EFL proved the ability to reduce default rate by 45%*
BTPN, Indonesia’s 4th largest MSME lender, sought to reduce risk and standardize credit operations across an extensive national branch network. However, a lack of credit data among BTPN’s target clients forced the bank to rely heavily on subjective methods of risk assessment and limited its ability to make objective, quantitative credit decisions.
BTPN engaged EFL in September of 2012 to help drive better credit analytics. EFL developed a new credit scorecard by integrating information from BTPN’s existing borrower database with EFL’s proprietary psychometric scoring tool, creating a new, layered scorecard.
EFL’s Psychometrics+ Scorecard demonstrated predictive capabilities beyond those of psychometrics or borrower data alone, enabling BTPN to segment borrowers with a 10x difference in default. Encouraged by the results, BTPN has chosen to roll out the Psychometrics+ Scorecard across its 600 branch network.Download Full Case Study
* Default reduction refers to the impact of removing the bottom two quintiles of EFL scorers from the borrowing population