Pngme’s Alternative Data API Can Help Lenders Increase Approvals by 48%
Lending Today
Issuing loans to consumers and businesses in emerging markets has been difficult for lending institutions when compared to developed markets. Borrowers’ lack of credit history has prevented their ability to access loans because lending institutions determine the creditworthiness of potential customers based on past repayment data. In emerging markets, where fewer than 10% of the population is on file in public credit registries, the traditional credit scoring methods fail to adequately identify creditworthy customers. An Ernst and Young study highlighted that 90% of new-to-bank applicants were rejected using existing loan application decision-making policies.
Lending Using Alternative Data
Because these customers rely on cash and don’t have any traceable financial history, they are considered expensive to serve in the conventional banking channels and are often thought to have low potential to create value. However, by leveraging alternative data, the study pointed out that lending institutions can increase loan approval rates by 48% and reduce risk by 39%. This will not only provide an opportunity to increase the number of creditworthy loans issued, but will also incorporate more people into the financial system. Furthermore, the use of alternative data is likely to positively impact the economy and could boost annual GDP of all emerging economies by $3.7 trillion by 2025.
Lending Using The Pngme Alternative Data API
To harness this potential, Pngme has developed a powerful API for lending institutions which uses alternative data to include more consumers and businesses in the financial system and provide greater access to credit. Pngme’s alternative data API goes beyond traditional scoring services (such as FICO) by looking at non-centralized, consumer-focused financial and behavioral data to create predictive credit models. Using machine learning algorithms, our models incorporate the mobile device’s transactional records as well as factoring in alternative data such as geo-location, text syntax, contacts, and social media behavior to create a complete and accurate credit profile. Borrowers are able to establish a credit score that has proven to be very reliable and can more accurately forecast a borrower’s risk of default. Based on these credit profiles, lending institutions can effectively qualify customers and make informed decisions at scale.
Our Customers
We are currently working with leading Banks, Microfinance Banks, Mobile Money Operators (MMOs), and fintechs in Africa to increase the value of their financial network while lowering risk. If you would like to further understand how Pngme can help increase your loan approval rate while reducing risk through an alternative data API, please request a consultation with our team using this link.
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