Financial Inclusion and Alternate Credit Scoring for the Millennials: Role of Big Data and Machine Learning in Fintech

62 Pages Posted: 14 Jan 2020 Last revised: 27 Feb 2020

See all articles by Sumit Agarwal

Sumit Agarwal

National University of Singapore

Shashwat Alok

Indian School of Business (ISB), Hyderabad

Pulak Ghosh

Indian Institute of Management (IIMB), Bangalore

Sudip Gupta

Fordham University - Finance Area

Date Written: December 21, 2019

Abstract

Using a unique and proprietary loan-level data from a large Fintech lending firm in India, we analyze whether unstructured data pertaining to a consumer’s social and mobile footprint can act as a substitute for traditional credit bureau scores. We find that the mobile footprint of an individual outperforms the credit score in predicting loan approvals and defaults. Importantly, including measures of borrower’s “deep social footprints” based on call logs significantly improves default prediction. We use machine learning-based prediction counterfactual analysis to predict the loan outcome for borrowers who were denied credit, perhaps due to the lack of traditional credit scores. We show that using alternate credit scoring using the mobile and social footprints can expand credit as well as reduce the overall default rate. 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, Big data, Credit scores, Financial inclusion, Lending, Machine Learning, Mobile footprint, Prediction Counterfactual, Social footprint, Social capital

Suggested Citation

Agarwal, Sumit and Alok, Shashwat and Ghosh, Pulak and Gupta, Sudip, Financial Inclusion and Alternate Credit Scoring for the Millennials: Role of Big Data and Machine Learning in Fintech (December 21, 2019). Available at SSRN: https://ssrn.com/abstract=3507827 or http://dx.doi.org/10.2139/ssrn.3507827

Sumit Agarwal

National University of Singapore ( email )

15 Kent Ridge Drive
Singapore, 117592
Singapore
8118 9025 (Phone)

HOME PAGE: http://www.ushakrisna.com

Shashwat Alok

Indian School of Business (ISB), Hyderabad ( email )

Hyderabad, Gachibowli 500 019
India
914023187188 (Phone)

Pulak Ghosh

Indian Institute of Management (IIMB), Bangalore ( email )

Bannerghatta Road
Bangalore, Karnataka 560076
India

Sudip Gupta (Contact Author)

Fordham University - Finance Area ( email )

33 West 60th Street
New York, NY 10023
United States

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