Cohesion, Fisheries And Other Internal Policies

• Year: 2021

COHESION AND FISHERIES

72

operations for the design and dissemination of innovative and more productive ways of

working; (ii) access to employment, in particular operations for job-seekers and inactive

people, including the long-term unemployed and people far from the labour market, and (iii)

support for self-employment and business start-up.

The most frequent fraudulent violations were about the use of false or falsified documents.

High financial amounts were involved where fraudulent infringements of contract

provisions/rules took place. This type of fraud often consisted in incomplete or non-

implementation of the funded action. Most of fraudulent violations concerning ethics and

integrity were about conflict of interests. Infringements of public procurement rules were

the most reported among non-fraudulent violation, but only in 4% of these cases fraud was

detected.

Risk analysis has still a marginal contribution in detecting fraud, while information from

civil society (including information published in the media) has a significant and growing

role. This is not the case for non-fraudulent irregularities. Detection of fraud and irregularities

could improve through ex-post thematic risk analysis projects focusing on groups of past

transactions.

Two thirds of the irregularities have been occurring over a period of time, averaging nearly

one year and a half. The rest of the irregularities consisted of a single act identifiable on a

precise date. On average, it took more than one year to come to a suspicion that a fraudulent

irregularity had been committed and one year and a half to close the case after reporting.

These average times are expected to increase as the implementation of the operational

programme progresses.

With reference to the programming period 2014-2020, the Fraud Detection Rates (FDR)

recorded by Romania and Slovakia were very high, but due to single irregularities that

involved huge financial amounts. These irregularities also had a strong impact on the EU-27

FDR, which was about 1% and higher than in the programming period 2007-2013. In line

with the general deep decrease in non-fraudulent irregularities reported, the Irregularity

Detection Rate (IDR) was above 1% only in Slovakia, Romania, Bulgaria, Greece. At EU-27

level, IDR was about 0.7%, much lower that in the programming period 2007-2013. These

FDRs and IDRs for the programming period 2014-2020 are likely to change significantly in

the coming years, with progress in the implementation of the operational programmes.

After about 10 years from initial reporting, the share of cases of suspected fraud that have not

led to conviction remains very high, while the share of cases in which fraud is established is

low. This may signal the need to invest further in reporting suspected fraud and in the

investigation/prosecution phase.

Concerning shared management Funds for other internal policies, the FEAD was the Fund

most affected by fraud. More than 90% of the detections of non-fraudulent irregularities were

related to the following Funds: AMIF, the FEAD and the YEI.

COHESION AND FISHERIES

73

4.1. Introduction

Section 4 presents a statistical evaluation of irregularities and fraud detected by the Member

States during 2021, with reference to the cohesion and fishery policies. It places these

detections in the context of past years and relevant programming periods. The Member States

reported these irregularities and cases of fraud to the Commission through the Irregularity

Management System (IMS).

Over half of EU funding is channelled through the five European Structural and Investment

Funds (ESIF):

 The European Regional Development Fund (ERDF), which promotes balanced

development in the different regions of the EU;

 The European Social Fund (ESF), which supports employment-related projects throughout

Europe and invests in Europe’s human capital, i.e. its workers, its young people and all

those seeking a job;

 The Cohesion Fund (CF), which funds transport and environment projects in countries

where the gross national income (GNI) per inhabitant is less than 90% of the EU average.

In 2014-2020, these countries were Bulgaria, Croatia, Cyprus, Czechia, Estonia, Greece,

Hungary, Latvia, Lithuania, Malta, Poland, Portugal, Romania, Slovakia and Slovenia;

 The European Agricultural Fund for Rural Development (EAFRD)

74

, which focuses on

resolving the particular challenges facing the EU's rural areas;

 The European Maritime and Fisheries fund (EMFF), which helps fishers to adopt

sustainable fishing practices and coastal communities to diversify their economies,

improving quality of life along European coasts. Due to the operating rules of the EMFF

and the European Fisheries Fund (EFF), which are very similar to those of the other

Structural Funds, irregularities reported by Member States in relation to fisheries policies

are treated in this section, jointly with the Funds for cohesion and economic convergence.

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

European economy and environment. They mainly focus on five areas: (i) research and

innovation; (ii) digital technologies; (iii) supporting the low-carbon economy; (iv) sustainable

management of natural resources; and (v) small businesses.

The European Commission and the EU Member States jointly manage ESIF. Each Member

State prepared a partnership agreement, in collaboration with the Commission.

After this introduction, Section 4.2. focuses on general trends for fraudulent and non-

fraudulent irregularities. It compares detection in the programming period (PP) 2014-2020

with detection in PP 2007-2013, to better assess current trends in detecting irregularities.

Section 4.3. analyses more specifically fraud and irregularities to get a better undestanding on

how different areas of the cohesion policy were impacted, including research and innovation

and the green and digital transitions, which are central also to the Recovery and Resilience

Facility. The same section includes an analysis of the types of violations reported for the

cohesion policy. Section 4.4. focuses on the reasons for carrying out checks that led to the

detection of irregularities. Section 4.5. takes a closer look at the Member States’ anti-fraud

activities and the results obtained, analysing fraud and irregularity detection rates (the ratio

between the amounts involved in cases reported as fraudulent (FDR) or not reported as

74

EAFRD expenditure is co nsidered in Section 3 'Common agricultural policy', when focusing on rural

development.

COHESION AND FISHERIES

74

fraudulent (IDR) and the relevant payments). Section 4.6. provides figures on other shared

management Funds.

4.2. General analysis

The analysis in this section 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 is focused on the current Member States and the EU-27 aggregate. In the whole

section, when reference is made to ‘fraudulent’ or ‘fraud’, it includes ‘suspected fraud’ and

‘established fraud’.

75

Member States are requested to communicate:

 non-fraudulent irregularities only when they are detected after the expenditure has been

introduced in a statement submitted to the Commission. This derogation does not apply to

fraudulent irregularities: Member States must always report them.

 fraudulent and non-fraudulent irregularities with financial amounts above EUR 10 000.

During 2017-2021, several Member States reported also a number of irregularities below

this threshold. However, these irregularities represented about 1% of all irregularities

reported (EU-27). They are included in the analysis for this section, to make use of all

available information.

76

Analysis of the EU cohesion policy is more complex than other budget sectors, as

information refers to different programming periods, which are regulated by different rules.

4.2.1. Irregularities reported as fraudulent

4.2.1.1. Trend by programming period

Table CP1 below provides an overview by programming period and by Fund of the

irregularities reported as fraudulent in the past 5 years (2017-2021)

77

.

Fraudulent irregularities related to PP 2007-2013 peaked in 2015, gradually decreased in

the following years and in 2018 they were overtaken by those related to PP 2014-2020. These

dynamics are in line with known trends and patterns in the detection and reporting of

irregularities and are linked to the PP 2007-2013 implementation cycle

78

.

75

‘Suspected fraud’ means an irregular ity that gives rise to the initiation of administrative or judicial

proceedings at national level in order to establish the presence of intentional behaviour, in particular fraud, as

referred to in Article 1(1)(a) of the Convention drawn up on the basis of Article K.3 of the Treaty on European

Union, on the protection of the European Communities’ financial interests’. Regardless of the approach adopted

by each Member State, ratification of the 1995 Convention has equipped every country with a basis for

prosecuting and possibly imposing penalties for specific conducts. If this occurs, i.e. a guilty verdict is issued

and is not appealed against, the case can be considered ‘established fraud’. See ‘Handbook on ‘Reporting

irregularities in shared management’ (2017).

76

Data for this section was downloaded from the irregularity management system (IMS) on 7 March 2022.

When entering a case, the contributor is requested to specify the currency in which the amounts are expressed.

Where the value of this field is 'EUR' or the field was left b lank, no transfor mation is applied . Where this field

was filled with another currency, the financial amounts involved in the irregularity have been transformed ,

based on the exchange rates published by the European Central Bank (ECB) at the b eginning of 2022.

77

In some cases, the Member States reported irregularities as non- fraudulent, while a pe nal procedure had been

started. This may be due to the need to wait for some procedural steps before classifying an irregularity as

fraudulent. These cases are not included as fraudulent in the analysis for this report; considering them as such

would increase the number of fraudulent irregularities b y about 11% (1% in terms of financial amounts

involved).

78

When s upport is based on multiannual progra mmes, the number of irregularities can be expected to increase

around the end of the eligibility period and decrease afterwards, when ro utine controls are less intense. In