Abstract 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 expenditures, or the amount of credit. The same considerations as in the binary choice case apply here. Finally, a model for counts of occurrences is described which could, in some settings also be treated as a model of sample selection. # 1998 Elsevier Science B.V
Credit scoring is one of important tools that help financial institutions decide whether or not to g...
This paper investigates the effect of including the customer loan approval process to the estimation...
The aim of this paper is to present how credit scoring models can be used in financial institutions,...
One of the aims of credit scoring models is to predict the probability of repayment of any applicant...
We derive a model for consumer loan default and credit card expenditure. The default model is based ...
Statistical methods have been widely employed to assess the capabilities of credit scoring classific...
Nowadays, the use of credit scoring models in the financial sector is a common practice. Credit scor...
Statistical methods have been widely employed to assess the capabilities of credit scoring classific...
This article belongs to the Special Issue Mathematics and Mathematical Physics Applied to Financial ...
© Cambridge University Press 2008.Acknowledgements: I am grateful to Terry Seaks for valuable commen...
Prediction models in credit scoring are often formulated using available data on accepted applicants...
This article seeks to gain insight into the influence of sample bias in a consumer credit scoring mo...
Graphical models simplify the analysis of multivariate observations by summarizing conditional indep...
The use of credit scoring - the quantitative and statistical techniques to assess the credit risks i...
Purpose: The study herein develops and tests a credit scoring model which can help financial instit...
Credit scoring is one of important tools that help financial institutions decide whether or not to g...
This paper investigates the effect of including the customer loan approval process to the estimation...
The aim of this paper is to present how credit scoring models can be used in financial institutions,...
One of the aims of credit scoring models is to predict the probability of repayment of any applicant...
We derive a model for consumer loan default and credit card expenditure. The default model is based ...
Statistical methods have been widely employed to assess the capabilities of credit scoring classific...
Nowadays, the use of credit scoring models in the financial sector is a common practice. Credit scor...
Statistical methods have been widely employed to assess the capabilities of credit scoring classific...
This article belongs to the Special Issue Mathematics and Mathematical Physics Applied to Financial ...
© Cambridge University Press 2008.Acknowledgements: I am grateful to Terry Seaks for valuable commen...
Prediction models in credit scoring are often formulated using available data on accepted applicants...
This article seeks to gain insight into the influence of sample bias in a consumer credit scoring mo...
Graphical models simplify the analysis of multivariate observations by summarizing conditional indep...
The use of credit scoring - the quantitative and statistical techniques to assess the credit risks i...
Purpose: The study herein develops and tests a credit scoring model which can help financial instit...
Credit scoring is one of important tools that help financial institutions decide whether or not to g...
This paper investigates the effect of including the customer loan approval process to the estimation...
The aim of this paper is to present how credit scoring models can be used in financial institutions,...