Across emerging markets, the scarcity of traditional data to predict credit-worthiness has prevented financial institutions from lending to the 2.5 billion under-banked across the globe. Lenders everywhere rely on borrowing histories, credit scores, and formal financial records to measure applicant credit-worthiness.
When this information is lacking or unreliable, the transaction costs of determining the applicants credit-worthiness are far too high and operationally burdensome. As a result, lenders have been unable to tap the significant under-banked opportunity. At the same time, even when this past data is available and accurate; trying to predict the future based on the past may not always lead to correct results. This is one of the reasons of default in cases where there is a good credit score.
This is where “Psychometric tests” have enabled lenders to expand product offerings to applicant segments for which they were previously unable to accurately assess risk. With the digital penetration, this has become even easier.