Behavior Revealed in Mobile Phone Usage Predicts Credit Repayment
Many households in developing countries lack formal financial histories, making it difficult for firms to extend credit, and for potential borrowers to receive it. However, many of these households have mobile phones, which generate rich data about...
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| Language: | English |
| Published: |
World Bank, Washington, DC
2019
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/811881575657172759/Behavior-Revealed-in-Mobile-Phone-Usage-Predicts-Credit-Repayment http://hdl.handle.net/10986/33018 |
| Summary: | Many households in developing countries
lack formal financial histories, making it difficult for
firms to extend credit, and for potential borrowers to
receive it. However, many of these households have mobile
phones, which generate rich data about behavior. This
article shows that behavioral signatures in mobile phone
data predict default, using call records matched to
repayment outcomes for credit extended by a South American
telecom. On a sample of individuals with (thin) financial
histories, our method actually outperforms models using
credit bureau information, both within time and when tested
on a different time period. But our method also attains
similar performance on those without financial histories,
who cannot be scored using traditional methods. Individuals
in the highest quintile of risk by our measure are 2.8 times
more likely to default than those in the lowest quintile.
The method forms the basis for new forms of credit that
reach the unbanked. |
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