In many parts of the world, lending looks straightforward from the outside. A company raises capital, builds a credit product, and begins issuing loans to borrowers who need funds.
Technology has made that process even more accessible. A small team can launch a lending platform with digital onboarding, automated scoring, and payment integrations within a short period of time.
Yet the reality of running a lending operation quickly reveals a different picture. Credit businesses deal with uncertainty every day. Borrowers behave in ways that models do not always predict.
Payments arrive late for reasons that have little to do with willingness to repay. Fraud attempts appear through channels that look entirely legitimate on the surface. Regulators revise rules that affect underwriting, pricing, or collections.
These pressures exist across every credit market, though lenders in emerging markets face an additional set of complications. Many borrowers lack formal credit histories.
Income often comes from informal or irregular work. Identity systems continue to evolve, which creates verification gaps. Payment infrastructure can behave unpredictably across networks and devices.
Because of these conditions, first-time lenders often discover that the mechanics of issuing loans differ sharply from the mechanics of running a sustainable lending business.
The early months of operation tend to expose underwriting gaps, operational weaknesses, and product design decisions that urgently need revisiting.
Several patterns appear consistently across new lending ventures, not because of negligence or bad intentions, but because teams underestimate how much complexity a credit business carries from its very first loan.
Why the entry barrier to lending appears lower today
Starting a lending business is easier than it has ever been. Lenders can now plug into ready-made tools that handle payments, identity verification, credit bureau checks, and loan management without needing to build any of that from scratch.
The Bank for International Settlements documented how fintech credit grew rapidly across multiple markets as lenders adopted alternative data and automated credit decisions, and a big part of that growth came down to how accessible the underlying technology had become.
The mobile money boom made things even more attractive. Sub-Saharan Africa leads the world in mobile money adoption, with hundreds of millions of registered accounts, and similar foundations exist across South and Southeast Asia and parts of Latin America.
These networks give lenders a ready distribution channel to reach borrowers who have never set foot in a bank branch, which is why digital lending has attracted everyone from early-stage startups to established microfinance institutions looking to move online.
The problem is that easy access to technology can make lending look simpler than it actually is. The tools have changed. The risk has not. Behind every loan product sits a set of underwriting decisions, operational dependencies, and borrower relationships that determine whether the business survives.
First-time lenders often learn that lesson through experience. The five mistakes below show what that experience typically looks like.
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Mistake one: underestimating credit risk
The first mistake many new lenders make is treating credit risk as something to solve at launch and then monitor passively. Most early-stage teams invest heavily in the product experience: the app design, the onboarding flow, the marketing campaign.
Loans go out, early numbers look encouraging, and the business feels like it is working.Then repayment cycles begin and the picture changes.
This pattern has played out in market after market.
In India, digital lenders saw non-performing loan ratios climb sharply during 2023 as platforms that had scaled quickly discovered their underwriting models had not kept pace with the risk they were taking on.
In the Philippines, the Securities and Exchange Commission revoked the licenses of dozens of lending apps after default rates and consumer complaints both rose to levels that regulators could not ignore.
In Nigeria, the FCCPC found that many digital lenders had extended credit to borrowers with no realistic ability to repay, driven partly by the fact that origination fees gave lenders revenue on every loan issued regardless of whether it was ever paid back.
That last point is important. Many digital lending businesses make money from fees charged at the point of origination, which means every new loan generates income whether or not it is repaid.
That structure creates a quiet incentive to prioritize volume over quality, and research by the OECD on fintech lending found that lenders chasing market share often relaxed underwriting standards and expanded originations in ways that directly compromised portfolio health.
The fix is not a more sophisticated algorithm. It is a commitment to treating underwriting as a continuous process rather than a one-time setup. Borrower behavior shifts as economic conditions change. A model that worked well in the first six months may perform poorly in the next six.
Lenders who review repayment data regularly, test their assumptions against actual outcomes, and adjust their credit policies accordingly build portfolios that hold up over time. Those who do not tend to find out why that matters the hard way.
Mistake two: ignoring operational complexity
Many first-time lenders assume that once the credit model is working, everything else will fall into place. It rarely does.
A lending business has a lot of moving parts that all need to work at the same time. Borrowers need to be verified when they sign up. Loans need to be disbursed through payment channels that actually work. Repayments need to be collected reliably.
Support teams need to respond when something goes wrong. Compliance teams need to keep records that regulators can review. Every single one of these depends on outside systems and infrastructure that can, and regularly does, break down without warning.
When a borrower tries to repay through mobile money and gets an error message, they have no way of knowing if the payment went through or not. That moment of uncertainty is enough to make some borrowers lose confidence in the platform entirely.
Identity verification creates similar friction. Databases sometimes contain inconsistencies, a name spelled differently, an outdated record, a mismatched detail, that block perfectly legitimate borrowers from completing their application.
In markets where USSD is still the main channel for financial transactions, session timeouts during repayment attempts are common enough to be a genuine business problem, not just a technical inconvenience.
New lenders tend to spend most of their early planning on underwriting and product design, treating operations as something to sort out once volume picks up. By the time the business is processing thousands of loans a month, that approach has usually produced a long list of problems that are harder and more expensive to fix at scale.
Lenders who monitor payment success rates, onboarding failures, and support volumes from the very beginning catch these issues early, before they become the kind of daily fires that slow everything else down.
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Mistake three: pricing loans without understanding borrower behavior
Pricing a loan looks simple on paper. Add up the cost of capital and running expenses, set a margin, and publish a rate. What that calculation misses is how the borrower actually experiences the cost of the loan when it is time to repay.
Digital loans are typically small, but the cost of processing each one is not. Lenders have to cover payment fees, bureau checks, fraud tools, and customer support for every single loan they issue.
Many new lenders try to recover those costs by stacking multiple fees or building pricing structures that look acceptable on the surface but become confusing, or even shocking, by the time the borrower is actually repaying.
Research published in The Economic Journal using data from Malawi found that most digital borrowers did not understand their loan terms, repaid late, and ended up paying far more than they expected in fees. The basic fee was visible. The late fee structure was buried. Borrowers only found out what the loan actually cost them after the damage was already done.
India saw the same problem play out at a much larger scale. Between 2020 and 2024, India’s Reserve Bank of India received over 50,000 complaints against digital lenders, with hidden charges consistently among the top grievances.
The RBI eventually passed a law requiring lenders to show borrowers the full cost of the loan, including all penalties, before they could accept it. The fact that a law was needed to make that happen says everything about how widespread the problem had become.
Regulators in Kenya, Nigeria, and South Africa have all moved in the same direction. Lenders who build transparent pricing from the start avoid that kind of regulatory pressure and build the trust that keeps borrowers coming back.
Those who treat pricing as purely a margin exercise, without thinking about how the borrower will experience it, tend to end up with complaints, lost customers, and regulators paying close attention.
Mistake four: weak fraud detection systems
Fraud is one of the most underestimated costs of running a lending business, and new platforms are especially vulnerable. Fraudsters actively target lenders that have just launched because they assume the security systems are not fully built out yet. In many cases, they are right.
The scale of the problem globally is significant. Identity fraud in the fintech sector rose 73% between 2021 and 2023.The average fintech company loses $51 million a year to fraud, and identity fraud alone accounted for $20 billion in global losses in 2022.
Perhaps most striking, a coordinated fraud group working with as little as $1,000 can inflict losses of up to $2.5 million on a lender within a single month. These are not problems reserved for large institutions. Smaller lenders tend to get hit harder because they have invested less in protection.
One of the most common tactics in African and Southeast Asian markets is loan stacking, where a borrower, or a network of people using shared or fake credentials, applies to several lenders at the same time before any one of them can spot the pattern.
Because credit bureau data can take days or even weeks to update, each lender makes its decision in isolation, not knowing that three others have already approved the same person. By the time the defaults show up, the money is gone.
Most experienced lenders now use several layers of protection together: identity database checks, device fingerprinting, biometric verification, and real-time transaction monitoring.
Each layer adds some friction to the onboarding process, but the alternative is a portfolio quietly filling up with fraud losses that are very difficult to recover.
Fraud detection is not something to build later when the business is bigger. It is something to build before the fraudsters find you.
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Mistake five: treating borrowers as one-time transactions
Many first-time lenders measure success by how many loans they have issued. Applications processed, capital deployed, loans disbursed. These numbers matter, but they do not tell you whether the business is actually building something sustainable or just burning through borrowers one loan at a time.
A lending business that has to constantly find new borrowers to replace the ones who left is expensive and unstable. Research from IPA found that around 80% of digital borrowers in sub-Saharan Africa who repaid their loans in full went on to take another loan from the same lender, and those repeat borrowers repaid at a rate of around 80%.
The economics are clear. Repeat borrowers cost less to serve, repay more reliably, and become more profitable with every loan cycle. A borrower on their fifth loan with your platform is a fundamentally different risk than someone applying for the first time.
The problem is that many lending platforms are built in ways that quietly push borrowers away. Credit limits that never increase no matter how well someone repays. Pricing that feels unfair by the end of the first loan. Collections experiences that leave a bad enough taste that the borrower decides not to come back.
In Ghana, MTN and JUMO found that borrowers were deliberately taking out small loans and repaying them quickly just to game the credit limit system, before taking out much larger loans they could not actually afford. The product design had created exactly the wrong behavior because the logic rewarded speed of repayment rather than genuine creditworthiness.
Lenders who think about the borrower relationship from day one, building clear credit growth paths, communicating honestly about how the product works, and treating early repayment history as the foundation of a longer relationship, build portfolios that get stronger over time rather than ones that require constant refilling.
Building a lending business that lasts
All five mistakes share the same root cause. They happen when a team puts most of its energy into getting loans out the door without building the systems, habits, and processes that allow the business to actually hold up over time.
Technology has made it easier than ever to launch a lending product. It has not made credit any simpler. The basics, good underwriting, reliable operations, honest pricing, fraud controls, and real borrower relationships, still matter just as much as they always did.
What technology has changed is how quickly a new lender can find out, sometimes at serious cost, what happens when those basics are ignored.
The lenders who do well in the long run tend to treat their first few months as a learning period. They watch their repayment data closely. They fix operational problems before they become habits.
They listen to how borrowers experience their pricing. They invest in fraud prevention before they get hit. And they think about retention from the very first loan, not as an afterthought once growth starts to slow.
Lenders who do all of that build businesses that get stronger over time. Those who treat early growth as a sign that the hard work is behind them usually find out it was only just beginning.
