Commission Staff Working Document: Statistical evaluation of irregularities reported for 2016 Own Resources, Natural Resources, Cohesion Policy, Pre-accession and Direct expenditure, accompanying the document "Report from the Commission to the European Parliament and the Council: Protection of the European Union's financial interests - Fight against Fraud Annual Report 2016" (Part 1/2)
Inhoudsopgave van deze pagina:
Council of the European Union
Brussels, 25 July 2017 (OR. en)
11503/17 ADD 1
GAF 40 FIN 496
COVER NOTE
From: Secretary-General of the European Commission, signed by Mr Jordi AYET PUIGARNAU, Director
date of receipt: 24 July 2017
To: Mr Jeppe TRANHOLM-MIKKELSEN, Secretary-General of the Council of the European Union
No. Cion doc.: SWD(2017) 266 final
Subject: Commission Staff Working Document: Statistical evaluation of irregularities reported for 2016 Own Resources, Natural Resources, Cohesion Policy,
Pre-accession and Direct expenditure, accompanying the document "Report from the Commission to the European Parliament and the Council: Protection of the European Union's financial interests - Fight against Fraud Annual Report 2016" (Part 1/2)
Delegations will find attached document SWD(2017) 266 final.
Encl.: SWD(2017) 266 final
EUROPEAN COMMISSION
Brussels, 20.7.2017 SWD(2017) 266 final
PART 1/2
COMMISSION STAFF WORKING DOCUMENT
Statistical evaluation of irregularities reported for 2016 Own Resources, Natural Resources, Cohesion Policy, Pre-accession and Direct
expenditure
Accompanying the document
REPORT FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT AND THE COUNCIL
Protection of the European Union's financial interests - Fight against Fraud
Annual Report 2016
{COM(2017) 383 final i} {SWD(2017) 267 final} {SWD(2017) 268 final} {SWD(2017) 269 final} {SWD(2017) 270 final}
TABLE OF CONTENTS
COMMISSION STAFF WORKING DOCUMENT Statistical evaluation of irregularities reported for 2016 Own Resources, Natural Resources, Cohesion Policy, Pre-accession and Direct expenditure .........................................................................................................................
LIST OF ABBREVIATIONS ..................................................................................................... 3
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1.Introduction ................................................................................................................... 5
1.1. Scope of the document .................................................................................................. 5
1.2. Structure of the document ............................................................................................. 5
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2.Traditional Own Resources .......................................................................................... 7
2.1. Introduction ................................................................................................................... 7
2.2. General analysis – Trend analysis ................................................................................ 7
2.2.1. Reporting Years 2012-2016 .......................................................................................... 7
2.2.2. OWNRES data vs TOR collection ............................................................................... 9
2.2.3. Recovery ..................................................................................................................... 10
2.3. Specific analysis ......................................................................................................... 11
2.3.1. Irregularities reported as fraudulent ............................................................................ 11
2.3.2. Irregularities not reported as fraudulent...................................................................... 15
2.4. Member States’ activities ........................................................................................... 18
2.4.1. Classification of cases as fraudulent and non-fraudulent and related rates ................ 18
2.4.2. Recovery rates ............................................................................................................ 19
2.4.3. Commission’s monitoring .......................................................................................... 20
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3.Common Agricultural Policy (CAP) .......................................................................... 22
3.1. Introduction ................................................................................................................. 22
3.2. General analysis – Trend analysis .............................................................................. 23
3.2.1. Irregularities reported 2012-2016 ............................................................................... 23
3.2.2. Irregularities reported as fraudulent ............................................................................ 25
3.2.3. Irregularities not reported as fraudulent...................................................................... 28
3.3. Specific analysis ......................................................................................................... 30
3.3.2. Fraud and Irregularity Detection Rates by CAP pillar .............................................. 33
3.3.3. Market measures – fraudulent and non-fraudulent irregularities .............................. 33
3.4. Anti-fraud activities of Member States ....................................................................... 34
3.4.1. Duration of irregularities ............................................................................................ 35
3.4.2. Detection of irregularities reported as fraudulent by Member State .......................... 35
3.4.2.1. Reported in 2016 ......................................................................................................... 35 3.4.2.2. Reported during the period 2012-16 ........................................................................... 36
3.4.3. Fraud and Irregularity Detection Rates by Member State .......................................... 37
3.4.4. Ratio of established fraud / Dismissal ratio ................................................................ 41
3.5. Recovery cases ............................................................................................................ 42 LIST OF ABBREVIATIONS
AMIF Asylum, Migration and Integration Fund
CAP Common Agricultural Policy
CF Cohesion Fund
CFP Common Fishery Policy
CMO Common Organisation of the Markets
CN Combined Nomenclature (Customs)
CP Cohesion Policy
DetE Detection Efficiency
DG Directorate General
EAFRD European Agricultural Fund for Rural Development
EAGF European Agricultural Guarantee Fund
EC European Commission
EFF European Fisheries Fund
EMFF European Maritime and Fisheries Fund
ER Error Rate
ERDF European Regional Development Fund
ESIF European Structural and Investment Funds
ESF European Social Fund
EU European Union
EU-10 The ten Member States having acceded the EU in 2004
EU-12 The twelve Member States having acceded the EU between 2004 and 2007
EU-15 The fifteen Member States of the EU before the 2004 accession
EU-2 Bulgaria and Romania
EU-27 The 27 Member States before Croatian accession
EUR Euro FAL Fraud Amount Level
FDR Fraud Detection Rate
FEAD Fund for European Aid to the most Deprived
FFL Fraud Frequency Level
IDR Irregularity Detection Rate
IMS Irregularity Management System
ISF Internal Security Fund
GNI Gross National Income
HRR Historical Recovery Rate
NR Natural Resources
OLAF European Anti-Fraud Office (Office pour la Lutte Antifraude)
OWNRES Web application for communication of irregularities in the field of Traditional Own Resources
RepE Reporting Efficiency
RR Recovery Rate
SME Small and Medium Sized Enterprise
TFEU Treaty on the Functioning of the European Union
TOR Traditional Own Resources
YEI Youth Employment Initiative
Statistical evaluation of irregularities reported for 2016 Own Resources, Natural Resources, Cohesion Policy, Pre-accession and Direct
expenditure
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1.I NTRODUCTION
1.1. Scope of the document
The present document 1 is based on the analysis of the notifications provided by
national authorities of cases of irregularities and suspected or established fraud. The reporting is performed in fulfilment of a legal obligation enshrined in sectoral
European legislation.
The document accompanies the Annual Report adopted on the basis of article 325 of the Treaty on the Functioning of the European Union (TFEU), according to which “The Commission, in cooperation with Member States, shall each year submit to the European Parliament and to the Council a report on the measures taken for the
implementation of this article”.
For this reason, this document should be regarded as an analysis of the achievements of Member States.
The methodology (including the definition of terms and indicators), the data sources and the data capture systems are explained in detail in the Commission Staff Working Document – Methodology for the Statistical Evaluation of Irregularities accompanying the Annual Report on the Protection of the EU financial interests for
the year 2015 2 .
1.2. Structure of the document
The present document is divided in two parts.
The first part is dedicated to the analysis of irregularities reported in the area of the Traditional Own Resources (Revenue).
The second part, concerning the expenditure part of the budget, is composed of three sections, dedicated, respectively, to shared, decentralised and centralised management
modes.
The section dedicated to shared management, covers agriculture, cohesion policy and
fisheries 3 . Decentralised management refers to the pre-accession policy, while the
centralised management section mainly deals with internal and external policies for which the Commission directly manages the implementation.
The document is completed by 28 country factsheets, which summarise, for each Member State, the main indicators and information that have been recorded
throughout the analyses.
11 Annexes complement the information and data of this document, providing a global overview of the irregularities reported according to the relevant sector regulations. Annexes from 1 to 10 concern Traditional Own Resources, Annex 11
1 This document does not represent an official position of the Commission.
2 SWD(2016)237final. http://ec.europa.eu/anti
href="http://ec.europa.eu/anti-%20fraud/sites/antifraud/files/methodology_statistical_evaluation_2015_en.pdf">fraud/sites/antifraud/files/methodology_statistical_evaluation_2015_en.pdf
3 Contrary to previous years, Fishery policy is analysed together with Cohesion policy intervention.
covers all the expenditure sectors for which Member States and beneficiary countries have a reporting obligation.
Part I - REVENUE
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2.T RADITIONAL O WN R ESOURCES
2.1. Introduction
The technical explanations and the statistical approach are explained in the accompanying document 'Methodology regarding the statistical evaluation of
reported irregularities for 2015'.
The following analysis is based on the data available on the cut-off date (5 April 2017) and aims to provide an overview of the reported cases of fraud and irregularities reported for 2016 together with their financial impact.
2.2. General analysis – Trend analysis
2.2.1. Reporting Years 2012-2016
The number of cases reported via OWNRES for 2016 (4 647) is about 12 % lower than the average number of cases of irregular cases reported for the 2012-2016 period (5 281).
The total estimated and established amount of TOR involved (EUR 537 million) is about 13 % higher than the average estimated and established amount for years 2012- 2016 (EUR 474 million).
In 2016, 5 big 4 cases for a total amount of about EUR 115 5 million were reported compared to 2015, when 2 6 big cases with a total amount of about EUR 31 million
affected the total estimated and established amount. Luxemburg did not communicate any case exceeding an amount of EUR 10 000.
CHART TOR1: Total number of OWNRES cases and the related estimated and established amount (2012-2016)
Annex 1 of the summary tables shows the situation on the cut-off date (5 April 2017) for the years 2012-2016.
4 Cases with an amount of TOR exceeding EUR 10 million.
5 NL (3 cases – EUR 77.8 million) and the UK (2 cases – EUR 37.6 million).
6 NL (2 cases – EUR 30.9 million).
2.2.1.1. Irregularities reported as fraudulent
The number of cases reported as fraudulent registered in OWNRES for 2016 (513) is currently 32 % lower than the average number of cases reported for the 2012-2016 period (749).
The total estimated and established amount of TOR involved (EUR 83 million)
represents a decrease of 30 % of the average estimated and established amount for the
years 2012-2016 (EUR 119 million).
For 2016, Luxemburg, Portugal and Slovenia did not communicate any fraudulent case exceeding an amount of EUR 10 000.
CHART TOR2: OWNRES cases reported as fraudulent and the related estimated and established amount (2012-
2016)
On the cut-off date, 11 % of all cases detected in 2016 were classified as fraudulent. The percentage remained quite stable in comparison to 2015.
Annex 2 of the summary tables shows the situation on the cut-off date for years 2012- 2016.
2.2.1.2. Irregularities not reported as fraudulent
At the same time, the number of cases not reported as fraudulent communicated via OWNRES for 2016 (4 134) was 9 % lower than the average number reported for
2012-2016 (4 532).
The total estimated and established amount of TOR (EUR 454 million) was 28 % higher than the average estimated and established amount for the years 2012-2016 (EUR 355 million).
Cyprus, Luxemburg and Malta did not report any case of irregularity exceeding an amount of EUR 10 000 for 2016.
CHART TOR3: OWNRES cases not reported as fraudulent and the related estimated and established amount
(2012-2016)
Annex 3 of the summary tables shows the situation on the cut-off date for years 2012- 2016.
2.2.2. OWNRES data vs TOR collection
In 2016, the total established amount of TOR (gross) was EUR 25.7 billion and more than 98 % was duly recovered and made available to the Commission via the A- account. According to the OWNRES data, around EUR 537 million has been established or estimated by the Member States in connection with cases reported as fraudulent/not fraudulent where the amount at stake exceeds EUR 10 000.
The total estimated and established amount reported in OWNRES represent 2.14 % of
7
the total collected TOR (gross) amount in 2016. This proportion has increased
compared with 2015 when it was 1.71 % 8 . A percentage of 2.14 % indicates that of
every EUR 100 of TOR (gross) established, an amount of EUR 2.14 is registered as irregular (fraudulent or non-fraudulent) in OWNRES. There are differences among
the Member States. In 11 Member States 9 , the percentage is above the average of
2.14 %. The highest percentage for 2016 can be seen in Latvia, Greece and Austria with 7.35 %, 7.14 % and 6.07 % respectively.
For the seven 10 Member States which established and made available most of the
TOR amounts, the percentage of the estimated and established OWNRES amounts to established TOR for 2016 was equal to 2.13 %. In comparison with the previous year, this represents an increase of 0.38%. For Belgium, the proportion of estimated and established OWNRES amounts to established TOR remained almost stable in 2016 compared to the previous year, while for Germany it has decreased. For other five Member States, the proportion of estimated and established OWNRES amounts to established TOR increased in 2016 compared to the previous year.
7 See Annex 4.
8 On the cut-off date .
9 Denmark, Greece, Spain, France, Latvia, Hungary, the Netherlands, Austria, Portugal, Romania and the UK.
TOR MAP1: Showing the percentage of established and estimated amounts in OWNRES of established TOR for 2016
2.2.3. Recovery
The fraud and irregularity cases detected in 2016 correspond to an established amount
of EUR 525 million 11 . Nearly EUR 189 12 million of this was recovered in cases where an irregularity was at stake and EUR 17 13 million in fraudulent cases. In total
EUR 205 million was recovered by all Member States for all cases which were detected in 2016. In absolute numbers, Germany recovered the highest amount in 2016 (EUR 66 million) followed by the United Kingdom (EUR 32 million). This is a starting point for the recovery. Analysis shows that lengthy recovery procedures spread over several years are usually required due to administrative and judicial
procedures in complex cases or cases with huge financial impact.
11 The estimated amounts are excluded.
12 See Annex 9.
13 See Annex 9.
In addition, Member States continued their recovery actions related to the detected cases of previous years. The EU-28 recovered EUR 139 million in 2016 related to
cases detected between 1989 and 2015.
2.2.3.1. Recovery rates
Over the past five years the annual recovery rate has varied between 39 % and 78 %
(see Chart TOR4). The recovery rate for 2016 is currently 39 % 14 . In other words, out
of every amount over EUR 10 000 of duties established and reported for 2016 in OWNRES as irregular/fraudulent, approximately EUR 3 900 has already been paid.
CHART TOR4: Annual recovery rates (2012-2016)
The overall recovery rate is a correlation between the detection, the established amount and the current recovery stage of individual cases (high additional duty
claims are more frequently associated with long lasting administrative and criminal procedures).
Recovery rates vary among the Member States. The highest recovery rates for 2016 are in Estonia (100%), Slovenia (100%), Sweden (97%), Germany (92 %), Czech
Republic (88 %) and Finland (84%). Differences in recovery results may arise from factors such as the type of fraud or irregularity, or the type of debtor involved.
Because recovery is ongoing, it can be expected that the recovery rate for 2016 will also go up in the future.
On the cut-off date, the overall recovery rate for all years 1989-2016 was 61 %.
2.3. Specific analysis
2.3.1. Irregularities reported as fraudulent
2.3.1.1. Modus operandi
A breakdown of frauds by mechanism type reveals that most fraudulent cases relate to smuggling of goods. Incorrect value, country of origin, country of dispatch, or
incorrect classification are frequently mentioned in 2016.
In 2016, the customs procedure ‘release for free circulation remained the procedure
most vulnerable to fraud (79 % of the number of cases and 84 % of the estimated and
14 See Annex 5.
established amount) . A total of 13 % of all cases reported as fraudulent and 8 % 15 of
all estimated and established amounts in OWNRES cases registered as fraudulent for
2016 fall under the category "Other". 16 A total of 7 % of all cases reported as
fraudulent and 8 % of all estimated and established amounts in OWNRES cases
registered as fraudulent for 2016 involve the transit procedure.
Of all cases reported as fraudulent about 72 % concern such goods as tobacco, textiles, articles of iron and steel, electrical machinery and equipment, and vehicles. In monetary terms those groups of goods represent about 71 % of all amounts estimated and established for cases reported as fraudulent. China, Morocco, United Arab Emirates and Malaysia are the most important - in monetary terms - countries of
origin of goods affected by fraud.
2.3.1.2. Method of detection of fraud cases
In 2016 17 , inspections by anti-fraud services (30 %) and customs controls carried out
at the time of clearance of goods (29 %) and post-clearance controls (28 %) were
almost equally successful methods of detecting fraudulent cases.
CHART TOR5: Method of detection 2016 – Cases reported as fraudulent – by number of cases
In monetary terms, of the EUR 83 million estimated or established in fraudulent cases registered for 2016, around 53 % were discovered during an inspection by anti-fraud services, 16 % during a post-clearance control, 15 % during a control at the time of
clearance of goods.
15 This is mainly due to the cases of cigarette smuggling detected in free zones or free warehouses and reported by
Greece.
16 The category "Other" combines, among others, the following procedures or treatments: Processing under customs
control, temporary admission, outward processing and standard exchange system, exportation, free zone or free warehousing, reexportation, destruction and abandonment to the Exchequer.
17 See Annexes 7 and 8.
CHART TOR6: Method of detection 2016 – Cases reported as fraudulent – by established amounts
In 8 Member States more than 50 % of all estimated and established amount in
fraudulent cases were detected by anti-fraud services 18 . As regards amounts, controls
at the time of clearance of goods were the most important method for detecting fraudulent instances in Greece, Croatia, Latvia, Lithuania, Finland and the United Kingdom whereas post-clearance controls were in Bulgaria, Hungary, Poland and
Slovakia.
In Cyprus and Austria the greatest part (89% and 69 % respectively) of all estimated and established amounts in fraudulent cases were detected by an inspection by
services or bodies other than customs.
Case study: Portugal, fraudulent import declarations of steel
In 2015, the Portuguese customs authorities (Tax and Customs Authority – AT) opened an investigation into a complaint concerning suspicions that, in 2013 and 2014, Portuguese companies had been making fraudulent declarations of imports of ‘flat-rolled products of non-alloy and alloy steel which are painted, varnished or coated with plastics on at least one side’. The companies were declaring the origin of the goods as Vietnam, when in fact they were from China, to avoid paying anti-dumping and countervailing duties.
As part of the nationwide investigation, the documents seized and information gathered were analysed (relating to the companies involved and the products traded), including commercial documentation, contracts, electronic communications between the Portuguese companies and the Chinese supplier and the product references (same type and price before and after the imposition of the anti-dumping duties). This led to the conclusion that the case under investigation was a specific type of commercial fraud, whereby the goods are transited through countries for which the EU does not have trade measures in place, meaning that the true origin of the goods traded is artificially ‘lost’, and, as a result of this illicit practice, the duties due are avoided.
This transiting of goods involved the fraudulent use of Vietnamese companies as the supposed producers of the goods, and traders based in Hong Kong and Singapore were used to export the goods to importers in the EU. In short, once trade measures began to be applied to Chinese goods, the imports were then brought into the EU through intermediaries (and not directly from the Chinese companies, as had previously been the case). The intermediaries were the link between the two Vietnamese companies (the ‘fraudulent’ suppliers) and the EU importers.
On the basis of the evidence gathered, on 19 January 2016 the AT sent the information to OLAF, in accordance with Council Regulation (EC) No 515/97 i of 13 March 1997, so that an on-site visit to Vietnam could take place. In the course of the investigation carried out by OLAF in Vietnam, and with the full cooperation of the Member
18 Belgium, the Czech Republic, Denmark, Germany, Ireland, Spain, France and Romania.
States’ authorities, and particularly the AT, and with the help of the Vietnamese Ministry of Industry and Trade (MOIT) and the Vietnamese Chamber of Commerce and Industry (VCCI), it was proven that the goods imported into the EU were Chinese and that anti-dumping and countervailing duties had indeed been avoided.
2.3.1.3. Smuggled cigarettes
In 2016, there were 147 cases of smuggled cigarettes registered (CN code 19 24 02 20
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90)involving estimated TOR of around EUR 25 million. In 2015 the number of cases of smuggled cigarettes was 241, totalling around EUR 31 million.
The highest number of cases was reported by Poland (29) and Greece (27). The highest amount was reported by Greece (EUR 13.3 million). No cases were reported
by ten Member States 20 .
Table TOR1: Cases of smuggled cigarettes in 2016
TOR: Cases of smuggled cigarettes in 2016
Cases Established and
MS estimated amount
N EUR
BE 4 2,409,819
BG 1 170,896
CZ 1 118,131
DE 5 225,088
IE 3 445,574
EL 27 13,288,089
ES 9 617,317
FR 15 1,294,284
HR 1 284,373
IT 4 1,327,532
LV 7 422,035
LT 9 246,756
AT 3 273,695
PL 29 1,681,717
RO 14 1,779,270
FI 5 107,717
SE 2 101,720
UK 8 279,810
Total 147 25,073,822
2.3.1.4. Cases reported as fraudulent by amount
In 2016, the estimated and established amount was below EUR 50 000 in 378 cases reported as fraudulent (74 % of all fraud cases), whereas it was above EUR 50 000 in
135 cases (26 %).
19 Combined nomenclature or CN – nomenclature of the Common Customs Tariff.
20 Denmark, Estonia, Cyprus, Malta, Luxembourg, Hungary, the Netherlands, Portugal, Slovenia and Slovakia.
The total estimated and established amount in cases reported as fraudulent, where the amount at stake was above EUR 50 000, amounted to EUR 66 million (79 % of the
total estimated and established amount for cases reported as fraudulent).
Table TOR2: Cases reported as fraudulent by amount category in 2016
2.3.2. Irregularities not reported as fraudulent
2.3.2.1. Modus operandi
A breakdown of irregularities by mechanism type shows that most cases of irregularity relate to incorrect declarations (incorrect classification, customs value or country of origin or dispatch) and formal shortcomings (incorrect use of preferential
arrangements or failure to fulfil obligations or commitments).
Not all customs procedures are equally susceptible to irregularities; their vulnerability may change in the course of time as certain economic sectors are briefly targeted. The customs procedure ‘release for free circulation’ is the customs procedure mostly
affected by irregularities since at the time of release for free circulation the noncompliance in the customs declaration may relate to a large number of irregularities, e.g. to the tariff, CN code, (preferential) origin, incorrect value, etc. On the other hand, in customs suspension regimes (like warehousing, transit, etc. - where the payment of duties is suspended) the sole irregularity that might occur is the subtraction of the goods from customs supervision. Thus it is normal, and indeed to be expected, that most fraud and irregularities be reported in connection with the procedure ‘release for free circulation’.
In 2016 most of the estimated and established amounts in OWNRES in the EU-28 (72 %) for cases reported as non-fraudulent related to the customs procedure ‘release
for free circulation’. 21 In all, 19 % of all amounts estimated or established in cases not reported as fraudulent in 2016 involved customs warehousing 22 , 8 % of all amounts
estimated or established related to inward processing. Other customs procedures are
only marginally affected in 2016.
Of all cases reported as non-fraudulent about 49 % concern electrical and mechanical machinery, vehicles, mechanical appliances, plastics, articles of iron and steel and textiles. In monetary terms those groups of goods represent about 46 % of all amounts estimated or established for cases reported as non-fraudulent. China, USA, Taiwan, Brazil, Russia are - in monetary terms - the most important countries of
origin of goods affected by irregularities.
21 See Annex 6.
22 In relation to inward processing Germany and the United Kingdom reported cases amounting to EUR 15.9 and 12
million respectively.
Case study: Poland, EU budget revenue - irregularities regarding the import of apple concentrate
The market for concentrate produced in Ukraine and Moldova (for export to the EU) is dominated by factories belonging to a single group. The group transports concentrate from its factories in Ukraine and Moldova to factories in Poland and on to Western Europe. Following its release for free circulation some of the concentrate is exported from the EU (USA, Canada, Russia). Before actually entering the EU the goods are subject to purchase/sale (chain transactions). In most transactions the exporters to the EU are companies registered in Great Britain.
The aim of creating trading scenarios in which the major player in the production of apple concentrate in Ukraine and Moldova does not appear as the actual exporter of the goods from Ukraine and creates a chain of purchases/sales is, inter alia:
• to avoid challenges from the EU customs authorities concerning direct links between the exporter and the importer that might affect the value of the goods entered in the declaration of release for free circulation;
• to avoid challenges from the Ukrainian tax and customs authorities regarding fraudulent VAT evasion (overdeclaration of the value of the goods at export) or irregularities linked to corporate income tax.
There are cases where one of the group presents, in the declaration for release for free circulation, invoices, transfers and contracts relating to companies in the chain, whereas it is actually selling the goods to itself (moving between the establishments from UA/MD to PL).
The above situation is highly relevant where there is a risk that the customs value of goods has been underdeclared. In such cases the importer's claims that changes to the prices result from slumps in the market, which it itself largely controls, should be treated with caution (Ukraine - Moldova). In the case of customs declarations concerning apple concentrate, the real risks are aggravated by additional risk factors:
• correct tariff classification;
• correct use of preferential tariff quotas.
All risks are present at the same time and can have fiscal consequences.
2.3.2.2. Method of detection of non-fraudulent cases
In 2016, most non-fraudulent cases (54 %) were revealed during post-clearance customs controls. Other methods of detection for non-fraudulent cases that featured frequently were voluntary admission (18 %), clearance controls (13 %), tax audits
(9 %), followed by anti-fraud services (5 %). 23
23 See Annex 7 and 8.
CHART TOR7: Method of detection 2016 – Cases not reported as fraudulent – by number of cases
Considering the estimated or established amounts, around 70 % of all irregularity cases registered for 2016 were discovered during a post-clearance control, 9 % were related to voluntary admission, 8 % were found during a control at the time of clearance of goods, whereas 7 % related to a tax audit, and 6 % to an inspection by
anti-fraud services.
CHART TOR8: Method of detection 2016 – Cases not reported as fraudulent – by established amounts
In 15 Member States, more than 50 % of all non-fraudulent cases — in amounts —
were detected by post-clearance controls. 24 In France and Romania more than 50 % of
the amounts relating to non-fraudulent cases were detected by anti-fraud services.
24 Bulgaria, the Czech Republic, Denmark, Estonia, Croatia, Italy, Latvia, Lithuania, Hungary, the Netherlands,
Poland, Portugal, Slovenia, Sweden and the UK.
Significant amounts were reported as non-fraudulent following voluntary admission by the United Kingdom (EUR 13 million) and Germany (EUR 12 million). In 16 Member States voluntary admission was keyed in as a method of detection of cases
reported as non-fraudulent.
2.3.2.3. Solar panels vulnerable to irregularities – mutual assistance
In 2016, solar panels originating in China were especially vulnerable to nonfraudulent irregularities in monetary terms. About 21 % (EUR 97 million) of the total amount that was established in non-fraudulent irregularities concerned this type of goods. Incorrect country of origin or dispatching country was the main pattern of the infringement reported. The Netherlands and the United Kingdom were particularly affected by this type of goods and infringement. Other 11 Member States reported
also cases related to solar panels to a smaller extent 25 . Following Mutual Assistance
notices issued by OLAF 59 cases totalling to 32 million were detected. This underlines the importance of investigations conducted by OLAF in this particular
field.
Case study: Netherlands, Customs – evasion antidumping solar panels/confiscation
Last year we reported on the coordination group on solar panels. In 2016, a number of successful results were reported. Due to the coordination group, DG Trade was informed about companies that were involved in the misuse of the Minimum Import Prices of solar panels (MIP). We confiscated in one case 43 containers with solar panels and in the same investigation, €4 million in anti-dumping was recovered. In several cases of solar panels a total of €27 million was involved and another 27 containers with solar panels were blocked as a guarantee for payment. The working method with a dedicated group on a specific issue, e.g. antidumping on solar panels, worked well, also due to the fact that specialists of several disciplines/units (import, physical checks, administrative controls) worked jointly in this group.
2.3.2.4. Cases not reported as fraudulent by amount
In 2016, the established amount was below EUR 50 000 in 3 185 non-fraudulent cases (77 % of all irregularity cases), whereas it was above EUR 50 000 in 949 cases
(23 %).
The total estimated and established amount in non-fraudulent cases where the amount at stake was above EUR 50 000 amounted to EUR 393 million (87 % of the total
estimated and established amount for non-fraudulent cases).
Table TOR3: Cases not reported as fraudulent by amount category in 2016
Amount, EUR N Estimated and established amount, EUR
< 50 000 3185 61,148,424
>= 50 000 949 392,609,198
Total 4,134 453,757,622
2.4. Member States’ activities
2.4.1. Classification of cases as fraudulent and non-fraudulent and related rates
For 2016, Member States reported 513 cases as fraudulent out a total of 4 647 cases reported via OWNRES, which indicates a Fraud Frequency Level (FFL) of 11 %. The differences between Member States are relatively large. In 2016 most Member States categorised between 10-50 % of all cases reported as fraudulent. However, Portugal
25 Belgium, the Czech Republic, Denmark, Germany, Ireland, Greece, France, Italy, Austria, Romania and Sweden.
and Slovenia did not categorise any cases reported as fraudulent. 26 Six Member States categorised less than 10 % of cases as fraudulent. 27 Five Member States registered
more than 50 % 28 of cases as fraudulent.
In 2016, the total estimated and established amount affected by fraud in the EU was
EUR 83 million and the overall incidence of fraud 29 was 0.33 %. For 2016, the
highest percentages can be seen in Greece (2.83 %), Austria (2.14 %) and Denmark
(2.04 %).) 30
The total estimated and established amount affected by irregularities was more than
EUR 454 million which indicates an irregularity incidence 31 of 1.81 %. The highest
percentages can be seen in Latvia (5.82 %), the Netherlands (4.96 %) and the Greece
(4.34 %). 32
There are large differences between Member States’ classifications, which may partly depend on their classification practices. This can influence the comparison of the amounts involved in cases reported as fraudulent and as non-fraudulent by Member
States. Moreover, individual bigger cases detected in a specific year may affect annual rates significantly. Factors such as the type of traffic, type of trade, the level of
compliance of the economic operators, the location of a Member State can influence the rates significantly. Bearing in mind these variable factors, the rates of incidence
can also be affected by the way a Member State’s customs control strategy is set up to target risky imports and to detect TOR-related fraud and irregularities.
2.4.2. Recovery rates
2.4.2.1. Cases reported as fraudulent
Over the 1989-2016 period, OWNRES shows that, on average, 21 % of the initially established amount was corrected (cancelled). The recovery rate (RR) for all years
33
(1989-2016) is 36 %. The RR for cases reported as fraudulent and detected in 2016
was 23 % 34 which is below the average rate of 40% for fraudulent cases for the 2012- 2016 period. 35 In general, the RR in cases reported as fraudulent is clearly much
lower than that for cases not reported as fraudulent.
2.4.2.2. Cases not reported as fraudulent
OWNRES shows that on the cut-off date, on average 37 % (1989-2016) of the initially established amount in relation to cases not reported as fraudulent has been corrected (cancelled) since 1989. The RR for non-fraudulent cases reported for 2016
is 42%. 36 On the cut-off date, the annual RR for the last five years has varied between
26 Luxembourg did not report any irregular case in 2016.
27 The Czech Republic (2%), Denmark (6%), Germany (6%), the Netherlands (1%), Sweden (2%) and the
UK (1%).
28 Bulgaria (85 %), Greece (79%), Cyprus (100%), Malta (10 %) and Poland (5 %).
29 The percentage that the total established and estimated amounts related to fraudulent cases represent on the total
TOR collected by Member States.
30 See Annex 4.
31 The percentage that the total established and estimated amounts related to non-fraudulent cases represent on the
total TOR collected by Member States.
32 See Annex 4.
33 This calculation is based on 17 948 cases, an established amount of EUR 2.1 billion (after already processed
corrections) and a recovered amount of EUR 0.75 billion.
34 See Annex 9.
35 On the cut-off date, for years 2012-2016, the annual RR for fraud cases varied between 23 % and 60 %.
36 See Annex 9.
42 % and 83 %. The overall RR for all years (1989-2016) for all cases not reported as
37
fraudulent is 71 %.
2.4.2.3. Historical recovery rate
The HRR confirms that in the long term recovery in cases reported as fraudulent is generally much less successful than in cases not reported as fraudulent (see table TOR4). Classification of a case as fraudulent is thus a strong indicator for forecasting
short- and long-term recovery results.
Table TOR4: Historical recovery rate (HRR
Table TOR4: Historical recovery rate (HRR)
Iregularities HRR 1989 – 2013
Reported as fraudulent 62.37%
Reported as non-fraudulent 90.46%
Total 83.93%
2.4.3. Commission’s monitoring
2.4.3.1. Examination of the write off reports
In 2016, 17 Member States submitted 92 new write-off reports to the Commission. In 2016, the Commission assessed 219 cases totalling EUR 88 million. In 92 of these
cases amounting to EUR 46 million 38 , the Commission's view was that the Member
States did not demonstrate satisfactorily that the TOR was lost for reasons not imputable to them so they were considered financially responsible for the loss.
Examination of Member States’ diligence in write-off cases constitutes a very effective mechanism for gauging their activity in the field of recovery. It encourages national administrations to step up the regularity, efficiency and effectiveness of their recovery activity, since any lack of diligence leading to failure to recover results in
individual Member States having to foot the bill.
2.4.3.2. Commission’s inspections
In its TOR inspections, the Commission has put a special emphasis on Member States’ customs control strategies and closely monitors their actions and follow-up in relation to the observations made during the inspections. Member States generally show their willingness to adapt their control strategies and to progressively implement systems that provide for efficient and effective risk analysis to protect the EU’s financial interests. However, budgetary constraints and the increase of tasks related to security have led to cuts in the number of customs officials in charge of duty collection control in many Member States. Coupled with continuing trade facilitations and simplification of procedures and controls, this may undermine the
control efficiency and thus pose risks to the protection of the EU financial interest.
In 2016, "Tariff suspensions and quotas", "Preferential tariff measures", "Reliability of the normal and separate accounts statements" and "Control strategy in the field of customs value" were the main inspection themes of the on-the-spot customs
inspections by the Commission services in Member States.
37 This calculation is based on 78 103 cases, an established amount of EUR 4.91 billion (after already processed
corrections) and a recovered amount of EUR 3.49 billion.
38 See Annex 10.
The on-the-spot inspection carried out in the United Kingdom found significant weaknesses in the management and control of undervalued imports of textiles and footwear and concluded, on the basis of the evidence available at the time of the inspection, that the United Kingdom had wrongly cancelled a very significant amount
of customs debts concerning undervalued imports.
OLAF also has concluded in March 2017 an investigation on the undervaluation of textiles and footwear imported in the United Kingdom from the People's Republic of China. This report indicates that the United Kingdom failed, even after repeated warnings and requests to that effect by OLAF, to apply the appropriate measures to prevent systematically undervalued imports of textiles and footwear from P.R. China from entering the EU through the United Kingdom, resulting in very significant losses to the EU budget between 2013 and 2016. The related fraud/irregularities were
only partially reflected in the OWNRES figures reported since 2013.
These elements led the Director-General of DG BUDG to make a reservation in the 2016 Annual Activity report on the inaccuracy of the TOR amounts transferred to the
EU budget by the United Kingdom since 2013.
The Commission is taking appropriate actions to ensure an effective follow up of the recommendations of the European Anti-fraud Office's investigation report and of the
DG BUDG's inspection findings 39 .
One general conclusion drawn by the Commission from its inspections in Member States in recent years is that their control strategies are increasingly shifting from customs controls at the time of clearance of goods to post-clearance customs controls. The customs controls before or at the time of clearance of goods remain however indispensable for addressing undervaluation and the detection of new types or patterns of fraud or irregularities. Therefore, the customs controls strategy should be
frequently reviewed taking into account recent detections or new risks.
Considering the fraud diversion and spreading of specific fraud mechanism, EU-wide and international cooperation in detection of irregular cases is more and more
required.
2.4.3.3. Particular cases of Member State failure to recover TOR
If TOR are not established because of an administrative error by a Member State, the
Commission applies the principle of financial liability. 40 Member States have been
41
held financially liable in 2016 for over EUR 32 million , and new cases are being
given appropriate follow-up.
39 The Commission performed in 2016 in Slovakia a traditional own resources inspection dedicated to undervaluation.
In this inspection, significant weaknesses were also detected.
40 Case C-392/02 of 15/11/2005. These cases are typically identified on the basis of Articles 220(2)(b) (administrative
errors which could not reasonably have been detected by the person liable for payment) and 221(3) (time-barring resulting from Customs’ inactivity) of the Customs Code, Articles 869 and 889 of the Provisions for application of the Code, or on the basis of non-observance by the customs administration of Articles of the Customs Code giving
rise to legitimate expectations on the part of an operator.
41 It includes customs duties and interest.
Part II - EXPENDITURE
S ECTION I - S HARED M ANAGEMENT
Sustainable Growth: Natural Resources
Success in previous decades in guaranteeing sufficient food production, has led to a shift in emphasis to, producing higher quality food for consumers, increasing farms' profitability, diversifying the rural economy and protecting the natural environment. There is a direct management component but the majority of expenditure is disbursed
by Member States under the following shared management funds.
The European Agricultural Guarantee Fund (EAGF) which finances direct
payments to farmers and measures to respond to market disturbances, such as private or public storage and export refunds.
The European Agricultural Fund for Rural Development (EAFRD) which
finances the rural development programmes of the Member States.
The European Maritime and Fisheries Fund (EMFF) which provides funding
and technical support for initiatives that can make the fishery industry more sustainable.
EAFRD and EMFF are among the five European Structural and Investment Funds (ESIF or ESI funds) which complement each other and seek to promote a growth and
job based recovery in Europe.
The EMFF is the successor of the European Fisheries Fund (EFF), for which the full resources have been committed by the end of 2014.
Table NR1 shows the financial resources available for this policy area.
However, in light of their belonging to the ESIF family, EFF and EMFF will be treated together with the other structural funds. EAFRD, also part of ESIF, will be
analysed separately from the EAGF, with the exception of a general introduction.
Table NR1: Financial instruments and 2016 appropriations for the Natural Resources Policies
Financial Management Appropriations 2016 As % of total budget instrument mode Commitments Payments Commitments Payments
EUR million EUR million % %
EAGF Shared 42 220 44 285 26.0% 31.3% EARDF Shared 18 676 12 306 11.5% 8.7% EMFF + EFF Shared 897 560 0.6% 0.4% Other programmes Direct 691 592 0.4% 0.4%
TOTAL 62 484 57 743 38.5% 40.9%
-
3.C OMMON A GRICULTURAL P OLICY (CAP)
3.1. Introduction
For the last 50 years the Common Agricultural Policy (CAP) has been the European Union's (EU) most important common policy. This explains why traditionally it has taken a large part of the EU's budget, although the percentage has steadily declined
over recent years.
The CAP is financed by two funds, EAGF and EAFRD, which form part of the EU's
general budget.
Under the basic rules for the financial management of the CAP, the Commission is responsible for the management of the EAGF and the EAFRD. However, the Commission itself does not make payments to beneficiaries. According to the principle of shared management, this task is delegated to the Member States, who themselves work through national or regional paying agencies. Before these paying agencies can claim any expenditure from the EU-budget, they must be accredited on
the basis of a set of criteria laid down by the Commission.
The paying agencies are, however, not only responsible for making payments to the beneficiaries. Prior to doing so, they must, either themselves or through delegated bodies, satisfy themselves of the eligibility of the aid applications. The exact checks to be carried out are laid down in the different sectorial regulations of the CAP and
vary from one sector to another.
The expenditure made by the paying agencies is then reimbursed by the Commission to the Member States, in the case of the EAGF on a monthly basis and in the case of EAFRD on a quarterly basis. Those reimbursements are, however, subject to possible financial corrections which the Commission may make under the clearance of
accounts procedures.
Apart from a difference in scope and objectives, the two funds also function differently. While entitlements and measures supported under the EAGF follow a yearly flow, those under the EAFRD are implemented through multi-annual
programmes, very much like the interventions financed through the other ESI funds.
Table NR2 shows the financial resources available for the CAP.
Table NR2: Financial instruments and 2016 appropriations for the CAP
Financial Management Appropriations 2016 As % of total budget instrument mode Commitments Payments Commitments Payments
EUR billion EUR billion % %
EAGF Shared 42 220 44 285 26.0% 31.3% EARDF Shared 18 676 12 306 11.5% 8.7% TOTAL 60 897 56 591 37.5% 40.1%
3.2. General analysis – Trend analysis
3.2.1. Irregularities reported 2012-2016
Table NR3 presents the trend of the irregularities (fraudulent and non-fraudulent)
reported by Member States for the period 2012-16 in relation to the funds concerned.
This shows a decrease between 2015 and 2016 by 16% and an increase by 76% between 2012 and 2016. However, while the irregularities affecting EAGF have remained relatively stable over time (-12% in comparison with 2015 and +20% with 2012), those related to the EAFRD have been constantly increasing until 2015 and then declined in 2016, as showed by the chart below (-18%% in comparison with
2015 and +117% in comparison with 2012).
Table NR3: Irregularities reported by Fund – 2012-16 for the CAP
REPORTING YEAR TOTAL
FUND 2012 2013 2014 2015 2016 PERIOD N N N N N N
EAGF 943 1 219 1 218 1 286 1 132 6 531
EAFRD 1 231 1 961 2 398 3 250 2 676 8 935
EAGF/EAFRD 7 13 16 20 25 374
TOTAL 2 181 3 193 3 632 4 556 3 833 15 840
It should be noted that the two funds function very differently, with the EAGF following an annual implementation, while programmes financed by the EAFRD have a multiannual logic, which resembles that of the ESI Funds. The trend of
irregularities detected and reported further highlights those similarities and therefore appears physiological.
The irregularities notified by a minority of Member States (Romania, Italy, Spain, Poland, Hungary, Portugal and France) represent about 70% of the total number of reported irregularities in 2016.
Table NR4 provides in the same form of Table NR3 information about the trends linked to the financial amounts involved in cases of reported irregularities, which have decreased by 59% in comparison with the previous year. For the monetary value, the largest share in 2016 is still represented by the EAFRD component, which becomes relatively predominant, if one bears in mind that it represents between 20% and 30% of the total resources for the CAP and the financial value of the irregularities reported counts for 67% of the total amount in 2016 and for the period 2012-2016.
The impact of the financial amounts involved in irregularities on payments is also very different between the two funds, as it is 0.20% for the EAGF and 1.50% for the EAFRD (0.48% on the overall 2016 CAP expenditure).
Table NR4: Financial amounts involved in reported irregularities by Fund – 2012-16
for the CAP
REPORTING YEAR TOTAL
FUND 2012 2013 2014 2015 2016 PERIOD
EUR EUR EUR EUR EUR EUR
EAGF 78 097 164 184 725 612 152 480 372 225 427 348 87 289 499 728 019 995 EAFRD 170 192 527 353 987 081 361 790 573 437 684 842 184 175 448 1 507 830 471 EAGF/EAFRD 460 548 1 149 970 1 936 513 2 796 963 1 652 729 7 996 723 TOTAL 248 750 238 539 862 663 516 207 459 665 909 153 273 117 676 2 243 847 188
The trend analysis about the financial amounts can be misleading as it can be greatly influenced by single observations of significant value. The continuous growth of the financial value of irregularities related to the EAFRD until 2015 is, however, in line with the general trend of irregularities reported showed in Table NR3.
3.2.2. Irregularities reported as fraudulent
Table NR5 presents the trend of the irregularities reported as fraudulent by Member States for the period 2012-16 in relation to the fund concerned. This shows a situation which is stable in comparison to 2015 (-3.5%). However, while the fraudulent irregularities related to the EAGF have decreased by 28%, those linked to the EAFRD have increased by 17%.
Despite these contrasting trends, for the third consecutive year in the analysed period, the irregularities reported as fraudulent related to the EAFRD have the highest share on the total (69%) and reaching 60% on the whole reference period 2012-16 (up from 47% in the previous analysis for 2011-15). The share of irregularities committed by beneficiaries of both funds appeared in only 1 occurrence.
Table NR5: Irregularities reported as fraudulent by Fund – 2012-16 for the CAP
REPORTING YEAR TOTAL
FUND 2012 2013 2014 2015 2016 PERIOD N N N N N N
EAGF 64 255 153 178 128 778
EAFRD 64 238 351 243 284 1 180
EAGF/EAFRD 2 6 2 7 1 18
TOTAL 130 499 506 428 413 1 976
The irregularities notified by three Member States (Romania, Poland and Bulgaria) represent about 55% of the total number of irregularities reported as fraudulent. This
concentration is far lower than in previous years.
Austria, Bulgaria, the Czech Republic, Denmark, France, Latvia and Sweden reported an increasing number of fraudulent cases.
The first ten countries taken together have reported 378 potential fraudulent cases, which represents 91% of the total (in 2013 they had reported 94% and in 2015 92%
of the total fraudulent irregularities).
Table NR6 provides in the same form of Table NR5 information about the trends linked to the financial amounts involved in cases reported as fraudulent, which have decreased by 57% in comparison with the previous. For the monetary value, the
largest share in 2016 is still represented by the EAFRD, which is predominant also if one takes into account the whole analysed period 54% of the total amount.
Table NR6: Financial amounts involved in irregularities reported as fraudulent by
Fund – 2012-16 for the CAP
REPORTING YEAR TOTAL
FUND 2012 2013 2014 2015 2016 PERIOD
EUR EUR EUR EUR EUR EUR
EAGF 23 057 468 107 363 086 46 161 774 52 778 723 12 393 638 241 754 689 EAFRD 12 436 910 77 286 737 57 915 599 90 055 026 49 437 884 287 132 156 EAGF/EAFRD 323 623 337 603 292 215 1 432 019 27 836 2 413 296 TOTAL 35 818 001 184 987 426 104 369 588 144 265 768 61 859 358 531 300 141
The trend analysis about the financial amounts can be misleading as it can be greatly influenced by single observations of significant value. For instance, the 'distance' observed in 2013 between the two funds, finds entire explanation in very few cases involving high amounts linked to the EAGF, which determine the divergence from the trend highlighted in Table NR5. In the period 2012-16, the share of the EAFRD
on the total is 54%, well above the share of the resources allocated to the fund on the total of the CAP resources over the same period.
Case study: Bulgaria EAFRD - Abuse of EU funds under the Rural Development Programme
While carrying out checks on projects under RDP 2014-2020, the State Fund Agriculture (DFZ) found six applications which indicated the existence of artificially created conditions for support, particularly operation of a market by the same suppliers and customers. In the cases concerned, six applications were submitted for the same investment (purchase of a certain type of agricultural machinery) to three offices of the State Fund Agriculture regarding investments to be implemented in four different regions of the country. A pointer to the existence of a corrupt scheme was the fact that in all six cases the tenderers’ bids for the supply of equipment were submitted by the same three companies, with the same date and validity, and that contracts for the sale and purchase of equipment in all six cases were signed with the same company, on the same date. It was established that the manufacturer of that particular type of agricultural machinery was a US company with an official dealer for Europe based in the Netherlands, and that the Dutch company had only one official representative for Bulgaria, namely the company mentioned as supplier of the equipment in all six bids.
Family relations were established between two of the tenderers, while three of the tenderers' managers were found to be members of the Management Board of a non-governmental sectorial organisation. Since the tenders
and sale/purchase contracts concluded between the tenderers and the Bulgarian supplier quoted a price of EUR 225 000 per unit of machinery, a study of the market environment was carried out using a particular macroeconomic approach called 'control purchase'.
That involved the creation of a special e-mail address used to receive an offer from the Bulgarian supplier that quoted a unit price of USD 160 000, including the possibility for a discount to be applied in the event of purchase of more than one unit. A study of the dynamics of the BGN/USD exchange rate during the relevant period did not show any significant changes. Consequently, the conclusion was drawn that the tender offers submitted for the six projects were intentionally inflated and used unreasonable prices to illegally benefit from EU funds and the national budget. The State Fund Agriculture referred the case to the Supreme Cassation Prosecutors’ Office.
The Sofia City Prosecutor’s Office initiated a check and asked the Directorate General of the National Police to carry out an audit, which confirmed the above facts. It also found that the managers of two of the applicant companies live as unmarried partners and use different companies to participate in the same tenders as different persons. It was established that the companies/individuals concerned had concluded contracts for the supply of eight units of agricultural machinery for a total of EUR 1 800 000 (unit price EUR 225 000). The real unit price quoted by the official representative was USD 135 000. The Sofia City Prosecutor’s Office initiated pretrial proceedings and asked AFCOS-MVR to check, via OLAF, what the unit price of the equipment in question is in the Netherlands. This check is currently being implemented.
3.2.3. Irregularities not reported as fraudulent
Regarding irregularities not reported as fraudulent, the number of those reported relating to EAFRD has been constantly increasing until 2015 (see Table NR7), while those related to EAGF remained relatively stable or recorded minor variations. Consistently with this trend, also the irregular financial amounts linked to the rural development instrument have been constantly increasing until 2015 (as highlighted in
Table NR8).
Only a marginal share of the irregularities not reported as fraudulent relates to infringements reported as affecting both funds (1% in 2016 and even less on the
analysed period, see Table NR8).
Table NR7: Irregularities not reported as fraudulent by Fund – 2012-16 for the CAP
REPORTING YEAR TOTAL
FUND 2012 2013 2014 2015 2016 PERIOD
N N N N N N
EAGF 879 964 1 065 1 108 1 004 5 020 EAFRD 1 167 1 723 2 047 3 007 2 392 10 336 EAGF/EAFRD 5 7 14 13 24 63 TOTAL 2 051 2 694 3 126 4 128 3 420 15 419
Unlike the fraudulent irregularities, the largest share, in terms of numbers, is for the EAFRD since 2012, and in the two last years of the period 2012-16 the number of irregularities linked to this fund have been at least the double of those affecting the
EAGF.
The irregular financial amounts related to the EAFRD have also been progressively increasing until 2015.
Table NR8 shows the information concerning the years 2012-16.
Table NR8: Financial amounts linked to irregularities not reported as fraudulent by
Fund – 2012-16 for the CAP
REPORTING YEAR TOTAL
FUND 2012 2013 2014 2015 2016 PERIOD
EUR EUR EUR EUR EUR EUR
EAGF 55 039 696 77 362 526 106 318 598 172 648 625 74 895 860 486 265 305 EAFRD 157 755 617 276 700 344 303 874 974 347 629 816 134 737 564 1 220 698 315 EAGF/EAFRD 136 925 812 367 1 644 299 1 364 944 1 624 893 5 583 428 TOTAL 212 932 238 354 875 237 411 837 871 521 643 385 211 258 317 1 712 547 048
3.3. Specific analysis
3.3.1. Modus operandi
3.3.1.1. EAGF
Table NR9 shows the most frequently categories of irregularity linked to fraudulent cases detected in relation to the EAGF in 2016 and the financial amounts linked to them. It also presents how these most recurrent categories have featured from 2012 to 2016 (included).
The most recurrent modus operandi is related to infringements linked to the documentary proofs requested, and in particular, to the use of 'false or falsified
declarations', 'false or falsified documents' and 'false or falsified request for aid',
‘declaration of fictitious product, species and/or land’ in line with what reported in 2015. ‘Quantities outside permitted limits, quotas
general for the whole period 2011-
or thresholds (related, respectively to products, species or land)’ remained a
significant reported type of breach.
For 12 of the 128 cases reported (10%), irregularities related to ‘Ethics and Integrity’ were specified. This typology refers to cases of ‘corruption’ and ‘conflict of interest’
in particular. In the previous four years taken into account for the analysis, other 31 cases had been reported.
Table NR9: Types of irregularities reported as fraudulent in relation to EAGF
irregularities reported as Irregularities reported as Code Type of irregularity fraudulent in 2016 fraudulent 2012-16
N EUR N EUR T11 Request 35 2 256 960 147 23 516 603 T14 Documentary proof 28 686 478 245 35 498 502 T15 Product, species and/or land 13 4 636 767 151 36 041 735 T19 Ethics and integrity 12 691 811 43 9 335 560 T16 (Non-)action 7 728 368 23 34 335 927 T11 | T13 Request / Accounts and records 6 433 132 12 2 430 490 T11 | T14 Request / Documentary proof 6 226 453 8 258 689 T12 Beneficiary 3 205 938 15 49 624 617 T14 | T11 Documentary proof / request 3 180 288 3 180 288 T16 | T11 (Non-)action / request 3 83 758 4 388 297
ALL OTHER 12 2 263 687 127 50 143 983
TOTAL TOTAL 128 12 393 640 778 241 754 691
When looking at the irregularities not reported as fraudulent, the situation is rather consistent with that presented in Table NR9 for those reported as fraudulent, with the top-10 categories represented in almost the same positions, as showed in Table NR10.
Table NR10: Types of irregularities not reported as fraudulent in relation to EAGF
irregularities not reported Irregularities not reported Code Type of irregularity as fraudulent in 2016 as fraudulent 2012-16
N EUR N EUR T11 Request 209 21 016 228 937 69 661 211 T15 Product, species and/or land 158 4 970 385 1257 89 958 790 T14 Documentary proof 150 9 440 594 709 87 595 360 T16 (Non-)action 143 12 133 022 774 75 174 525 T90 Other 130 15 053 740 304 22 845 806 T12 Beneficiary 55 2 761 515 220 13 508 414 T13 Accounts and records 39 1 165 585 69 2 780 773 T19 Ethics and integrity 26 824 313 82 3 894 045
(blank) 16 551 126 201 11 847 108 T11 | T15 request / product, species and/or land 12 535 666 124 31 317 710
ALL OTHER 66 6 443 689 343 77 681 561
TOTAL TOTAL 1 004 74 895 863 5 020 486 265 303
3.3.1.2. EAFRD
Table NR11 shows the most frequently categories of irregularity linked to fraudulent cases detected in relation to the EAFRD in 2016 and the financial amounts linked to them. It also presents how these most recurrent categories have featured from 2012 to
2016 (included).
In 2016, 61 irregularities reported as fraudulent indicated that breaches had occurred in relation to ‘Ethics and Integrity’ appearing as the most frequently detected. In the period 2012-2016 this category is the third most frequently detected, although the greatest majority of cases have been reported mainly over the last two years. The remaining detected typologies more frequently are in line with those reported in previous years and relate to the ‘documentary proof (supporting documents provided), the ‘request for aid’, the ‘quality of the beneficiary’, the 'implementation'
of the action.
Table NR11: Types of irregularities reported as fraudulent in relation to EAFRD
irregularities reported as Irregularities reported as Code Type of irregularity fraudulent in 2016 fraudulent 2012-16
N EUR N EUR T19 Ethics and integrity 61 6 873 057 115 8 810 221 T14 Documentary proof 57 8 692 464 231 56 197 738 T16 (Non-)action 43 7 782 437 137 67 478 241 T11 Request 33 6 992 747 108 26 195 816 T90 Other 16 10 997 173 42 32 829 009 T14 | T11 Documentary proof / Request 12 283 907 14 2 031 903 T12 Beneficiary 10 1 711 636 94 20 589 527 T15 Product, species and/or land 10 206 524 64 2 560 749 T12 | T14 Beneficiary / Documentary proof 6 606 075 31 6 853 850
blank 4 1 208 780 23 2 729 208 ALL OTHER 32 4 083 083 321 60 855 895
TOTAL TOTAL 284 49 437 883 1 180 287 132 157
When looking at the irregularities not reported as fraudulent, showed in Table NR12, the most frequently detected category is related to 'non-action' ('action not completed', 'failure to respect deadlines', 'action not implemented', 'irregular termination, sale or reduction'), which occurred in 39% of the cases not reported as fraudulent affecting the EAFRD in 2016. It is followed by 'documentary proof' representing 17% of the non-fraudulent cases ('Documents missing and/or not provided', 'documents incomplete', 'documents incorrect' and 'documents provided tool late'). 10% of the cases belongs to the category 'Beneficiary' ('Operator/beneficiary not having the required quality'). These three categories
together represent 66% of the cases reported in 2016.
Table NR12: Types of irregularities not reported as fraudulent in relation to EAFRD
irregularities not reported Irregularities not reported Code Type of irregularity as fraudulent in 2016 as fraudulent 2012-16
N EUR N EUR T16 (Non-)action 943 40 999 677 3 141 275 620 513 T14 Documentary proof 400 19 576 235 1 239 126 928 586 T12 Beneficiary 241 19 100 604 934 185 658 670 T11 Request 154 10 053 899 1 002 153 983 009 T90 Other 145 12 041 169 596 48 047 161 T15 Product, species and/or land 100 2 540 818 1 176 121 326 241 T16 | T12 71 5 434 228 121 11 392 724 T19 Ethics and integrity 49 7 260 020 188 29 250 903 T13 Accounts and records 46 1 695 955 120 6 122 630
T40 Public procurement (see annex Commission Decision
C(2013)9527) 31 1 587 687 41 5 165 261 OTHER 212 14 447 272 1 778 257 202 617
TOTAL TOTAL 2 392 134 737 564 10 336 1 220 698 315
Case study: Croatia, EAFRD - Forgery of an official document when applying for projects co-financed by EU funds
On the basis of a call for the implementation of the agriculture measure: "Supporting the development of small farms", an agricultural cooperative applied for subsidies. In the e-application (via AGRONET), the agricultural cooperative sent all necessary documents needed for the call.
During the review of documents received by the agricultural cooperative and before the payment, Intermediate body level 2 (IB2) suspected that one of documents (Certificate of No Tax Due), a document which is issued only by Tax Administration, was forged. The suspicion was related to mismatch of dates within the document. Namely, the date of issue was 1.1.2015 but the document stated that the agricultural cooperative did not have tax debt on 1.2.2015. Therefore, the date of issue of Certificate and the date of the tax debt were different. IB2 contacted the Tax Administration to check the validity of the Certificate. The Tax Administration determined that the Certificate was issued by the Tax Administration.
Actions initiated/conducted:
IB 2 reported the case to State Attorney’s Office and criminal proceedings were initiated against a person who was an employee of an EU funds consultancy. It was found that this person had scanned an older Certificate, changed the dates and sent the forged document along with other necessary data via e- application (AGRONET) on behalf of the agricultural cooperative. It was determined that the responsible person in the agricultural cooperative was not involved in this criminal act. The person concerned (employee of the EU funds consultancy) was convicted for committing criminal act of Forgery of an Official Document and was sentenced to eight months imprisonment, but was given a two-year suspended sentence according to Article 56 (2) & (3) of the Criminal Code on condition of not repeating the crime. Should he commit a criminal act within the period of two years he would be imprisoned for eight months.
3.3.2. Fraud and Irregularity Detection Rates by CAP pillar
Via its two funds (EAGF and EAFRD) the CAP acts on two main paths to support agriculture across Europe. The EAGF itself has two components with different aims: direct payments to farmers and measures regulating or supporting agricultural
markets.
Table NR13 shows the FDR and the IDR per type of policy measure. Further details
about this calculation can be found in paragraph 3.4.2.
Looking at the overall detection rate (FDR + IDR), direct payments clearly show a very low level of detections. This confirms previous findings of the Commission audit services that the level of errors (and consequently of the possible detections) represent only a marginal part of the resources available. The situation is different for market measures, in particular for the FDR, which is the highest of all shared management policy measures. Interestingly, the "Total detection rate" is equal to that of rural development and to that of the cohesion policy. Rural development, for its part, shows results that are exactly aligned to those of the other Cohesion policy
measures (see chapter 4.2).
Table NR13: FDR and IDR by CAP policy measure
Irregularities detected and reported 2012- Policy measure 2016 / payments 2012-2016
FDR IDR Total Pillar I - direct payments 0.03% 0.07% 0.1% Pillar I - market measures 1.1% 1.5% 2.6% Pillar II - rural development 0.5% 2.1% 2.6% TOTAL 0.1% 0.4% 0.5%
A part of the irregularities used for these calculations are not referred exclusively to a specific policy measure, but the reporting authority may have also included several budget posts as affected, referring to different measures. As it is not possible to attribute the specific amount to each individual budget post, they have been included in their full value for each policy measure. However, the total has been calculated on the total amounts reported by Member States and therefore no double counting has
occurred.
3.3.3. Market measures – fraudulent and non-fraudulent irregularities
As showed in Table NR13, market measures show high FDR and IDR. Table NR14 shows the number and financial amounts linked to fraudulent irregularities detected by market measure for the period 2012-2016, while Table NR15 shows those not
reported as fraudulent.
Table NR14: Irregularities reported as fraudulent in relation to market measures
Market measure Irregularities reported as fraudulent 2012-2016
N EUR
Products of the wine-growing sector 62 11 766 401 Fruit and vegetables 50 97 217 237 Sugar Restructuring Fund 18 4 281 688 Refunds on non-Annex 1 products 11 6 017 838 Olive oil 8 845 319
Pigmeat, eggs and poultry, bee-keeping and other animal products 6 21 598 329 Beef and veal 5 76 712 Food programmes 4 626 280 Milk and milk products 3 107 526 Other plant products/measures 3 10 777 051 Promotion 2 113 637 Sugar 2 7 539 117 Other plant products/measures / Refund 1 58 876 Refunds on non-Annex 1 products / Fruit and vegetables 1 368 053 TOTAL 176 161 394 064
Table NR15: Irregularities reported as fraudulent in relation to market measures
Market measure Irregularities not reported as fraudulent 2012-2016
N EUR
Products of the wine-growing sector 793 79 518 331 Fruit and vegetables 363 69 124 341 Pigmeat, eggs and poultry, bee-keeping and other animal products 76 29 670 746 Sugar 41 14 477 343 Sugar Restructuring Fund 78 12 167 836 Other plant products/measures 73 5 435 279 Milk and milk products 29 4 247 053 Food programmes 12 3 437 922 Olive oil 24 2 610 315 Promotion 23 2 557 525 Cereals 3 1 277 214 Refunds on non-Annex 1 products 16 893 261 Beef and veal 17 397 460 (blank) 1 39 049 Textile plants 2 30 952 Sheepmeat and goatmeat 2 30 623 TOTAL 1 553 225 915 250
3.4. Anti-fraud activities of Member States
Previous paragraphs have examined the trend and main features and characteristics of the irregularities reported as fraudulent.
The present paragraph aims at examining some aspects linked to the anti-fraud activities and results of Member States. Four elements are analysed and taken into
account:
-
(1)duration of irregularities (fraudulent and non-fraudulent). No analysis by Member State is presented in this section;
-
(2)the number of irregularities reported as fraudulent by each Member State (in 2016 and over a five years’ time period);
-
(3)the fraud and irregularity detection rates over the last five years (the ratio between the amounts involved in cases reported as fraudulent and the payments occurred in the financial years 2012 to 2016);
-
(4)the ratio of cases of established fraud on the total number of irregularities reported as fraudulent.
3.4.1. Duration of irregularities
Of the 37 110 detected irregularities (fraudulent and non-fraudulent) reported by Member States in relation to the programming period 2007-13, 18 142 (47% of the total) involve infringements that have been protracted during a given span of time. For the 1 750 irregularities reported as fraudulent this percentage is higher at 60%. The remaining part of the datasets refers to irregularities/breaches which consisted of a single act identifiable on a precise date (19% of the whole dataset and 26% of that represent exclusively by the fraudulent irregularities) or for which no information has been provided (34% of the whole dataset, but only 14% of the irregularities reported
as fraudulent).
Taking into account only those irregularities which have been protracted in time, their average duration is almost 20 months (i.e. almost 1 year and 8 months). For the
irregularities reported as fraudulent, this average is just one month less: 19.
3.4.2. Detection of irregularities reported as fraudulent by Member State
3.4.2.1. Reported in 2016
Table NR16 offers an overview of the irregularities reported as fraudulent by Member States in 2016. It also shows the related amounts, overall payments for the
agricultural policy and the FDR.
Belgium, Cyprus, Finland, Ireland, Malta, the Netherlands and Slovenia have notified no irregularity as fraudulent; seventeen (17) Member States reported less than 30 fraudulent irregularities; one (1) country reported between 30 and 60; two (2)
Member States more than 60.
Romania, Poland and Bulgaria are the three countries which have reported the highest
numbers.
Table NR16: Irregularities reported as fraudulent by Member States in 2016
Member Irregularities reported as Payments in FDR
State fraudulent in 2016 2016 2016
N EUR EUR
AT 2 27 444 1 357 588 988 0.00% BE 668 032 722 0.00% BG 60 12 107 506 1 000 734 848 1.21% CY 74 682 614 0.00% CZ 14 852 246 1 205 700 370 0.07% DE 3 231 833 6 277 306 989 0.00% DK 4 254 730 994 682 262 0.03% EE 5 1 735 030 254 025 620 0.68% ES 10 580 768 6 554 590 467 0.01% FI 963 599 710 0.00% FR 22 3 375 812 8 393 964 473 0.04% EL 2 38 015 2 888 822 583 0.00% HR 10 2 575 582 341 354 556 0.75% HU 24 1 154 158 1 664 275 889 0.07% IE 1 631 481 267 0.00% IT 20 2 707 009 5 475 136 257 0.05% LT 11 2 087 218 716 579 085 0.29% LU 46 158 034 0.00% LV 12 987 285 362 080 904 0.27% MT 11 619 941 0.00% NL 892 525 909 0.00% PL 97 13 020 953 4 709 693 469 0.28% PT 4 6 033 837 1 508 523 973 0.40% RO 108 14 007 684 2 709 162 157 0.52% SE 1 0 937 094 490 0.00% SI 275 064 714 0.00% SK 1 1 483 643 752 969 0.00% UK 3 80 766 3 968 612 007 0.00% TOTAL 413 61 859 359 56 526 847 266 0.11%
Paragraph 3.4.3 offers a detailed analysis of the FDR per policy pillar.
3.4.2.2. Reported during the period 2012-16
Table NR17 offers an overview of the irregularities reported as fraudulent by Member States between 2012 and 2016. It also shows the related amounts, overall
payments for the agricultural policy and the FDR.
Only Finland notified no irregularity as fraudulent; the majority of countries (22) reported less than 100 fraudulent irregularities; one (1) country reported between 100 and 200; two (2) Member States notified between 201 and 300 and other two (2)
more than 300.
Romania, Poland, Italy and Hungary are the countries which have reported the
highest numbers.
Table NR17: Irregularities reported as fraudulent by Member States between 2016 and 2017
Member Irregularities reported as Payments in FDR
State fraudulent in 2012-16 2012-16 2012-16
N EUR EUR
AT 9 87 236 5 965 929 090 0.00% BE 3 401 569 3 389 649 199 0.01% BG 163 20 095 312 4 744 822 653 0.42% CY 6 252 222 371 045 540 0.07% CZ 53 75 559 902 5 854 643 133 1.29% DE 25 2 799 744 31 599 980 686 0.01% DK 81 27 936 608 5 028 985 748 0.56% EE 30 10 360 149 942 541 988 1.10% EL 35 2 559 226 13 622 234 149 0.02% ES 52 2 621 559 33 266 059 904 0.01% FI 4 206 992 342 0.00% FR 56 29 413 378 45 446 306 415 0.06% HR 10 2 575 582 437 803 395 HU 253 20 142 925 8 641 867 386 0.23% IE 35 462 723 7 613 331 160 0.01% IT 280 58 548 849 28 950 919 471 0.20% LT 37 13 319 249 2 991 946 079 0.45% LU 1 252 050 215 037 302 0.12% LV 34 2 365 281 1 462 783 726 0.16% MT 6 175 628 72 502 220 0.24% NL 4 53 250 160 4 759 107 865 1.12% PL 346 55 453 478 24 403 757 307 0.23% PT 17 8 543 901 6 820 023 602 0.13% RO 378 134 686 086 12 128 876 705 1.11% SE 6 507 702 4 586 894 370 0.01% SI 14 1 213 360 1 224 888 227 0.10% SK 24 6 854 573 2 865 526 463 0.24% UK 18 861 693 19 737 269 357 0.00% TOTAL 1976 531 300 142 281 351 725 481 0.19%
Paragraph 3.4.3 offers a detailed analysis of the FDR per policy pillar.
3.4.3. Fraud and Irregularity Detection Rates by Member State
3.4.3.1. EAGF – Market measures
Market measures present FDR and IDR that are significantly higher than those concerning direct payments, as already seen in paragraph 3.3.2.
Table NR16 shows the Member States which have detected and reported potentially fraudulent irregularities in the period 2012-2016. Detections are measured against the expenditure over the same period to calculate the FDR. 16 Member States have
detected and reported potential fraudulent cases in this area.
Table NR16: Market measures: number of irregularities reported as fraudulent 2012- 2016, amounts involved and fraud detection rate by Member State
Irregularities reported as fraudulent Expenditure
MS 2012-2016 2012-2016 FDR
N EUR EUR %
AT 2 19 625 135 007 063 0.0% BE 2 390 000 376 460 679 0.1% BG 2 327 118 174 125 844 0.2% CY 2 81 332 34 717 758 0.2% DE 2 1 124 773 704 143 130 0.2% DK 1 7 526 516 68 140 899 11.0% ES 7 748 968 2 831 263 577 0.0% FR 49 28 142 814 3 069 506 188 0.9% EL 2 965 115 327 017 721 0.3% HU 35 7 670 513 314 030 684 2.4% IT 36 26 583 494 3 350 911 084 0.8% NL 3 46 900 603 366 354 074 12.8% PL 17 37 648 623 1 501 458 293 2.5% PT 2 1 890 221 573 765 796 0.3% RO 6 757 077 400 830 790 0.2% SI 8 617 273 39 839 904 1.5% TOTAL 176 161 394 065 15 069 304 944 1.1%
Individual cases involving significantly high amounts can produce a distortive effect on the overall analysis. This is particularly the case for Denmark and, even more, the Netherlands, which show the highest FDR despite the low number of detections. The case reported from the Netherlands is also referred to events dating back almost ten years.
Furthermore, a part of these irregularities are not exclusively referred to market measures, but the reporting authority may have also included in the budget post affected also direct payments and/or rural development. As it is not possible to attribute the specific amount to each individual budget post, they have been included in their full value.
Table NR17 shows the IDR per Member State, which therefore, refers to irregularities detected and reported as non-fraudulent.
Combining FDR and IDR, market measures have been the object of significant detections, equalling 2.6% of the payments, by national authorities in several Member States over the last years.
Table NR17: Market measures: number of irregularities reported as fraudulent 2012- 2016, amounts involved and irregularity detection rate by Member State
Irregularities not reported as Expenditure
MS fraudulent 2012-2016 2012-2016 IDR
N EUR EUR %
AT 3 473 737 135 007 063 0.4% BE 20 461 366 376 460 679 0.1% BG 1 800 406 174 125 844 0.5% CY 10 838 225 34 717 758 2.4% CZ 6 13 032 936 85 354 021 15.3% DE 74 1 965 999 704 143 130 0.3% DK 7 1 656 329 68 140 899 2.4% ES 429 28 025 486 2 831 263 577 1.0% FR 304 54 822 395 3 069 506 188 1.8% EL 42 2 348 581 327 017 721 0.7% HU 46 3 220 276 314 030 684 1.0% IE 4 144 252 68 324 277 0.2% IT 226 19 890 662 3 350 911 084 0.6% NL 86 15 693 609 366 354 074 4.3% PL 79 13 405 112 1 501 458 293 0.9% PT 108 5 062 186 573 765 796 0.9% RO 68 47 099 160 400 830 790 11.8% SE 15 16 251 187 88 800 123 18.3% SI 6 280 219 39 839 904 0.7% SK 7 244 782 45 447 778 0.5% UK 12 198 344 264 976 397 0.1% TOTAL 1 553 225 915 249 15 069 304 944 1.5%
A part of these irregularities are not exclusively referred to market measures, but the reporting authority may have also included in the budget post affected also direct payments and/or rural development. As it is not possible to attribute the specific
amount to each individual budget post, they have been included in their full value.
3.4.3.2. EAFRD - Rural development
Fraud and Irregularity Detection Rates concerning EAFRD over the last five years show overall similar results (2.6% of the payments paid out during the period 2012- 2016) to those already described for market measures.
There is, however, a wider distribution among Member States and no real distortive effect by individual cases involving high amounts. 25 Member States have reported potential fraudulent cases detected in relation to EAFRD during the period under consideration, as showed in Table NR18. Detections are measured against the
expenditure over the same period to calculate the FDR.
FDR in rural development is similar to that recorded in relation to the Cohesion policy. It is worth underlying that EAFRD functions in a way similar to that of the
other ESI funds and therefore this finding is not surprising.
Table NR18: Rural development: number of irregularities reported as fraudulent 2012-2016, amounts involved and fraud detection rate by Member State
Irregularities reported as fraudulent Expenditure
MS 2012-2016 2012-2016 FDR
N EUR EUR %
AT 5 44 206 2 324 081 145 0.0% BG 137 17 148 044 1 760 695 227 1.0% CY 4 170 890 100 708 148 0.2% CZ 39 69 771 598 1 606 872 681 4.3% DE 15 1 438 900 5 234 331 221 0.0% DK 3 212 058 388 967 224 0.1% EE 30 10 360 149 420 189 963 2.5% ES 27 1 357 130 4 695 504 081 0.0% FR 6 913 958 4 012 572 018 0.0% EL 18 752 593 2 216 344 496 0.0% HR 10 2 575 582 151 306 384 1.7% HU 211 11 837 708 2 207 890 533 0.5% IE 32 385 305 1 369 766 786 0.0% IT 71 7 455 768 5 922 742 895 0.1% LT 37 13 319 249 1 073 269 891 1.2% LU 1 252 050 44 581 031 0.6% LV 34 2 365 281 681 792 285 0.3% MT 6 175 628 44 716 000 0.4% PL 227 13 863 075 8 000 206 091 0.2% PT 12 6 556 785 3 025 346 083 0.2% RO 209 117 617 072 5 538 003 478 2.1% SE 4 436 273 1 086 205 855 0.0% SI 5 785 522 524 913 236 0.1% SK 23 6 853 089 918 158 816 0.7% UK 14 484 244 3 551 763 121 0.0% TOTAL 1 180 287 132 157 59 076 977 718 0.5%
A part of these irregularities are not exclusively referred to rural development, but the reporting authority may have also included in the budget post affected also direct payments and/or market measures. As it is not possible to attribute the specific amount to each individual budget post, they have been included in their full value.
Table NR19 shows the IDR per Member State, which therefore, refers to irregularities detected and reported as non-fraudulent.
Combining FDR and IDR, rural development interventions have been the object of significant detections, equalling 2.6% of the payments, by national authorities in all Member States over the last years.
Table NR19: Rural development: number of irregularities reported as fraudulent 2012-2016, amounts involved and irregularity detection rate by Member State
Irregularities not reported as Expenditure
MS fraudulent 2012-2016 2012-2016 IDR
N EUR EUR %
AT 50 975 737 2 324 081 145 0.0% BE 25 569 716 249 799 985 0.2% BG 101 17 901 045 1 760 695 227 1.0% CY 26 801 282 100 708 148 0.8% CZ 278 265 908 343 1 606 872 681 16.5% DE 265 10 695 212 5 234 331 221 0.2% DK 55 15 306 644 388 967 224 3.9% EE 152 4 855 816 420 189 963 1.2% ES 916 72 115 076 4 695 504 081 1.5% FI 67 1 317 279 1 507 365 232 0.1% FR 355 7 497 900 4 012 572 018 0.2% EL 313 6 556 670 2 216 344 496 0.3% HR 17 317 999 151 306 384 0.2% HU 862 39 446 980 2 207 890 533 1.8% IE 119 4 355 186 1 369 766 786 0.3% IT 872 42 065 039 5 922 742 895 0.7% LT 480 61 950 748 1 073 269 891 5.8% LV 113 3 611 278 681 792 285 0.5% MT 10 206 044 44 716 000 0.5% NL 291 9 388 976 418 883 813 2.2% PL 1040 38 863 498 8 000 206 091 0.5% PT 944 41 259 941 3 025 346 083 1.4% RO 2402 522 130 345 5 538 003 478 9.4% SE 103 29 714 251 1 086 205 855 2.7% SI 62 1 586 511 524 913 236 0.3% SK 154 15 549 432 918 158 816 1.7% UK 264 5 751 366 3 551 763 121 0.2% TOTAL 10 336 1 220 698 314 59 076 977 718 2.1%
A part of these irregularities are not exclusively referred to rural development, but the reporting authority may have also included in the budget post affected also direct payments and/or market measures. As it is not possible to attribute the specific
amount to each individual budget post, they have been included in their full value.
3.4.4. Ratio of established fraud / Dismissal ratio
Since the PIF Report 2014, the analysis has also tried to focus on the rate of irregularities reported as fraudulent by Member States for which a final decision was taken, establishing that fraud really occurred. By comparing updated data with those published in 2014, it is also possible to identify how many cases have been dismissed
(initially reported as fraudulent and then "declassified" or cancelled).
Table NR20, therefore, updates the table already published in the last two Reports indicating that the "ratio of established fraud" has slightly increased in comparison to last year (from 10% to 11%). Likewise, the dismissal ratio increased from 12% to
14%.
Table NR20: Number of cases of suspected and established fraud and ratio of established fraud – cases reported between 2009-13 in the CAP
Member Suspected Established Ratio Dismissal
State fraud fraud
TOTAL established TOTAL
fraud 2013 ratio
N N N % N %
AT 9 1 10 10% 10 0% BE 10 1 11 9% 12 -8% BG 167 59 226 26% 233 -3% CZ 24 1 25 4% 20 25% DE 17 4 21 19% 24 -13% DK 118 118 0% 118 0% EE 19 4 23 17% 22 5% ES 22 1 23 4% 29 -21% FI 0 #DIV/0! 1 -100% FR 13 13 0% 27 -52% GR 28 1 29 3% 34 -15% HU 66 7 73 10% 89 -18% IE 4 4 0% 4 0% IT 301 11 312 4% 409 -24% LT 5 5 0% 1 400% LU 1 1 0% 1 0% LV 5 2 7 29% 8 -13% MT 5 5 0% 5 0% NL 5 5 0% 4 25% PL 144 29 173 17% 194 -11% PT 2 1 3 33% 2 50% RO 103 8 111 7% 147 -24% SE 6 6 0% 6 0% SI 13 1 14 7% 16 -13% SK 4 1 5 20% 2 150% UK 8 2 10 20% 8 25% TOTAL 1 099 134 1 233 11% 1 426 -14%
If only the "decided" cases are taken into account (established fraud cases and
dismissals 42
3.5. Recovery cases
For an in-depth analysis of recovery and financial corrections in the CAP, see section 2.1.1.3.3 of the Annual Activity Report of DG AGRI and the Communication of the
Commission to the Parliament on the protection of the EU budget 43 .
42 Dismissals are always calculated.
43 To be adopted by the month of July 2017.
| 25 jul '17 |
Report from the Commission to the European Parliament and the Council: Protection of the European Union’s financial interests — Fight against fraud 2016 Annual Report COVER NOTE |
Secretary-General of the European Commission 11503/17 |