FairMoney Onboards Better Neobank Customers Thanks to Digital & Social Footprint Checks
Consumer lending is booming in Nigeria, a country with a burgeoning digital economy and a significant unbanked population. Among the companies thriving in this environment is FairMoney, an app-based online lending bank with a reach of 1.3 million users across Nigeria and 10,000+ loans a day. The company’s vision extends beyond Nigeria, with an ongoing expansion into India, where it has processed over half a million loan applications. FairMoneys offerings include savings, banking and lending from microfinance to business loans, positioning itself as a comprehensive digital financial services provider.
The Challenge
Despite its rapid growth, FairMoney faced significant challenges in serving underbanked populations. Juris Rieksts-Riekstins, Head of Risk at FairMoney, highlights the difficulty of obtaining reliable data in Nigeria’s financial landscape.
Getting reliable data is the biggest challenge in our market. Financial inclusion is growing n Nigeria, but we still have to build risk models without banking data. We also need to be very precise with our blacklisting due to the high rate of fraudulent actors.
The solution
To tackle these challenges, FairMoney turned to SEON, a fraud prevention solution that utilizes alternative data. This approach aligns with FairMoney’s need to gather reliable data discreetly and efficiently without compromising the speed of its decision-making process.
FairMoney focused on two key SEON modules as part of a multi-layered bad debtor detection and fraud prevention strategy:
Digital footprinting: To provide insights into a user’s potential legitimacy.
Device Intelligence: To identify and track device data points, offering an additional layer of insights into the customer.
By combining these modules, FairMoney can quickly filter out obvious fraudsters who lack a digital or social presence and automate more informed decision-making processes.
‘We overlay SEON’s digital and social lookup with device fingerprinting to get a good indication of whether the phone or tablet belongs to the actual client. We can instantly filter out obvious fraudsters/bad debtors with no digital or social presence, and we get better intelligence to automate our decision making.’
Allow rapid decision making for a frictionless onboarding experience. Leaving your team more time to help your business grow.
Results
The integration of SEON’s technology has significantly enhanced FairMoney’s operational efficiency and fraud detection capabilities. Key metrics illustrating these improvements include:
Within a month of deploying SEON, FairMoney streamlined its onboarding process, enabling the company to deliver microloans of up to $2000 in less than five minutes. This efficiency has resulted in a seamless user experience, where a loan is approved on average every 8 seconds.
The deployment of SEON has provided several critical benefits:
Reduced Fraudulent Activities: By leveraging SEON’s advanced data analytics and blacklisting capabilities, FairMoney has been able to significantly reduce fraudulent loan applications.
Improved User Experience: The frictionless onboarding process ensures legitimate users can access loans quickly, enhancing customer satisfaction and retention.
Operational Efficiency: Automating the decision-making process has allowed FairMoney to handle a high volume of loan applications daily without compromising accuracy or security.
Juris Rieksts-Riekstins commends SEON’s adaptability and support, noting, “SEON’s blacklisting system is very flexible and well-suited for our needs in Nigeria. We’re also happy to get one of the best customer support. The team is always interested to learn how they can make our lives easier.
FairMoney’s partnership with SEON exemplifies how leveraging innovative fraud prevention solutions can address the unique challenges of emerging markets. By integrating digital and social data analysis with device fingerprinting, FairMoney has successfully enhanced its risk management framework, enabling secure and efficient financial services delivery. This case study underscores the importance of adopting adaptive technologies to maintain growth and integrity in the rapidly evolving digital lending landscape.
Head of Risk
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