EarlySalary improves scorecard performance by 5-10 percent
Mumbai, April 3, 2018 – Equifax India, registered as Equifax Credit Information Services Private Limited (ECIS), today announced the launch of Equifax Dimensions, an innovation to provide a robust view of the customer’s credit profile for strong credit decisions and more relevant offers across the entire customer lifecycle.
Equifax Dimensions is a set of 460 bureau variables that have been created by incorporating the last 24 months data of sanctioned amount, credit limit, balance, utilization, past due and delinquency data using a proprietary methodology of aggregating enhanced bureau information. It delivers a comprehensive insight that shows an increase in credit card utilization, decrease in past due amounts and the rate of decrease in installment loan balances, which all have a significant impact on the customer performance. These all can be used to differentiate from the regular credit report data and increase the accuracy of score and model.
EarlySalary, India’s first salary advance mobile app that offers short term instant loans to young salaried individuals is an early adopter of Equifax Dimensions. In addition to bureau variables, the company has been using alternative data from Equifax for its real-time decisioning.
“Bureau reports provide the information with some history but does not give balance and overdue amount data over a time period,” said Vimal Saboo, Chief Business Officer, EarlySalary. “We explored a lot using dimensions variables, as they give trend over time period, while building application scorecard. The latest version of scorecards has approx. 10-15 percent weightages to Dimension variables. These variables have improved scorecard performance by around 5-10 percent.”
“To develop and implement a strategy that helps you identify and compete for the best customers, you need deeper information that reveals what’s happening with consumers over time,” said K M Nanaiah, Country Head, Equifax India. “Equifax Dimensions come up with the variables that will help financial institutions to have refined credit strategies for stronger and more confident credit decisions. It will also help them to achieve a significant lift in model accuracy over snapshot variables and internal transaction data for application risk, portfolio risk, balance transfer, propensity to take a new product in the next three months and probability of delinquent customers to be current in the next six months.”
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