Competition intensifies to enhance lending data in Nigeria
In November 2020, a new player entered the Nigerian digital lending scene, with Kenyan data marketplace CARMA announcing plans to set up operations in the country. CARMA, a credit data marketplace, aims to provide digital lenders with more data points to make informed loan decisions, addressing the need for a more robust data gathering process.
CARMA's peer-to-peer system allows digital lenders to put their customer data on a virtual shelf, and other lenders can pay for the specific data points they need. This approach can be particularly beneficial for lenders dealing with customers who have limited credit history, known as thin files.
The incentive CARMA provides is revenue for digital lending players who share data. This sharing of data points helps lenders determine a customer's willingness to pay, a crucial factor in the digital lending industry where successful lenders rely on the strength of their decision-making.
However, many companies are reluctant to share data with external organizations, as pointed out by Ted Martynov, CARMA's CEO. Martynov believes that existing credit bureaus in Nigeria are not up to the task. Despite the data submitted to these bureaus, formal sector credit penetration as a ratio of the adult population in Nigeria was below 5.3% in 2017, indicating a significant gap in credit access.
Nigeria's digital lenders offer simpler processes with no paperwork and instant loan decisions, making them a popular choice among consumers. However, the risk of default remains high due to the lack of traditional credit history. To mitigate this risk, lenders collect an array of data points, including call records, GPS information, and messages.
The use of improved digital identification systems, such as linking loans to the National Identification Number (NIN), makes defaults more traceable and credit profiles more reliable. Lenders also leverage alternative data from telecoms, airtime usage, and other non-traditional sources shared with credit bureaus to assess creditworthiness.
These enhanced data-sharing practices and tighter entry criteria enable startups to identify quality borrowers less likely to default, thereby reducing credit risk. This is particularly impactful in Nigeria's large population with a significant unbanked or underbanked segment. The adoption of these data strategies occurs in the context of heightened regulation introduced by Nigeria’s Federal Competition and Consumer Protection Commission (FCCPC), which mandates transparent, responsible lending practices and imposes heavy penalties for unethical lending.
Another startup, Migo, is building infrastructure to help lenders make loan decisions without depending on credit bureaus. Migo's partner banks and fintechs don't have to consult credit bureaus for data before lending to consumers, as they trust Migo to do the backend work and help originate the right loans. Migo does data science work and builds flexible algorithms to help banks determine what low-income customers to lend to, further promoting financial inclusion by granting responsible access to credit for individuals who otherwise might be excluded due to lack of traditional credit history.
In conclusion, new startups in Nigeria's digital lending space are enhancing loan decision-making with more diverse and accurate data signals while supporting wider financial inclusion through innovative credit assessment methods. This approach helps lenders make more accurate loan decisions, reduce default rates, and increase financial inclusion by extending credit to underserved segments without conventional credit records.
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