Anti-fraud tools

• Author: Mélissa Campagno - Goya Razavi - Brian Kessler - Léna Bonnemains - Olga Mala
• Pages: 19-23

DG REGIO

Study on the implementation of Article 125(4)(c) of the CPR in the Member States

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4. Anti-fraud tools

This section assesses the use of anti-fraud tools by the authorities of the 50 selected OPs.

Authorities are using a number of national and EU-wide tools to detect and prevent fraud in ESI

Funds. While all authorities are using the Irregularity Management System (IMS) for reporting

irregularities to OLAF, they also implement a number of specific tools that are used for preventing

and detecting fraud. In this section we analyse the use of these tools, such as Arachne.

4.1 Uptake of Arachne

The majority of the interviewed MAs do not use Arachne . Only one third of the

interviewed MAs26 are using Arachne as a risk scori ng or fraud detection tool (see figure below)27.

The ma jority of the MAs that are using the tool consid er it gives added value to assess potential

conflicts of interest, and identifying red flags.28

Figure 3: Use of Arachne across Operational Programmes

Source: PwC, based on a sample of 45 OPs

MAs mentioned the following difficulties regarding the use of Arachne :

 Data collection and accuracy issues;

 High number of false positives;

 Legislative barriers, in particular compliance with national data protection laws .

All interviewed MAs are aware of the existence and technical capabilities of Arachne. However, a

number of issues were raised both by the MAs that are already using the tool, and by the MAs that

are not using or planning to use it.

Authorities for eight OPs mentioned the incompleteness of the database as a reason of not using

Arachne. More specifically, they refer to the fact that not all OPs and not all MS have provided dat a

to the system and therefore the checks cannot be done against all the MS. This provides uncertainty

in the results and reduces the added value of the tool when the checks co ver several MS.

Authorities for six OPs mentioned outd ated data. Arachne calculates risks for all MS every week,

based on available data. However, part of this data is periodicall y uploaded by MAs.29 It is not

26 Arachne is available for OPs under ERDF, ESF, CF, YEI and FEAD, but not EMFF OPs at the moment of this analysis. Therefore,

five EMFF OPs out of the sample of 50 OPs are excluded form analysis of Arachne usage in the sections below.

27 The data represented in this section was collected in October 2017- March 2018. The actual number of OPs that are using Arachne at

the moment of publication could be different, potentially including OPs that were planning to use or had piloted Arachne at the time of

the data collection.

28 This study does not assess the extent to which different functionalities of Arachne are explored by OPs in the sample and does not

assess the completeness of the data that OPs have available when working with Arachne.

29 Data on their projects, contracts and expenses.

51%

16%

33% Does not use Arachne

Plans to use Arachne in

the future

Uses Arachne