Credit bureaus gather, aggregate and analyse information about consumers and business entities in order to assess credit related risks. On a methodological and technical level this involves the integration and quality assurance of data from various sources, the analysis of incoming data streams and the ability to train and apply predictive models. In this talk we will give an overview of challenging tasks related to use cases in the credit bureau industry and illustrate some modern approaches in the field of machine learning and data mining to address these tasks. All information about the talk available at https://www.uni-koblenz-landau.de/de/koblenz/fb4/ifi/Kolloquien/kolloquium_Gottron. Slides from this talk are available here.
31.01.2018 - 16:15