Big data analytics as a tool for auditors to identify and prevent fraud and corruption in public procurement

Adam, I. & Fazekas, M. (2019). Big data analytics as a tool for auditors to identify and prevent fraud and corruption in public procurement. European Court of Auditors Journal 2/2019: pp. 172-179.

ECA Journal Short Read:

Government contracts and big data analytics – big data in public procurement can help auditors on two levels: (1) it can facilitate decisions about monitoring, audit and investigations; (2) it can inform country or sector-wide policy decisions on resource allocation and regulations.

Measuring corruption requires a proxy – a ‘corruption risk index’ (CRI) has been developed, combining four observable risk indicators: (1) tendering risk; (2) political connections; (3) supplier risk; and (4) contracting body risk.

Interpreting procurement data is difficult – publication practices, format and data quality vary between different online publication platforms and systems, leading to a lack of transparency.

A comprehensive, standardized dataset – the EU-funded DIGIWHIST project has collected, standardised and republished data from 32 countries in a dataset containing about 20 million contracts from across Europe. This enables auditors to measure fraud and corruption in public procurement at unprecedented levels of precision.

See the full article here from page 172.