77 citations · 154 across the 21 of their papers we have counts for
26 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 (GLMs), with gradient-boosted machines as the leading machin…
Foundation Models for Credit Risk Prediction: A Game Changer?
Bart Baesens, Andreas Goethals, Stefan Lessmann +10
Predictive models play a pivotal role in credit risk management, guiding critical decisions through accurate estimation of default probabilities and losses. Extensive research has…
Inductive inference of gradient-boosted decision trees on graphs for insurance fraud detection
Félix Vandervorst, Bruno Deprez, Wouter Verbeke +1
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
Money laundering, a global problem estimated to account for 2%-5% of the global GDP, required regulators to enforce stringent rules on financial institutions to combat it. One prom…
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…
Sources of Gain: Decomposing Performance in Conditional Average Dose Response Estimation
Christopher Bockel-Rickermann, Toon Vanderschueren, Tim Verdonck +1
Estimating conditional average dose responses (CADR) is an important but challenging problem. Estimators must correctly model the potentially complex relationships between covariat…