Credit risk rating systems at large US banks

Feasibility Study of Credit Risk Rating Systems in Banks

Cost Stickiness and Banks Credit Risk

The credit risk in banks is a function of the profitability and quality of bank assets. Moreover, cost stickiness also affects the quality of assets and profitability of banks. To achieve the research aims, is to explore relationship between cost stickiness and banks credit risk were tested and analyzed is based on pooling data from 21 banks in duration 2012-2019. The findings show that there i...

Linear versus nonlinear dimensionality reduction for banks' credit rating prediction

Dimensionality reduction methods have shown their usefulness for both supervised and unsupervised tasks in a wide range of application domains. Several linear and nonlinear approaches have been proposed in order to derive meaningful low-dimensional representations of high-dimensional data. Among nonlinear algorithms manifold learning methods, such as isometric feature mapping (Isomap), have rec...

Rating the Actual Customers of Banks based on Credit Risk using Multiple Criteria Decision Making and Artificial Intelligence Hyperbolic Regression

This study wants to investigate the rating of the actual customers of banks based on credit risk using multiple criteria decision making and artificial intelligence hyperbolic regression. This is an applied research. The statistical population of the study includes the credit customers of Agriculture Bank in west branches of Mazandaran province, Iran in 2012-2016. A total of 100 cases have been...

Forecasting Credit Risk in Banks Listed on Tehran Stock Exchange

The present study aim is to offer a systematic method of assessing the credit risk of banks and also to identify key indicators using Decision Making Trial and Evaluation Laboratory (DEMATEL) technique as well as using Logit Regression in order to predict the credit risk of listed banks. The population of the study consists of the legal clients of the bank (Ansar Bank, Bank Saderat Iran, Bank M...