In response to the call of the Chinese government to support low-carbon development, the issue has come to the view gradually as to whether the behaviors of banks’ green credit will contribute to easing their own credit risk. To reflect the behaviors of green credit of banks in detail, an indicator, named the carbon intensity of loans (CIL), is first proposed in this paper to measure the carbon...

There are many methods introduced to solve the credit scoring problem such as support vector machines, neural networks and rule based classifiers. Rule bases are more favourite in credit decision making because of their ability to explicitly distinguish between good and bad applicants.In this paper multi-objective particle swarm is applied to optimize fuzzy apriori rule base in credit scoring. ...

There are many methods introduced to solve the credit scoring problem such as support vector machines, neural networks and rule based classifiers. Rule bases are more favourite in credit decision making because of their ability to explicitly distinguish between good and bad applicants.In this paper multi-objective particle swarm is applied to optimize fuzzy apriori rule base in credit scoring. ...

I study the time series dynamics of commercial mortgage credit risk and the unobservable systematic risk factors underlying those dynamics. A first-passage model with equilibrium macroeconomic dynamics is presented, and the default hazard rate is solved. The solutions are then put into a state space form and estimated with real world commercial mortgage performance data using extended Kalman fi...

Quality credit has been an academic and commercial hotspot recently. This paper is mainly devoted into using a quantitative method to evaluate credit quality. Firstly, a plain but logical indicator system of quality credit is established. Then, the classical MCDM method TOPSIS is introduced to evaluate the credit quality of 8 air-conditioning enterprises in China market. The discussion of evalu...

U.S. commercial banks are increasingly using credit scoring models to underwrite small business credits. This paper discusses this technology, evaluates the research findings on the effects of this technology on small business credit availability, and links these findings to a number of research and public policy issues. JEL classification: G21, G28, G34, L23

This paper uses the “creditist” theoretical framework that explains credit rationing by financial market imperfections to analyze the developments in Thailand’s credit market during the 19971998 currency and financial crisis. In section II, after reviewing the literature, we propose our definition of a “credit crunch” and its transmission channels. Then, we look for empirical tests in Thailand ...

We examine three models for sample selection that are relevant for modeling credit scoring by commercial banks. A binary choice model is used to examine the decision of whether or not to extend credit. The selectivity aspect enters because such models are based on samples of individuals to whom credit has already been given. A regression model with sample selection is suggested for predicting e...

The paper attempts to determine whether there exists a relationship between the on-time payments of credit card owners of a Commercial Bank and their demographic characteristics (particular personal and family status). It evaluates the statistical technique of discriminant analysis on credit card customers’ data of a Greek Commercial Bank and examine whether it is possible to create a model eva...