Detecting corruption in the digital age: big data issues and reform opportunities
The rise of big data offering real-time access to volumes of micro-level electronic data is the most visible face of the third generation of corruption measures. It has raised expectations for innovative methods of detection supporting bottom-up and top-down reforms. The “datafied society” has opened avenues for new quantitative analyses, many related to procurement and its political connections, often in the form of analyzing party and campaign financing, bid-rigging and beneficial ownership frauds, and network analysis based on news and court documents. However, challenges remain. Academic research requires access to good-quality data and specialized analytical tools. This chapter asks whether corruption studies have reached a plateau requiring new measurements using big data. It argues for new measures, in particular to address “legal corruption”, by linking corruption to practices such as lobbying, revolving doors, political finance, and for refining our notions of state, business and media capture. Reforms should tackle “big data ISSUES” (Inaccessible, Scattered, Structureless, Unreliable, Erratic, and Sizable data). This is crucial to prevent naive or superficial applications reducing the value of AI-based anti-corruption technologies which, if misused, could conceal corruption and mislead analysts and law enforcement.
Year of publication: 2026
Author: Fernanda Odilla