In the course of my work at the Deutsche Bundesbank, I have been dealing with various quantitative models and methods used by banks in the context of risk measurement for 10 years now. My main task is to assess whether the mathematical models comply with the regulatory requirements. I do not have a specific focus, but cover the entire range of risk types as well as banks. Therefore, I have been able to acquire and successfully apply an extensive range of knowledge of different mathematical methods and models as well as the associated regulatory rules during my work so far.
Besides the theoretical aspects, I reprogram the models of the banks and also program my own models. Usually I use R for programming (if it should be implemented quickly) or C# (if it should run user-friendly and fast). Since in the last years models with artificial intelligences / machine learning have become more and more important, I have extended my knowledge spectrum to AI models. I usually program these in Python, since Python has very powerful libraries in this regard.
Before joining the Bundesbank, I worked as a research assistant at the Chair of Applied Analysis at the University of Rostock under Prof. Dr. Takác and received my PhD during this time. In my dissertation I worked on nonlinear Black-Scholes equations. My research interests were mainly in the area of partial differential equations and their application in financial mathematics. Since the application of differential equations at banks is generally limited to valuation models in trading (market price risk), I see differential equations only occasionally in my professional environment. Therefore, and due to increasing private commitments, I have not been able to pursue my original research interests lately.