Using a transactor/revolver scorecard to make credit and pricing decisions

Abstract

In consumer lending the traditional approach is to develop a credit scorecard which ranks borrowers according to their risk of defaulting. Bads have a high risk of default and Goods a low risk. To maximise the profitability of credit card customers, a second classification between Revolvers and Transactors becomes important. Building a Transactor/Revolver scorecard together with a Good/Bad scorecard over the Revolvers, gives rise to a risk decision system whose ranking of risk is comparable with the standard approach. The paper develops a profitability model of card users including the Transactor/Revolver score leads. This gives more accurate profitability estimates than models which ignore the transactor/revolver split.

The use of profit scoring as an alternative to credit scoring systems in peer-to-peer (P2P) lending

“…Other studies develop profit scoring for credit cards and consumer credit [12,13,14,15,16,3]; however, the lack of data resulted in the use of customer profit proxies. To the best of our knowledge, there are no previous studies using the IRR as a dependent variable.…”

“…Stewart [13] proposes another profit-based scoring system for credit cards and reports that borrowers most likely to charge-off are also more likely to spend on their cards, pay finance charges and pay fees. So et al [16] develop a profitability scoring model for credit card users including revolver assessments. The approach is similar to the standard method in predicting default but it is more accurate in estimating the profitability of potential applicants.…”

“…The use of the expected maximum profit measure for model selection leads to more profitable credit scoring models So et al (2014) [16] A profitability model for potential credit card applicants including the transactor/revolver score leads. Credit card data originate from a Hong Kong financial institution…”

Wide and deep learning for peer-to-peer lending

“…The interested readers are suggested to refer to (Lessmann et al, 2015) for a detailed review of credit scoring approaches used in other areas of consumer credit such as credit card and mortgages (So et al, 2014).…”

A Bayesian approach for incorporating expert opinions into decision support systems: A case study of online consumer-satisfaction detection

“…In recent years this process has accelerated as a result of the exponential growth of electronically stored information, which is available to companies, organizations, and individuals. The literature on decision support systems highlights several application domains that have been significantly affected by this trend, including credit risk [2,3], bankruptcy prediction [4], customer relationship management [5,6], and fraud detection [7].…”