This paper examines the combination of traditional banking credit assessment techniques with contemporary internal sales accounting systems in Kazakhstan, aiming to augment the precision and resilience of financial assessments pertaining to SMEs. The proposed model consists of two discrete...

Bankruptcy prediction is currently a widely researched topic, as it typically results from a chain of negative events. Logistic Regression (LR) is one of the standard prediction tools; however, with advances in technology, machine learning (ML) methods are gaining prominence and demonstrating...

Banks often assume that higher credit limits increase customer default risk because greater exposure appears to imply greater vulnerability. This reasoning, however, conflates correlation with causation. Whether increasing a customer's credit limit truly raises the likelihood of default remains...

Islamic Microfinance Institutions (IMFIs) encounter distinct difficulties with credit scoring because they need to follow Shariah principles that combine riba bans with fair financial dealings regulations. Conventional credit scoring models exhibit two shortcomings: a poor capability to...

How borrowers respond to future changes in the interest rate on their debt matters for the transmission of monetary policy and for household financial stability. Combining bank data, a letter RCT, and a survey, we study this question in the context of the German mortgage market, where since 2022...

How borrowers respond to future changes in the interest rate on their debt matters for the transmission of monetary policy and for household financial stability. Combining bank data, a letter RCT, and a survey, we study this question in the context of the German mortgage market, where since 2022...

This study examines how climate-related physical and transition risks affect credit risk. We develop a modular framework based on a threshold model for credit migrations, linking the latent credit cycle to key economic indicators to measure credit risk in corporate bond markets. Using historical...

Machine learning credit scoring expands the informational frontier of retail lending, particularly for thin file borrowers, yet it also erodes the practical meaning of disclosure duties that anchor consumer protection and prudential oversight. The central financial implication is that...

This paper provides issuance-level evidence from an emerging economy with a dual-currency primary bond market, showing that currency denomination not only affects the level of corporate bond spreads but also fundamentally reshapes the transmission of macro-financial shocks across credit ratings....

In dynamic models of asset markets with asymmetric information and endogenous screening, the anticipation of signaling through delayed sales incentivizes originators to exert greater effort ex ante. A central prediction in those models is a positive relationship between screening effort and the...

This study addresses the quantification of credit risk in solidarity economy entities, proposing a new methodology to redefine the concept of a "default" in the frequent situations of extreme class imbalances. The objective is to develop and evaluate credit scoring models that enhance risk...

In the peer-to-peer (P2P) lending market, current studies focus on two categories of approaches to evaluate the loans, thus providing investment suggestions to the investors: credit scoring (i.e., predicting the credit risk) and profit scoring (i.e., predicting the profitability). However,...

Research background: Financial exclusion is a very important phenomenon due to its socio-economic nature. It is linked to social exclusion and means limited access to financial services and products provided, among others, by cooperative banks. In the paper, the author presents the reasons for...

The significant increase in non-performing loans (NPLs) during the escalating recession of the Greek economy motivates us to study the predictive power of credit rating models in periods of economic shocks. In parallel, we examined the responsibilities of bank management in the expansion of NPLs...

This paper uses survival analysis as a tool to assess credit risk in loan portfolios within the framework of the Basel Internal Ratings-Based (IRB) approach. By modeling the time to default using survival functions, the methodology allows for the estimation of default probabilities and the...

This study presents a novel Early Warning System for monitoring the credit risk of commercial customers at a large international bank headquartered in the Netherlands. Traditional early warning methods often rely on backward-looking indicators such as probability of default or loss given...