معرفی
Christophe Mues is a Professor of Data Science and Information Systems at the University of Southampton's Department of Decision Analytics and Risk. He specializes in credit scoring, consumer credit risk modeling, and predictive analytics, focusing on applications like loan default prediction and debt collection optimization. His work integrates advanced statistical methods and machine learning techniques to address challenges in financial risk assessment.
Previously, he held a research position at KU Leuven (Belgium), where he earned his Doctorate in Applied Economics. Since joining the University of Southampton in 2004, he has led the Information Systems & Business Analytics section and contributed to organizing the biennial Credit Scoring and Credit Control conference. His teaching spans data-driven decision-making and business analytics.
Key research interests include credit risk modeling for consumers and SMEs, leveraging non-traditional data sources with deep learning, ensuring fair credit scoring models, and optimizing debt recovery strategies. He currently supervises PhD students in Business Studies & Management, focusing on topics like AI-driven credit scoring and financial risk evaluation.
His publications span journals like European Journal of Operational Research and International Journal of Forecasting, emphasizing methodological advancements in credit risk assessment and financial decision-making. He actively participates in interdisciplinary collaborations to bridge operational research, data science, and financial regulation.
