Paper Info
Title
A Tripartite Scorecard for the Pay/No pay Decision-Making in the Retail Banking Industry
Abstract
Traditionally retail banks have supported the credit decision-making on scorecards developed for predicting default in a six-month period or more. However, the underlying pay/no pay cycles justify a decision in a 30-day period. In this work several classification models are built on this assumption. We start by assessing binary scorecards, assigning credit applicants to good or bad risk classes according to their record of defaulting. The detection of a critical region between good and bad risk classes, together with the opportunity of manually classifying some of the credit applicants, led us to develop a tripartite scorecard, with a third output class, the review class, in-between the good and bad classes. With this model 87% decisions are automated, which compares favourably with the 79% automation rate of the actual scorecards.
Year
Venue
Keywords
2007
DMBiz@PAKDD
retail banking industry,credit applicant,tripartite scorecard,30-day period,pay cycle,six-month period,review class,bad class,bad risk class,output class,credit decision-making,assigning credit applicant
Field
DocType
Citations 
Retail banking,Actuarial science,Automation,Default,Balanced scorecard,Mass market,Business
Conference
2
PageRank 
References 
Authors
0.37
3
2
Name
Order
Citations
PageRank
Maria Rocha Sousa120.37
Joaquim Pinto Da Costa226214.82