AccuRate* is a set of tools for calibration, validation and automated selection of PD models, which assigns corresponding credit scores and alphanumeric rating grades to borrowers and individual claims, based on their PD estimates. It provides state of art internal rating model fully aligned with regulatory requirements for transition from standardized to internal ratings based approach to calculating risk weighted assets under Basel framework. Smart brute force algorithm has been implemented to allow for globally optimal model search based on model predictive power.
AccuRate* is developed in a multi-layered architecture. Its components include:
AccuRate* employs logistic regression techniques for calibrating PD models, which are considered an industry standard and are recognized as the best practice, both by banks and their regulators. The result of the estimation is a PD model which is then subject to thorough validation, using in-sample and out-of-sample statistical tests, as well as by performing out-of-time model performance tests. The proceeding automated selection of optimal model specification is implemented through information criteria. Lastly, borrowers and exposures are assigned credit scores and mapped onto alphanumeric rating scale, using various techniques of statistical clustering.
AccuRate* has the following functionalities:
AccuRate* utilizes advanced methodologies for model calibration and validation in order to completely bypass common problems of standard logit models: multicollinearity, extreme factor values, missing values, and non-linear relationship between log odds and factor itself. These are overcome using AccuRate* by applying various data transformations and Firth’s bias reducing regression.
AccuRate* is well ahead of its peers both in terms of complexity and speed of calculations.
Key features of AccuRate* are the following:
AccuRate* comes with accompanying internal ratings model methodology where detailed introduction to statistical methods applied in modeling process is provided.