This paper examines the issues of the aggregation and comparison of the credit ratings of various economic agents for risk management purposes in a commercial bank. The empirical results of the study make it possible to increase the assessment of credit risks based on the constructed system of...

The recent financial crisis proved that financial contagion could spread among countries resulting in disruptive effects. In this paper, by modeling and simulating banking system behavior and linkages across countries, we assess, based on data from the BIS and IMF, the possible outcome of...

Bank lending is a major source of income for a bank. Compliance with higher Basel capital requirements (CAR) portends serious implication for distribution of loan portfolio across different sectors. The objective of the study is to examine African banks' responses to higher CAR in terms of...

We propose a simple, parsimonious, and easily implementable method for stress-testing banks using a top-down approach that evaluates the impact of shocks to macroeconomic variables on banks' capitalization. Our method relies on a variable selection method to identify the macroeconomic drivers of...

The transformation of credit scores into probabilities of default plays an important role in credit risk estimation. The linear logistic regression has developed into a standard calibration approach in the banking sector. With the advent of machine learning techniques in the discriminatory phase...

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 different phases of the credit cycle (e.g. application, behavioural, collection models). The credit score empowers users...

The problem of credit risk management at commercial banks is solved using the stochastic dominance criteria supplementing them with the voting theory elements. The developed stochastic dominance algorithm is based on an investment approach whose basic concept consists in management of both...

Retail credit issuers traditionally rely on cutoffs derived from risk-based scorecards for acquisition and account management purposes. However, in recent years, advances in data and increased comfort with advanced modeling practices such as machine learning have given rise to more sophisticated...