8 papers
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…
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…
Native Design Bias: Studying the Impact of English Nativeness on Language Model Performance
Manon Reusens, Philipp Borchert, Jochen De Weerdt +1
Large Language Models (LLMs) excel at providing information acquired during pretraining on large-scale corpora and following instructions through user prompts. This study investiga…
Are Economists Always More Introverted? Analyzing Consistency in Persona-Assigned LLMs
Manon Reusens, Bart Baesens, David Jurgens
Personalized Large Language Models (LLMs) are increasingly used in diverse applications, where they are assigned a specific persona - such as a happy high school teacher - to guide…
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…
On the Performance of LLMs for Real Estate Appraisal
Margot Geerts, Manon Reusens, Bart Baesens +2
The real estate market is vital to global economies but suffers from significant information asymmetry. This study examines how Large Language Models (LLMs) can democratize access…