Machine Learning Applications in Credit Risk Assessment: Implications for Accuracy and Fairness in European Banking Markets

Abstract

CHARLES UNIVERSITY FACULTY OF SOCIAL SCIENCES Institute of Political Studies Department of Political Science Bachelor's Thesis 2026 Leonardo Mermoglia CHARLES UNIVERSITY FACULTY OF SOCIAL SCIENCES Institute of Political Studies Department of Political Science Machine Learning Applications in Credit Risk Assessment: Implications for Accuracy and Fairness in European Banking Markets Bachelor's Thesis Author of the Thesis: Leonardo Mermoglia Study programme: Philosophy, Politics and Economics Supervisor: Ing. Petr Špecián, Ph.D. Year of the defence: 2026 Declaration 1. I hereby declare that I have compiled this thesis using the listed literature and resources only. 2. I hereby declare that my thesis has not been used to gain any other academic title. 3. I fully agree to my work being used for study and scientific purposes. 4. During the preparation of this thesis, the author used Claude Code Pro with the Opus 4.6 model in order to have support with the code writing; ChatGPT-5 was also used to translate the Abstract and Summary sections in Czech language. After using these tools/services, the author reviewed and edited the content as necessary and takes full responsibility for the content of the publication. In Prague on 04/05/2026 Leonardo Mermoglia Bibliographic record MERMOGLIA, Leonardo. Machine Learning...