Christophe Mues is Professor of Data Science and Information Systems, specialising in credit scoring and other applications of analytics in consumer lending.
- Credit scoring
- Predictive analytics
- Machine learning
- Credit risk
- Loss Given Default (LGD)
Professor Mues is currently researching a variety of topics relating to consumer or SME credit risk modelling, including but not restricted to the use of deep learning techniques to incorporate non-traditional data sources, the transparency and fairness of credit scoring models, and debt collection.
Professor Mues teaches a variety of subjects relating to information systems and business analytics.
Previously, he was employed as a researcher at KU Leuven, Belgium, where he obtained the degree of Doctor in Applied Economics. Having joined the School in September 2004, he now leads the Information Systems & Business Analytics section within the Department of Decision Analytics and Risk. He is a member of the organising committee for the main conference in the credit scoring area (the biennial Credit Scoring and Credit Control conference).