Abstract
In the realm of anti-corruption initiatives, critical challenges need to be addressed for reinforcing the global fight against corruption. FALCON, a Horizon Europe research program, employs a multi-actor, evidence-based approach to develop actionable indicators and data-driven tools aiming to offer comprehensive corruption intelligence. In this context, the proposed prototype tool, ACRA (Advanced Corruption Risk Assessment), addresses FALCON’s objectives. Designed for Law Enforcement Agencies and Anti-corruption Authorities, ACRA enables real-time analysis for identifying high risks related to corruption cases. The platform allows for anomaly detection in ownership structures, generating corruption probability scores based on diverse risk indicators, providing an overall risk assessment report based on likelihood and impact, integrating inputs from various sources, and tracing cross-border links. ACRA stands as a customizable, real-time analytical platform prototype, facilitating the identification and prioritization of investigations. The current study contributes to the scope of the SAMOSXXIV conference by presenting the capabilities of the ACRA tool and the challenges addressed by it, focusing on transparency and on the sharing of insights that may benefit the broader research community.
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Co-funded by the European Union within the Horizon Europe programme, under FALCON project - grant agreement No. 101121281. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency. Neither the European Union nor the the granting authority can be held responsible for them.
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Peppes, N., Daskalakis, E., Alexakis, T., Adamopoulou, E. (2025). ACRA: A Cutting-Edge Analytics Platform for Advanced Real-Time Corruption Risk Assessment and Investigation Prioritization. In: Carro, L., Regazzoni, F., Pilato, C. (eds) Embedded Computer Systems: Architectures, Modeling, and Simulation. SAMOS 2024. Lecture Notes in Computer Science, vol 15227. Springer, Cham. https://doi.org/10.1007/978-3-031-78380-7_15
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