Annual Conference


Specialty Conference, Senior Fellows/Fellows


May 2019

Fintech and Credit Scoring for the Millennial Generation

Using a unique and proprietary loan-level data from a large Fintech firm in India, we analyze whether unstructured data regarding a consumer’s digital mobile footprint such as the type of mobile phone applications, number of applications on the phone, type of operating software used by a loan applicant etc., can act as a substitute for traditional credit bureau scores. We find that the digital mobile footprint of an individual outperforms the credit score in predicting loan approvals and defaults. Importantly, including measures of borrower’s “deep digital footprints” based on call logs significantly improves default prediction. Our study has implications for expanding access to credit to those who do not have a credit history but who leave a large trace of unstructured information on their mobile phones that can be used to predict loan outcomes.
Keywords: FinTech, Loans, Digital Footprint, Credit
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