How do banks and fintechs determine your credit worthiness?

By March 2025, Mubarak Umar had spent a twelvemonth and a fractional moving arsenic a supplier cause for Sun King, a star institution successful Ibadan, occidental Nigeria, earning astir ₦200,000 ($126)  monthly, paid straight into his GTBank account. Earlier successful the year, helium conceived the thought to unfastened an electronics store and believed his accordant income and banking past would suffice him for a sizable indebtedness from his bank. But erstwhile helium applied, helium recovered helium could get nary much than ₦120,000, acold beneath the ₦2 cardinal helium wanted.

He turned to PalmPay and Opay for a speedy loan, the fintech apps helium often borrowed from, but was besides offered humble amounts of ₦23,000 and ₦8,000, respectively.

“It amazed maine that [the] slope I person been utilizing for implicit 10 years couldn’t connection maine specified an amount, not adjacent fractional of it,” Umar said. “The mobile apps excessively person ne'er lent maine much than ₦35,000, though I usage them for regular large transactions.  It is similar we are the lone ones that spot them; they don’t spot us.”

Every day, many Nigerians similar Umar question loans from banks oregon pat their smartphones to use for speedy loans from integer lenders. Unbeknownst to the indebtedness seekers, the determination connected however overmuch they tin get isn’t ever wholly made by humans. Lenders are progressively employing tech systems that usage customers’ data to cipher their recognition people and find however overmuch they tin spend to borrow.

The exertion that decides a customer’s borrowing powerfulness depends connected whether they get from a accepted slope oregon a indebtedness app. While the erstwhile trust connected systems that measure structured-income verification and recognition past for indebtedness limits, the second research integer footprint and mobile telephone information with algorithms that scan done a customer’s smartphone analysing app usage and accessing interaction lists.

Traditional banks successful Nigeria chiefly springiness loans to firm clients, wage earners who person astatine slightest 1 twelvemonth of wage history, oregon are employed by companies affiliated with the bank, according to a slope staff. This signifier often excludes micro, small, and mean enterprises (MSMEs), arsenic good arsenic informal assemblage workers, who whitethorn not conscionable these criteria. 

TechCabal’s investigation of the 2023 yearly reports of Nigeria’s starring banks—FirstBank, UBA, GTBank, Access  Bank, and Zenith Bank—shows a beardown penchant for firm lending implicit retail oregon idiosyncratic lending.

In 2023, FirstBank allocated 94% of its ₦6.6 trillion indebtedness portfolio to firm borrowers, giving conscionable 6% to individuals and tiny businesses. UBA followed a akin pattern, giving 70% of its ₦5.5 trillion indebtedness publication to corporates. Access Bank’s 2023 audited financials amusement that it committed 88% of its ₦8 trillion loans to firm clients, with lone 12% going to retail borrowers. GTBank’s indebtedness portfolio was 69.4% firm and 24.1% retail.

Abdulhakeem Abdulmajeed, a merchandise manager astatine The Alternative Bank, said accepted banks stay cautious successful lending to the broader colonisation owed to the inherent risks successful recognition recovery. “Banks are deposit collectors, not concern funds, truthful they indispensable beryllium highly cautious with wherever they enactment these funds to guarantee depositors tin entree their wealth astatine immoderate time,” helium said. 

He added that banks debar high-risk individuals and sectors apt to default connected indebtedness repayment to support their liquidity and support regulatory standards. Unlike fintechs that cushion indebtedness defaults with precocious involvement rates, “banks indispensable support default rates beneath 5%; that makes them much selective with who gets entree to their credit,” Abdulmajeed said. 

For eligible customers, banks usage rule-based recognition scoring systems that measure customers’ turnover, and usage the Central Bank of Nigeria’s (CBN) recognition cheque bundle to scrutinise the customer’s relationship for past recognition with their BVN. “The lawsuit indispensable person an relationship with the bank, and we look astatine their relationship turnover of the amounts coming successful and going retired from their relationship each month. We besides bash a recognition cheque to spot if the lawsuit has a past of default,” said Obayemi Gbenga, a indebtedness table serviceman astatine Keystone Bank.

The mean of a customer’s turnover and recognition past standing find the indebtedness bounds the lawsuit could borrow. The little the recognition people is, the higher the hazard of the lawsuit defaulting connected the repayment, and vice versa.

According to CreditRegistry, a recognition bureau licensed by the CBN, recognition scores scope from 300 to 900, with scores supra 700 considered bully and those beneath 500 regarded arsenic poor.

Gbenga stated that a customer’s monthly turnover is expected to beryllium astatine slightest doubly the magnitude helium intends to borrow, arsenic this indicates their repayment capacity. 

He explained that if the turnover with the slope falls short, the indebtedness table uses a strategy to cheque the customer’s accounts successful different banks and fintech platforms to measure their wide fiscal activity. “Everybody has lone 1 BVN; inputting the customer’s BVN connected the [credit check] bundle volition bring each past recognition past crossed each banks, including integer lending apps,” Gbenga said. “But for a concern oregon company, the strategy uses the Corporate Affairs Commission’s registration number to entree the company’s borrowing history, portion utilizing the BVN for the idiosyncratic recognition past of the proprietor of the concern oregon company.”

Digital lenders trust connected tech-driven information to connection loans

Unlike accepted banks that mostly restrict loans to customers with wage income and ceremonial recognition histories, fintechs similar PalmPay, OPay, FairMoney, and different integer lenders usage behaviour-based algorithms and smartphone information to measure creditworthiness.

The lender uses algorithmic recognition scoring systems powered by instrumentality learning, which cod customer’s data—SMS alerts, contacts, apps usage, instrumentality information, and location—accessed with the customer’s permission, which they consent to portion agreeing to the app presumption during signup. 

Some lenders besides usage apps that necessitate customers’ BVN oregon petition entree to slope statements done APIs to supply much ceremonial fiscal insights. The information determines the recognition limit, sets the involvement rate, and defines repayment schedules.

Despite integer lending offering collateral-free loans, zero paperwork, and support wrong minutes, it often comes with precise precocious involvement rates. These rates are not fixed but are dynamically determined by algorithms that measure a borrower’s hazard level from behavioural and fiscal data. As a result, the aforesaid lawsuit whitethorn get antithetic involvement rates for the aforesaid indebtedness amounts astatine antithetic times, depending not lone connected the magnitude borrowed, but connected however risky the strategy judges their updated data.

“I person an overdue indebtedness with Opay, truthful they can’t lend maine until I wage up,” said Blessing Efiete, a accustomed borrower from integer lenders. “And for PalmPay, I conscionable repaid their ₦15,000 loan; they are bringing maine a ₦1,000 indebtedness bounds connection present due to the fact that the past indebtedness was overdue earlier I repaid, and I haven’t done galore transactions for astir a period now,”  Efiete said. 

The recognition bounds offers are usually tiny for first-time borrowers, with abbreviated repayment periods and options. The in-app algorithms support monitoring customers’ activities implicit the repayment window.  And erstwhile the repayment owed day approaches, an in-app automated strategy issues a notification for reminders.

When repayment is delayed, the strategy triggers betterment actions specified arsenic nudges, automated calls, and reminder substance messages to punctual the customer. In cases of default, involvement continues to accrue implicit time.

Automated betterment actions replaced indebtedness shaming 

In past cases, the terms of default connected a indebtedness repayment is that borrowers are subjected to humiliating tactics, involving lenders engaged successful indebtedness shaming, calling and sending threatening messages not lone to defaulters but besides to their telephone contacts. 

These practices person sparked nationalist outrage and raised superior concerns astir information privateness violations and unethical indebtedness betterment methods, prompting regulatory scrutiny from bodies similar the Federal Competition and Consumer Protection Commission (FCCPC). However, determination are inactive a fewer specified tactics wherever borrowers person threatening calls and curse-like substance messages.

“There is usually a machine dependable telephone reminding maine to repay my loan,” said Efiete. “Around March, erstwhile I inactive owed them (referring to PalmPay), I got messages [where] they were cursing me, saying I should wage them if I don’t privation a downfall for myself.”

However, the integer lenders are shifting distant from the indebtedness shaming practices and adopting automated betterment systems. The determination marks a important measurement toward much liable lending successful Nigeria.

For fintech similar PalmPay, erstwhile a borrower connects his slope to the app, the strategy sets up an auto-deduction from their slope relationship erstwhile the indebtedness is overdue.

“I often get from PalmPay, truthful I linked it to my Access Bank account. When the indebtedness is due, they effort to auto-debit astir each day. If determination is wealth successful the account, it is deducted instantly to repay the loan. If not, the effort fails, but you volition inactive spot it recorded successful your transaction history,” Ibrahim Adekunle said portion scrolling done his transaction past to amusement this reporter.

A telephone for a tech-inclusive lending model

Experts accidental the aboriginal of lending successful Nigeria could beryllium shaped by information and improved exertion that fortify inclusive lending for some banks and integer lenders. 

Abdulmajeed stated that cautions are indispensable erstwhile utilizing customers’ information to connection loans without violating their privacy. He added that a tech exemplary susceptible of including informal players successful agrarian areas, who are retired of the ceremonial and integer banking system, is essential.

“Rural dwellers, astir of whom bash not person a slope account, successful that case, it is highly hard for banks oregon immoderate integer lender to find the eligibility for recognition due to the fact that they bash not person the indispensable data,” helium said. “But if we are capable to find a mode to assistance look astatine these peculiar cases and make a recognition scoring exemplary that volition enactment with radical successful that conception of the market.”

Lending provides economical maturation opportunities 

Abimbola Adewale, an economist, said the discriminatory entree to loans marginalises MSMEs and informal players who deficiency ceremonial documentation and structured-income flows, could hinder the country’s economical growth. This causes “severe financing constraints, limiting their capableness to scale, oregon lend meaningfully to occupation instauration and economical growth.”

He, however, iterates that collaboration betwixt banks and fintechs could assistance standard fiscal lending inclusion. “Banks bring stableness and infrastructure, portion fintechs connection innovation and agility. By moving together, they tin make inclusive, data-driven lending models that service some ceremonial and informal sectors much effectively.”

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