Scoring as a method of assessing credit risk
Abstract and keywords
Abstract (English):
The relevance of the topic is determined by the key role of accurate and manageable models in the sustainability of financial institutions, as well as by the strengthening of regulatory requirements for managing model risk and calibrating expected credit losses. In this paper, scoring is defined as assigning a borrower an integral score, which is a monotonic function of the probability of default over a fixed horizon, and is applied at the stages of pre-approval, underwriting, limiting, monitoring, collection, and reserve revaluation. The paper discusses the integration of disparate methodological approaches into a unified process framework, from data requirements (representativeness, quality, and traceability of transformations) and the selection of architectures (ballistic maps, logistic models, trees, and ensembles) to a consistent system of metrics (separation capacity, calibration, stability, and sensitivity to drift) and organizational procedures for managing model risk (independent validation, model catalogs, change control, and disaster recovery plans). It has been shown that interpretability and verifiability are necessary conditions for the applicability of complex algorithms, and that combining statistical rigor with transparent operational regulations increases the predictive power and manageability of a portfolio. It has been empirically proven that effective scoring reduces delinquency and reserves, increases conversion in green segments, optimizes prices and risk limits, reduces manual verification costs, and speeds up decision-making; however, key risks are associated with sample bias, feature drift, calibration degradation, and limited model portability between segments. The results are supplemented by the author's proposals: to create an internal library of reference sets and cases for regular reevaluation of models and comparison of architectures; to regulate scenario stress tests with an assessment of the sensitivity of approval thresholds and default probabilities to adverse macro scenarios; to systematize the model passport and implement independent monitoring of drift with formalized intervention thresholds.

Keywords:
scoring, credit risk, methodological approaches, risk management, interpretability, verifiability, monitoring
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