Our financial mathematics department has its methodological guidelines in data science and financial mathematics. Data Science refers to an interdisciplinary field of science with the goal of gaining knowledge from data. Often methods from machine learning are used, which are the basis for many applications in the field of artificial intelligence (AI). Financial mathematics includes stochastic modeling, simulation and optimization as well as statistical methods.
We use our expertise to make sustainable contributions to current social challenges in cross-sectoral areas of focus: demographic change, energy system transformation and digitization. We are convinced that cooperation generates more value than the sum of its parts, which is why we cooperate with partners from the institute, science and industry.
In the area of retirement provision, we have a holistic view of old-age provision in Germany and Europe in cooperation with the Product Information Office for Old-Age Provision.
Flexible loads will become more important in the energy system of the future. These will be price-sensitive in electricity trading, which means that a basic assumption of many models is no longer valid and we are developing new solutions in this area.
The digitalization of processes will open up new possibilities for efficiently checking billing transactions. We have already developed testing tools for several industries and are working closely with the industry on new algorithms. We are also expanding our expertise in the healthcare industry and are working with the public prosecutor's office and the police on the auditing of care service invoices.
In the course of the digitalization of processes, new possibilities arise for efficiently checking billing transactions. We have developed tools for several industries and are working closely with the industry on new algorithms.