Traditional and Machine Learning Algorithms in Evaluation of Financial and Non-financial Determinants of Russian Banks Stability

Student: Kudryashova Anna

Faculty: International College of Economics and Finance

Educational Programme: International Programme in Economics and Finance (Bachelor)

Final Grade: 8

Year of Graduation: 2024

Present work elaborates on the topic of default probability estimation in the realm of the Russian credit market. The key purpose is identification of significant financial ratios, institutional and macroeconomic indicators, capable of signalling about the quality of banking system functioning. Additional attention is paid to the methodology, resulting in the assessment of both classical approaches, namely, Logit models and more sophisticated machine learning algorithms with respect to their predictive abilities, based on several alternative versions of the initial datasets.

Full text (added June 10, 2024)

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