Does Credit Scoring Improve the Selection of Borrowers and Credit Quality?

Does segmentation always improve model performance in credit scoring?

Credit scoring allows for the credit risk assessment of bank customers. A single scoring model (scorecard) can be developed for the entire customer population, e.g. using logistic regression. However, it is often expected that segmentation, i.e. dividing the population into several groups and building separate scorecards for them, will improve the model performance. The most common statistical ...

Credit scoring and the sample selection bias

For creating or adjusting credit scoring rules, usually only the accepted applicant’s data and default information are available. The missing information for the rejected applicants and the sorting mechanism of the preceding scoring can lead to a sample selection bias. In other words, mostly inferior classification results are achieved if these new rules are applied to the whole population of a...

the study of practical and theoretical foundation of credit risk and its coverage

پس از بررسی هر کدام از فاکتورهای نوع صنعت, نوع ضمانت نامه, نرخ بهره , نرخ تورم, ریسک اعتباری کشورها, کارمزد, ریکاوری, gdp, پوشش و وثیقه بر ریسک اعتباری صندوق ضمانت صادرات ایران مشخص گردید که همه فاکتورها به استثنای ریسک اعتباری کشورها و کارمزد بقیه فاکتورها رابطه معناداری با ریسک اعتباری دارند در ضمن نرخ بهره , نرخ تورم, ریکاوری, و نوع صنعت و ریسک کشورها اثر عکس روی ریسک اعتباری داردو پوشش, وثی...

Small Business Credit Scoring and Credit Availability

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

Sample selection bias in credit scoring models