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Credit data start-up lands lucrative Zambia deal

Kenya , 31 Jul 2020

Credit data start-up, CARMA is looking to expand in Africa after securing a deal in Zambia to provide data to credit companies.

The start-up signed an agreement with NASCU Zambia to provide credit reference services for 1,122 credit unions, enabling the company to provide customer credit data. The credit unions serve almost 1.5 million members, equivalent to almost 15% of Zambia’s adult population.

CARMA offers a simple API to companies to access data on a peer-to-peer basis through a pay-as-you-go service.

Ted Martynov, Co-founder and CEO of CARMA, told ITWeb Africa: “In the circumstances when only 11% of adults in Africa have histories with credit bureaus, the uncollected credit data and non-credit data has to be exposed. It is exactly the role of CARMA. Once lenders will have access to a bigger number of data points they can build perfect scorecards for themselves.”

CARMA wants to address the issue of creditworthiness and the increased criteria applied to evaluate users. Criteria has increased as a result of the surge in micro-lending companes, including mobile creditors.

A report by independent global think tank CFI (Center for Financial Inclusion) said that the lack of credit data has led into over-indebtedness by borrowers in Kenya.

An excerpt from the report said: “The scalability of app-based lenders depends on ‘low touch’ or ‘no touch’ models that use experimental lending phases to collect data to refine their credit decision algorithms. Experimental lending is the learning phase of the algorithm when loans are distributed to refine the model based on real repayment behaviour.”

The report added that the app-based lenders miss crucial client data outside IT systems and cannot measure that data against actual income or cash flows.

“The splintered landscape is a basic issue for data in Africa. Everybody assumes a lot of data exists but unavailable. The fundamental thing is to create an inclusive environment for any kind of data that is nearly impossible by aggregating this data into a single centralised silo,” said Martynov.

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