Accelerating mobile credit: Could a universal credit score be the answer?
Mobile credit and savings services have been gaining traction using different models all of which require a credit or savings provider to partner with a financial institution — be it a bank, mobile money provider or MFI. However, in the past year, a new approach has emerged, which minimises the need for mobile credit providers to partner with financial institutions and/or mobile money providers. Driven by the ubiquity of smartphones, this new approach uses data from users’ smartphones to credit score potential customers and offer them loans. Tala and Branch are two start-ups who use this approach to credit score their customers via an app. Both companies then rely on these self-created scores and lend off their own balance sheet. Although the businesses are too nascent to evaluate success — both have significant backing from VCs.
- Tala (formerly InVenture) secured USD 11.2 million in funding, with a USD 10 million series A round in September 2015
- Branch secured USD 9.2 million in funding in their series A round in March 2016
There are more than a dozen prominent start-ups looking to innovate on credit assessment. Success in these areas can deliver huge impact by bringing formal, accessible and affordable credit to mass-market consumers.
However, whilst each lender continues to do its own credit scoring, it will remain a fragmented and inefficient way to achieve mass-scale. In developed markets, credit scores are available to all lenders (e.g.: FICO score in the United States). Whereas in developing markets, each lender has to create their own credit score, making it very difficult for the industry to scale rapidly as the majority of existing lenders do not have access to the data or the tools required to create credit scores.
A universal credit score using alternate data for developing markets
The ability for every individual with a mobile number (MSISDN) to provide a financial institution of their choice with access to their credit score, if they wish, would be a novel and empowering one. This credit score could be calculated on alternate data (such as call data records, mobile money transactions and loan repayments) using an open-source algorithm across a number of developing markets — creating common infrastructure for a public good.
So far the partnership model (financial institutions and mobile money providers) has resulted in only eight of the top 30 mobile money providers (each having over one million active users (90 day) offering a mobile credit service. Perhaps it’s time to move to a less fragmented approach that will allow the thousands of existing lenders to leverage a universal credit score to deliver affordable credit to hundreds of millions of aspiring low-income and lower middle-class consumers in developing markets.
 Disbursing loans and collecting re-payments using mobile money rails does not require a partnership
 Android smartphones provide access to call data records, messages (mobile money transaction history), location history, browser history etc.
 MNOs could all use a common methodology to calculate the credit score, however customer data itself is not shared with a third party as MNOs must continue to ensure customer data privacy.
 An open source algorithm to provide lenders the opportunity to understand the mechanics and contribute to improve the algorithm
Originally published at www.gsma.com on November 24, 2016.
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