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A US study: Utility and telecom payment data predict loan repayment capacity!

A US study: Utility and telecom payment data predict loan repayment capacity!

I still remember my times at CGAP when the Technology Team was working with PERC, a research center and advocacy group working on:

reducing credit invisibility, ie., “credit invisibles” without credit data are most often rejected by mainstream lenders using automated underwriting systems;

abolishing the “credit catch 22″, i.e., mainstream lenders rely on credit reports to assess credit risk and to extend a loan, plus credit bureaus only have data on the already banked population. In this dynamic to qualify for a loan, you will already have to have credit.

pointing fingers at alternative data which presents a wealth of data that could be used to drive financial inclusion. If it can be accessed, it could dramatically increase access to financial services for low income persons worldwide.

Credit Risk & Scoring