1 citations · 1 across the 2 of their papers we have counts for
5 papers
Is TabPFN the Silver Bullet for Insurance Pricing?
Bruno Deprez, Wouter Verbeke, Tim Verdonck
Modelling claim frequency and severity for non-life insurance pricing predominantly relies on generalised linear models, with gradient-boosted machines as the leading machine learn…
Inductive inference of gradient-boosted decision trees on graphs for insurance fraud detection
Félix Vandervorst, Félix Vandervorst, Bruno Deprez +2
Graph-based methods are becoming increasingly popular in machine learning due to their ability to model complex data and relations. Insurance fraud is a prime use case, since fraud…
GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money Laundering
Bruno Deprez, Bart Baesens, Tim Verdonck +1
Purpose: We introduce GARG-AML, a fast and transparent graph-based method to catch `smurfing', a common money-laundering tactic. It assigns a single, easy-to-understand risk score…
Network Analytics for Anti-Money Laundering -- A Systematic Literature Review and Experimental Evaluation
Bruno Deprez, Toon Vanderschueren, Bart Baesens +2
Money laundering presents a pervasive challenge, burdening society by financing illegal activities. The use of network information is increasingly being explored to effectively com…
Advances in Continual Graph Learning for Anti-Money Laundering Systems: A Comprehensive Review
Bruno Deprez, Wei Wei, Wouter Verbeke +3
Financial institutions are required by regulation to report suspicious financial transactions related to money laundering. Therefore, they need to constantly monitor vast amounts o…