based on the total established and estimated amount of traditional own resources (TOR) as reported in OWNRES. Figures on recovery are based only on established amounts.

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

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

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

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

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

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

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

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

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

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

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

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

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.

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

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

The 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.

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

EUROPEAN COMMISSION Brussels, 20.9.2021 SWD(2021) 258 final COMMISSION STAFF WORKING DOCUMENT Statistical evaluation of irregularities reported for 2020: own resources, agriculture, cohesion and fisheries policies, pre-accession and direct expenditure Accompanying the document REPORT FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT AND THE COUNCIL 32nd Annual Report on the protection of the European Union's financial interests - Fight against fraud - 2020 {COM(2021) 578 final} - {SWD(2021) 257 final} - {SWD(2021) 259 final} - {SWD(2021) 262 final} - {SWD(2021) 263 final} - {SWD(2021) 264 final}



Table of Contents List of abbreviations 4.COHESION, FISHERIES AND OTHER INTERNAL POLICIES Executive summary 4.1.Introduction 4.2.General analysis 4.2.1.Irregularities reported as fraudulent 4.2.1.1.Trend by programming period 4.2.1.2.Trend by Fund 4.2.2.Irregularities not reported as fraudulent 4.2.3.Irregularities reported in relation to the PP 2014-2020: comparison with PP 2007-2013 4.3.Specific analysis 4.3.1.Detection rates by objective 4.3.2.Priorities concerned by the reported irregularities 4.3.2.1.Irregularities reported as fraudulent (fisheries not included) 4.3.2.2.Irregularities not reported as fraudulent (fisheries not included) 4.3.2.3.Irregularities related to investments in health infrastructure 4.4.Reasons for carrying out checks

4.5.Antifraud and control activities by Member States 4.5.1.Duration of irregularities 4.5.2.Detection of irregularities reported as fraudulent by Member State 4.5.3.Fraud detection rate 4.5.4.Irregularity detection rate 4.5.5.Follow-up to suspected fraud (programming period 2007-2013) 4.6.Other internal policies Main Findings 5.PRE-ACCESSION POLICY Executive Summary 5.1.Introduction 5.2.Instruments for Pre-accession Assistance 5.2.1.Before 2007: Pre-accession Assistance (PAA) 5.2.2.2007-2013: The Instrument for Pre-accession Assistance (IPA I) 5.2.3.2014 – 2020: The Instrument for Pre-accession Assistance (IPA II) 5.3.General analysis 5.4.Pre-accession Assistance (PAA 2000-2006) 5.4.1.Recent trends 5.4.2.Recent trends by component 5.4.3.Recent trends by beneficiary country

5.4.4.Trends since the start of PAA, by beneficiary country and component 5.5.Instrument for Pre-Accession Assistance (IPA I, 2007-2013) 5.5.1.Recent trends 5.5.2.Recent trends by component 5.5.3.Recent trends by beneficiary country 5.5.4.Trends since the start of IPA I, by beneficiary country and component 5.6.Instrument for Pre-accession Assistance II (IPA II 2014-2020) 5.6.1.Recent trends 5.6.2.Recent trends by component 5.6.3.Recent trends by beneficiary country 5.6.4.Trends since the start of IPA II, by beneficiary country and component 6.Direct Management 6.1.Introduction 6.2.General analysis 6.2.1.Five year analysis 2016-2020 6.3.Specific analysis 6.3.1.Recoveries according policy areas 6.3.2.Recoveries according to legal entity residence 6.3.3.Method of detection 6.3.4.Types of irregularity

6.3.5.Recovery COUNTRY FACTSHEETS Belgium - Belgique/België Bulgaria – България Czech Republic - Česká republika Denmark – Danmark Germany – Deutschland Estonia – Eesti Ireland – Éire Greece – Ελλάδα Spain – España France Croatia – Hrvatska Italy – Italia Cyprus – Κύπρος Latvia – Latvija Lithuania – Lietuva Luxembourg Hungary - Magyarország Malta

Netherlands - Nederland Austria – Öst