Data-driven banking and insurance

Banks and insurance companies strive to use the large amounts of data that become available internally and externally to analyse the behaviour of their customers.

The aim of this project is to develop fundamental insights and new techniques for Big Data analysis for banks and insurers for a wide range of applications. Think of detecting unwanted intrusions into computer networks, detecting fraud, predicting defaults and predicting extreme insurance claims.

The theme of the research is the efficient combination of large amounts of data with the knowledge of the experts, so that the strong characteristics of man and machine can be used optimally. We bring in three important data science expertises: predictive analysis, modern statistics and visual analysis. This unique combination will lead to breakthroughs in the banking and insurance sectors. We use a two-phase approach: first, new techniques will be developed for familiar situations; in the second phase, we aim for new applications, such as the automatic development of new products.


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