Scoring models as a driver of retail banking credit risk management
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Scoring models as a driver of retail banking credit risk management

Scoring models as a driver of retail banking credit risk management
Статьи, Журналы

Scoring models as a driver of retail banking credit risk management

Girinsky, A.V. Scoring models as a driver of retail banking credit risk management / A. V. Girinsky, A. O. Aldoshin // Финансовые рынки и банки. — Москва, 2025 — N 11. — С.229-233. — Библиогр. в конце ст.
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Финансовые рынки и банки, 2025, N 11
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Аннотация

In the context of retail banking, the evolution of scoring models represents a consistent transition from deterministic logistic regressions to nonlinear machine learning algorithms, which has fundamentally transformed the credit risk management paradigm. The historical retrospective demonstrates how the integration of alternative data and artificial intelligence methods not only increased the discriminatory ability of forecasts, but also led to convergence of credit and operational risks, since the complexity of the models itself became a source of operational losses related to interpretability, data biases and regulatory compliance requirements. The article discusses the prospects for development in the field of creating hybrid systems, where scoring functions as the core of a unified risk management.

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