The Credit risk model validation team of KBC Group gave a lecture on “Anomaly Detection” to the students of the master's program “Artificial Intelligence for Business and Finance”.

Anomaly detection is a very important step in data processing and analytics. During the lecture, the students got familiar with various techniques in this field and their application in practice, presented by Veselin Mitrov, Mitko Tanev and Petar Damyanov.

In addition, students were given the opportunity to participate in two different analytical projects: Explain ability of tree-based algorithms and Outliers' detection for LGD models, that could be subsequently developed into a master's thesis. Any student can apply by preparing a motivation letter. Finally, two students will be selected to work independently on each of the projects, in return for which they will receive a scholarship and an internship opportunity at the Credit risk model validation team of KBC Group, tailored to their study schedule.

The management of the Faculty of Economics and Business Administration expresses its gratitude to Dr. Irem Yaman and to the entire “Credit risk model validation” team.