Credit risk models are commonly based on large internal data sets to produce reliable
estimates of the probability of default (PD) that should be validated with time. However, in …

In contemporary world, binary choice models are used in many areas. However, for all such
areas, a problem arises when the share of one of the classes in the data sample is small. If …

Credit scoring models play a fundamental role in the risk management practice of most
banks. They are used to quantify credit risk at counterparty or transaction level in the …

Abstract The Basel Committee on Banking Supervision finalized the Basel III accord in the
December 2017 and launched the set of its standards–the Basel Framework–in December …

Credit scoring models play a fundamental role in the risk management practice at most
banks. They are used to quantify credit risk at counterparty or transaction level in the …

The main focus of this thesis is to provide a comprehensive assessment of default risk
modelling: the relevant literature, the empirical implementations and the levers driving …

The issue of estimating the probability of default constitutes one of the foundations of risk
systems applied in modern banking. The Basel Committee pays a lot of attention to ways of …

В работе представлен метод построения кредитных рейтинговых моделей в условиях
недостаточной статистики наблюдаемых дефолтов на примере рейтинговой модели …

This article proposes a logistic regression model to predict future unpaid debts and optimize
the recovery portfolio of the Support Fund for Large Ivorian Enterprises (FSGE-COVID-19) …

Consider a bank which wishes to decide whether a credit applicant will obtain credit or not.
The bank has to assess if the applicant will be able to redeem the credit. This is done by …