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The University of Southampton
CORMSIS Centre for Operational Research, Management Sciences and Information Systems

Credit Risk Modeling: A Benchmark of Machine Learning Methods (joint CORMSIS and CRR seminar)  Event

13:00 - 14:00
2 March 2016
Room 1043 Building 58

For more information regarding this event, please telephone Dr Yuan Huang on +44(0)2380595168 or email .

Event details

Credit scoring involves the development of empirical models to support decision making in the retail credit business. In particular, financial institutions use predictive models, called scorecards, to decide upon new credit applications or to manage existing loan agreements. Such scorecards estimate the probability of a borrower to default. The paper presents results of a comprehensive benchmark experiment in which we contrast the performance of 41 alternative forecasting methods across eight real-world credit scoring data sets. The objective of the study is to examine the potential of recent advancements in the field of predictive analytics for credit scoring. More specifically, we consider several novel learning methods that are for the first time assessed in a credit scoring context. Furthermore, using the principles of cost-sensitive learning, we shed light on the link between the (statistical) accuracy of scorecard predictions and a scorecard's business value. Finally, we examine the extent to which different indicators of predictive accuracy agree in their scorecard assessment and thereby contribute to a recent debate concerning the appropriateness of receiver operating characteristics. Our study provides valuable insight for professionals and academics in credit scoring. It helps practitioners to stay abreast of technical advancements in predictive modeling. From an academic point of view, the study provides an independent assessment of recent prediction methods and offers a new baseline to which future models can be compared.

Speaker information

Professor Stefan Lessmann,Humboldt-University of Berlin,Stefan received a diploma in business administration and a PhD from the University of Hamburg in 2002 and 2007, respectively. He worked as a lecturer and senior lecture in business informatics at the Institute of Information Systems of the University of Hamburg. Since 2008, Stefan is a guest lecturer at the School of Management of the University of Southampton, where he teaches under- and postgraduate courses on quantitative methods, electronic business, and web application development. Stefan completed his habilitation in the area of predictive analytics in 2012. He then joined the Humboldt-University of Berlin in 2014, where he heads the Chair of Information Systems at the School of Business and Economics. Stefan published several papers in leading international journals and conferences, including the European Journal of Operational Research, the IEEE Transactions of Software Engineering, and the International Conference on Information Systems. He actively participates in knowledge transfer and consulting projects with industry partners; from small start-up companies to global players. More info:

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