Consumer Credit Scoring Research Articles

Consumer credit scoring: Do situational circumstances matter?

Although credit history scoring offers benefits to lenders and borrowers, failure to consider situational circumstances raises important statistical issues that may affect the ability of scoring systems to accurately quantify an individual's credit risk. Evidence from a national sample of credit reporting agency records suggests that failure to consider measures of local economic circumstances and individual trigger events when developing credit history scores can diminish the potential effectiveness of such models. There are practical difficulties, however, associated with developing scoring models that incorporate situational data, arising largely because of inherent limitations of the credit reporting agency databases used to build scoring models.

Consumer credit scoring: Do situational circumstances matter?

Although credit history scoring offers benefits to lenders and borrowers, failure to consider situational circumstances raises important statistical issues that may affect the ability of scoring systems to accurately quantify an individual’s credit risk. Evidence from a national sample of credit reporting agency records suggests that failure to consider measures of local economic circumstances and individual trigger events when developing credit history scores can diminish the potential effectiveness of such models. There are practical difficulties, however, associated with developing scoring models that incorporate situational data, arising largely because of inherent limitations of the credit reporting agency databases used to build scoring models.

A study in the combination of two consumer credit scores

Credit scores measure the creditworthiness of individuals in a population of interest. In this paper, we employ the concepts of sufficiency and extraneousness to study the conditions under which scoring results can be improved through the combination of individual scores. The concept of sufficiency is used to identify scores that are dominant. Extraneousness is used to determine whether a particular score provides additional useful information relative to other scores. In addition, we employ a profit-based utility measure to evaluate the performance of different scores. We investigate the performance of a regression-based combination of a bureau credit score and an application credit score on a large historical data set. Our results show that the bureau score is dominated by the application score, but the bureau score is not extraneous to the combination. Thus, both scores contribute to the combined score, which indeed outperforms both of the scores upon which it is based.

Statistical Classification Methods in Consumer Credit Scoring: A Review

Summary Credit scoring is the term used to describe formal statistical methods used for classifying applicants for credit into ‘good’ and ‘bad’ risk classes. Such methods have become increasingly important with the dramatic growth in consumer credit in recent years. A wide range of statistical methods has been applied, though the literature available to the public is limited for reasons of commercial confidentiality. Particular problems arising in the credit scoring context are examined and the statistical methods which have been applied are reviewed.