PROBABILITY OF DEFAULT MODELS UNDER CREDIT RISK VALUATION
This article describes some aspects of building and assessing the quality of mathematical models for predicting the probability of default as part of the process of assessing the credit risk of counterparties. Special attention is paid to the issue of calibration of the constructed models. It is proposed to use Brayer's estimate as the calibration metrics, and Platt's calibration and isotonic regression to carry out the correction itself.