A practical playbook for credit underwriting using statement of account

As a lender, your biggest blind spot isn’t the loans you approve. It’s the loans you shouldn’t have touched in the first place. If you’re a lender in developing markets such as Southeast Asia, Africa, and LATAM, you already know: we don’t have the luxury of pulling a FICO score and feeling safe. We have to do it the hard way. We have to look at behavior, read between the lines, and trust our instincts more than the loan application itself.

In more developed countries, credit scores are sacred. Your credit history isn’t just a number. It’s you. Mess with it, and you’ll find yourself locked out of housing, jobs, and even a simple personal loan. In places like Canada, the US or UK, people are so obsessed with credit that even a peek at your history could raise a red flag if too many people are looking at it. Trust me, that’s how seriously they take it.

But once you find yourself in Africa or Southeast Asia, you have to look deeper. And the best place to start is the statement of account. It’s not about what a borrower promises. It’s about what their money movements show. The truth is, a bank statement can reveal more about a borrower’s financial habits than any credit report. 

This is something I’ve learned firsthand over the years.

Unfortunately, most lenders still follow the traditional approach. They pull a few months of statements, divide total inflow by the number of months, and get an “average income.” Then they base an entire credit decision on that. But that approach is wildly outdated and dangerously simplistic. It’s even worse than crossing a busy street blindfolded.

Also, just looking at average income doesn’t help you understand capacity or character, which are the two most important qualities in a borrower. You need a deeper, behavior-based review of their financial life. To effectively evaluate capacity and character, it’s necessary to look beyond the surface.

Now, let’s look at how to “properly” review statement of account

To conduct a proper and professional review of a bank statement, lenders must move beyond surface-level impressions and adopt a forensic, data-informed mindset. This process is not about skimming a few line items or glancing at average income. It’s about interrogating the document for financial patterns, behavioral cues, and structural stability. These are the very attributes that determine whether a borrower can and will repay a loan.

Start with the right time frame

When assessing a borrower’s financials, the length of the bank statement you review can make or break your decision. Many lenders, particularly digital ones eager to move fast, often settle for three months of transaction data. But that short-term snapshot can be dangerously misleading. A borrower might appear creditworthy with three months of clean inflows and stable balances, but those months could coincide with seasonal business booms, temporary freelance gigs, end-of-year bonuses, or even borrowed funds meant to create the illusion of financial stability. Three months is just long enough to stage a façade and nowhere near long enough to expose the truth.

Twelve months of statements, at the very least, provide the kind of clarity that truly reduces risk. With that amount of data, patterns begin to emerge. You can see how a borrower handles seasonal cycles. Maybe their income drops during certain months, or spending spikes during holiday periods. You’ll also catch one-off life events like medical emergencies, weddings, school fees, or other large expenses that might not recur, but impact cash flow significantly. These are all things that three-month windows simply fail to reveal.

Over a full year, you also begin to notice debt patterns. Many borrowers juggle multiple loans and may be caught in a cycle of taking one loan to repay another. Short statements can miss this, but a year’s worth of data will show the recurring inflows from different lenders followed by immediate repayments, signaling potential over-indebtedness. You’ll also get a more honest view of income consistency. Maybe the borrower missed two salary payments earlier in the year. Maybe they had great sales one quarter and none the next. Only long-term data tells that story.

More importantly, you get to observe how the borrower reacts to pressure. When funds are low, do they adjust their spending, or do they continue buying airtime and eating out? Do they prioritize rent and school fees, or default on essentials to keep up appearances? These behavioral patterns, especially in lean times, are often better predictors of creditworthiness than income itself.

In short, anyone can appear financially stable for a few months, especially if they know they’ll be applying for a loan. But consistency over a full year reveals discipline, resilience, and true financial habits. Twelve months of data isn’t overkill. It’s the minimum lens you need to separate genuinely stable borrowers from those riding temporary waves.

Evaluate the nature and regularity of income

Income alone does not make a borrower creditworthy. It is easy to be impressed by large one-off deposits or inflated figures on a statement, but without consistency and traceability, those numbers mean very little. What truly matters is the pattern, the source, and the dependability of that income. Regular, salaried payments from a recognized employer landing on or around the same day each month, offer a clear signal of financial reliability. These deposits show not only that the borrower has a job, but also that they are part of a structured financial ecosystem. Such regularity provides predictability, which reduces the risk for any lender.

On the flip side, irregular income from gigs, freelance work, or small businesses is more complicated. These sources might still represent legitimate and sustainable earnings, but they require much deeper analysis. A borrower may receive income from ride-hailing apps, food delivery, hairdressing, or mobile money agency services. These are all valid occupations, but they don’t always guarantee stable inflows. What matters here is not just how much the borrower earns, but how often and how predictably they earn it. If payments are inconsistent or come in lump sums spaced out by weeks or months, the borrower’s financial stability may be more fragile than it first appears.

It is also important to understand whether the income is tied to volatile factors. Some businesses thrive only during holidays or specific seasons. Others are entirely dependent on contracts that can expire or be terminated without notice. Even performance-based salaries, commissions, or bonuses, while lucrative, are risky because they fluctuate depending on variables beyond the borrower’s control. A borrower might have a high earning potential, but without a steady track record, lenders are left guessing.

Another layer of risk lies in untraceable or unverifiable deposits. Money received through peer-to-peer transfers or cash-based businesses often lacks documentation or a clear trail. If a lender cannot identify the source, there is no way to evaluate the sustainability or legality of that income. In some cases, large unexplained inflows could even signal fraud, money laundering, or other high-risk behavior. Verifiability, in this context, becomes just as important as regularity.

Perhaps the most common mistake lenders make is relying on average monthly income. This metric can be dangerously misleading. A borrower who receives $15,000 once every four months may technically average $3,750 per month, but in practice, they are going through long dry spells between payments. Compare that to someone who earns $3,000 like clockwork every month, their financial life is easier to manage and far more predictable. Regularity beats volume every time when it comes to responsible borrowing.

Assess regular living expenses

Where money goes is often more telling than where it comes from. A borrower’s spending habits reveal a lot about their priorities, financial discipline, and risk tolerance. While income provides a sense of capacity, expenses offer insight into character. For lenders, this is a big piece of the puzzle. It is not just about how much a borrower earns, but how well they manage what they have. Patterns of spending can uncover the habits that shape financial behavior and ultimately determine creditworthiness.

A borrower might have monthly inflows of $5000, but if $4800 disappears into living expenses before the 15th of the month, they can’t repay a loan, no matter how “high-earning” they appear on paper.

The trick here is not to be fooled by silent accounts. Many borrowers use their main bank account only to receive salary and repay loans. But when you look closer, you’ll find little to no data about everyday spending; no food, no fuel, no rent, no subscriptions.

That’s a trap.

These expenses haven’t vanished. They’re just being carried out on another platform, maybe a mobile wallet, another bank, or even cash. You must ask the borrower: “Where do you usually spend from?” And then ask to see that account too.

Why does this matter?

Because living expenses are your first clue about financial strain. If someone is spending $100 monthly on data, $400 on leisure activities, and still claims they have enough room to take a $600 loan, you need to push back and recalculate.

Also look at the ratio of discretionary vs. essential spending. Is the borrower buying concert tickets and cocktails but defaulting on savings? That’s poor money discipline. Also, if someone prioritizes school fees, food, and modest rent, that’s a mark of financial maturity even if the income is modest.

One of the strongest signals of financial health is the ability to live within one’s means. A bank statement that shows controlled, deliberate spending, even on a modest income, is often more reassuring than one filled with flashy deposits followed by wasteful expenses. For lenders, this kind of balance is gold. It reflects not just a borrower’s current position but their long-term approach to financial responsibility.

Understand their existing obligations

Many borrowers carry more debt than they openly disclose, and not all of it shows up as formal loans in credit reports. Sometimes, the signs are buried in everyday transactions. Frequent transfers to the same contact, regular repayments to loan apps, or recurring deductions labeled under vague categories like utilities or savings contributions. These payments may not look like debt at first glance, but they often represent existing financial obligations that can significantly affect the borrower’s ability to take on and repay new loans.

This is why it’s not enough to check for official loans. A lender must look closely at bank statements for patterns that indicate informal borrowing or silent commitments. For example, consistent monthly transfers to digital loan apps, family members, or thrift groups may point to recurring repayment responsibilities. Even contributions to a rotating savings and credit association (ROSCA) or cooperative society can behave like debt, especially when the borrower is expected to contribute regardless of personal cash flow.

At this point, calculating a borrower’s debt-to-income (DTI) ratio becomes essential. This metric helps quantify how much of a borrower’s monthly income is already tied up in repaying debts or obligations. If more than 30 to 40 percent of income is being used to settle existing liabilities, it is a clear sign that the borrower is financially stretched. Introducing another loan into the mix may only worsen the situation. A high DTI ratio means that the borrower has little room to maneuver in case of unexpected expenses, which increases the risk of delinquency or default.

Even more concerning is when repayment patterns show signs of financial juggling: borrowing from one source to pay off another. For instance, if a borrower receives a digital loan and shortly after transfers the funds to clear a different loan, that is an indication of debt cycling. This behavior suggests that the borrower is not resolving their obligations but merely shifting them around. While this may help them appear up to date on repayments in the short term, it’s a fragile strategy that can quickly unravel.

Hidden liabilities are the kind that most easily slip past a surface-level review. They don’t show up in credit reports and are often disguised within everyday transactions. But they still weigh heavily on a borrower’s financial position. That’s why lenders must go beyond what is declared and conduct a thorough, line-by-line review of financial records to uncover these obligations. Understanding a borrower’s true financial load, whether formal and informal, is one of the best ways to assess whether they can responsibly take on more debt. Ignoring this layer can lead to decisions based on incomplete or misleading data.

Look for discipline beyond debt

Creditworthiness isn’t just about how much someone earns or how well they manage their debt. It’s also about whether they show signs of financial discipline outside of loan obligations. And one of the clearest indicators of that discipline is a savings habit. Borrowers who consistently set aside even a small portion of their income each month are sending a powerful signal. They understand the importance of planning. They know how to delay gratification. And most importantly, they are preparing for the future, not just reacting to the present.

Savings behavior, however modest, reveals more than just the ability to set money aside. It reflects a mindset: a commitment to financial health. These are people who are less likely to default when life takes an unexpected turn. Whether it’s a medical bill, car trouble, or a temporary job loss, those with savings have a cushion to fall back on. And that cushion often makes the difference between staying current on repayments and falling into default.

On the flip side, the absence of savings in a bank statement often tells its own story. It may indicate that the borrower is stretched to their financial limit, with every naira or dollar spoken for the moment it hits their account. This hand-to-mouth existence leaves no buffer for emergencies and creates a fragile financial state where any disruption, either a late salary, a sick child, or a broken phone can spiral into missed repayments or new loans taken out in desperation.

Lenders who only focus on how borrowers manage debt often miss this part. A borrower might have no active loans and yet still be high-risk because they lack the basic discipline to manage income proactively. Meanwhile, another borrower might carry moderate debt but consistently save on the side, signaling long-term financial resilience.

Ultimately, savings habits act as a silent character reference. They are not mandatory, like rent or loan repayments, which makes them an even stronger signal. Nobody forces a borrower to save. So when they do it voluntarily, month after month, it reveals a maturity and self-awareness that every lender should look out for. In assessing creditworthiness, this kind of discipline deserves as much attention as income or debt levels.

Spot the red flags early 

Early detection of red flags in a borrower’s financial behavior can make the difference between issuing a successful loan and walking straight into a default. The most concerning signs are often not dramatic. They’re subtle and easy to miss unless you’re looking closely. Things like sudden or unexplained cash deposits, recurring overdrafts, or inconsistent bill payments might seem like noise in the data, but they often signal deeper issues. A borrower might be scrambling to stay afloat or using short-term debt to plug gaps in their daily finances.

One of the clearest signs of financial distress is the presence of multiple repayments to different loan apps within the same month. This suggests a dependency on short-term credit just to get by. It’s not just about the number of loans, it’s the frequency and overlap that indicate a pattern. Similarly, when salary inflows are depleted within a day or two, it’s worth asking where the money is going. Is it being swallowed up by existing debts? Are there unrecorded obligations? Is the borrower simply unable to manage basic monthly expenses?

These red flags are not merely data points, they are behavioral cues. They tell you how a borrower handles pressure, whether they rely on quick fixes, and how much control they truly have over their finances. But spotting them is just the first step. The real work lies in interpreting them accurately. Lenders must approach this analysis with both curiosity and caution. Jumping to conclusions can lead to unfair exclusions, while ignoring the signs altogether increases exposure to risk.

It’s also important to look at frequency and recurrence. A single overdraft might not mean much, but if it happens every payday, that’s a trend. One delayed bill payment might be an oversight, but three in two months should raise eyebrows. The key is to connect the dots and view the borrower’s financial activity as a story, not just a series of transactions.

The truth is, these red flags don’t always mean a borrower should be rejected outright. They’re signals that demand further scrutiny. Sometimes, a deeper look reveals that the issues are temporary or circumstantial. Other times, they expose underlying instability that makes lending unwise. Either way, they should always shape the final risk assessment. Ignoring them is the same as flying blind.

Confirm loan repayment behavior

When a borrower says, “I’ve taken loans and paid them off,” don’t nod and move on. That claim must be treated as a hypothesis to be tested, not a fact to be accepted.

Start by scanning the statement for obvious signs of disbursement: lump-sum credits from lenders, especially ones labeled with references like “Branch,” “Tala,” “Revolut,” “Loan Disbursement,” or even informal naming like “Credit Transfer – Lender XYZ.” A real loan often has a timestamped trail. You’ll see the funds arrive, and shortly after, the money is withdrawn or spent.

Then go looking for repayments. Are there recurring debits with similar descriptors? Are these repayments weekly, biweekly, or monthly? Do the deductions continue steadily over time? If you find a pattern like $16 leaving the account every Tuesday for five weeks, that’s likely a repayment plan.

But it’s not just about spotting one transaction. Assess the borrower’s repayment behavior. Did they make timely payments or skip a few and later pay in bulk? Did they stop repaying halfway? Did they borrow from another lender to service the old one?

If you only find one loan repayment that was completed out of five visible disbursements, that borrower has a habit of ghosting lenders. That’s not someone you want to extend credit to.

Pro tip: Always ask the borrower which lender they’ve used before. If the statement shows no activity from that lender, they’re either lying or using another account to hide liabilities.

Identify “sweepers” and trace fund movements

A “sweeper” is a borrower who, the second their salary or business revenue hits the account, instantly transfers it somewhere else. You’ll notice it easily: salary comes in at 8:47 AM, and by 8:49 AM, it’s transferred to a fintech wallet, spouse’s account, or a second bank account.

What’s the motive? Avoiding deductions. Many sweepers are overleveraged and have standing orders or direct debit mandates with other lenders. So, the moment money hits their account, they ‘sweep’ it out to escape automatic collections. If you’re a lender trying to assess repayment ability, this behavior signals two things: They’re juggling too many lenders at once or they’re trying to avoid accountability.

To get the full picture, don’t stop at just the primary bank statement. Ask for wallet statements (e.g., Nubank, Alipay, Kuda) or other bank accounts where the funds are being swept to. You’ll often find that while one account looks “empty,” the real financial activity is happening elsewhere.

One borrower might appear cash-strapped on their traditional bank statement, but their mobile wallet, whether it’s PayPal, Cash App, or M-Pesa reveals a different story. They might be spending $100 a month on airtime and ordering takeout every Friday. You need to follow the money across platforms to get the full picture.

A good underwriter doesn’t just ask for a bank statement, they ask for the right bank statement.

Verify SME revenue with supporting documents

When lending to small and medium-sized enterprises (SMEs), bank statements alone are rarely enough to paint a full picture of the borrower’s financial health. Many SMEs, especially in developing markets, operate in cash-heavy or informal sectors. This means their revenue streams may not follow predictable patterns or appear as consistent, labelled deposits in a business account. Relying solely on the bank statement can leave major gaps in understanding the true scale and nature of their operations.

This is where supporting documents become critical. Ask for customer invoices, signed sales receipts, mobile money transaction histories, POS statements, and payment confirmations from digital channels like WhatsApp or Instagram, which many small businesses use to manage orders. The goal is to triangulate what the SME claims to earn with what is verifiable. For instance, if a fashion retailer claims to make $600 monthly, they should be able to show a backlog of messages, receipts, or delivery records that support that volume. And those earnings should, at least in part, be traceable in the form of mobile deposits, transfers, or bulk cash lodgements in their bank account.

This type of cross-checking helps lenders separate genuine businesses from those exaggerating their income to secure loans. It also allows a lender to see how disciplined the borrower is in recordkeeping and customer transactions, both important indicators of financial maturity. In many cases, it is this attention to supporting documents that uncovers the difference between a hobby and a viable business.

Corroborate the borrower’s narrative with the data

Perhaps the most overlooked step in analyzing a bank statement is matching the story the borrower tells with what the financial data actually shows. Borrowers rarely present their circumstances in purely neutral terms. Sometimes they’re trying to put their best foot forward, other times they’re attempting to downplay financial stress. It’s not always malicious, it’s human nature. A borrower might say, “I recently got a great job,” or “Things were rough for a while, but they’re much better now.” These statements can’t be taken at face value. They need to be checked against the cold facts.

If a borrower claims to be employed but no salary credits show up during the claimed period, that’s a red flag. If they mention that business has picked up, but the bank statement shows irregular income and mounting charges, it may suggest a gap between aspiration and reality. Even seemingly harmless claims, like “I have a major deal coming soon,” must be approached with skepticism unless there’s evidence to support forward momentum such as increased deposits, down payments, or incoming transfers that align with that claim.

This is not about assuming the worst. It’s about being grounded in what’s verifiable. A well-told story can be persuasive, but numbers offer something more dependable. They reveal whether the borrower truly has financial momentum or is still trying to get out of a rut. The bank statement is an unfiltered record of how money is earned, spent, and managed. If the numbers contradict the narrative, the numbers should take precedence every time.

Lenders who skip this cross-verification step risk anchoring decisions on misplaced confidence. They trust what’s said without examining what’s shown. That’s a risky move. Verifying the narrative against the data helps strip emotion out of the decision-making process and lets facts lead the way. If a borrower’s story checks out, it builds credibility. If it doesn’t, that’s a warning that due diligence is needed before proceeding.

Listening to the borrower is important, but listening to their bank statement is non-negotiable. The data won’t flatter you or try to impress. It just tells the truth and when making a credit decision, that’s exactly what you need.

Choose a qualitative approach

The best lenders today don’t just read numbers; they interpret behavior. A statement of account isn’t a spreadsheet to audit. It’s a behavioral record. Behind every inflow and outflow is a decision, a priority, a habit. And that’s where real credit insight lives.

Yes, the quantitative metrics matter; income, average balance, expense ratios, debt obligations. But those only tell what is happening. The qualitative layer answers the more important question: why.

Why does the borrower spend heavily at the beginning of the month? Why is there a pattern of savings for only three consecutive months before stopping? Why are there frequent transfers to friends just before payday?

Bank statements should be reviewed with the curiosity of a behavioral analyst, not just the precision of an accountant. You are not just evaluating the financial position. You are trying to understand the borrower as a financial actor.

What story do the patterns tell? Are they building toward stability or just surviving? Do they show signs of foresight and discipline, or impulse and volatility? Are they prepared for a rainy day, or are they consistently one emergency away from default?

When lending decisions are made with this kind of qualitative depth, approval becomes more than a numbers game. It becomes a judgment of character, resilience, and intent.

And if you can answer those behavioral questions with confidence, you are not just making a loan. You are managing risk like a pro.

AI will destroy lending. But here’s how lenders could fight back

Let me get straight to it: AI is poised to upend the lending industry as we know it. And not in some distant, sci-fi future. It’s happening right now.

This is 2025. Unless you’ve been living off-grid without internet access, you’ve probably noticed that AI is now dangerously proficient. Scarily so. What was once a novelty for tech enthusiasts is now a deeply integrated part of everyday tools, and it’s getting disturbingly good at deception. If you’re a lender and you’re not losing sleep over this, you’re either uninformed or in denial.

Let’s rewind a bit. Remember when students actually wrote their essays? Just two years ago, ChatGPT made its grand entrance, and the world hasn’t been the same since. Today’s students may never understand the struggle of writing an essay from scratch, battling typos, or agonizing over tone. Back then, tone was a personal touch. Now, it’s just another setting in your AI tool. But this is merely the beginning. If AI only corrected grammar and composed love letters, we’d be fine. But no, it had to evolve further.

We’re now in a world where a tool like ChatGPT can write job applications, fabricate employment histories, and convincingly generate bank statements. The AI that helps you polish your emails is now helping fraudsters polish their lies. Although the productivity upside is huge. But for lenders, this same technology is turning into a nightmare.

Remember when a forged document looked like it was forged?

It used to be that you could easily spot a fake document. The font would be wrong, the formatting sloppy, the grammar laughable. You’d look at a suspicious payslip and instantly know something was off. Not anymore. These days, AI-generated documents are not only accurate but also hyper-realistic. They come with just enough variation to mimic a real-world scenario; misspellings in the right places, timestamps that match bank operating hours, salary numbers that align with market benchmarks. These aren’t the cheap forgeries of the past. These are professional-grade fakes that could fool a trained compliance officer, and they’re getting better by the month.

The scary part is how easy this has become. A quick prompt to an AI model and you have a fully fabricated three-month bank statement with perfect arithmetic, realistic merchant names, and plausible spending habits. Want to fake an offer letter? Just describe the company, job title, and salary range. Need a utility bill? That can be generated too. It’s not just that the fakes are good. It’s that they’re effortless. And when forgery becomes this easy, the default assumption in lending, that what a borrower submits is real, gets flipped on its head.

Lending is built on trust. AI is wiping that out.

The foundation of lending has always been trust backed by documentation. Whether you’re giving out a small personal loan or a multimillion-dollar mortgage, you’re relying on some form of evidence that the borrower can pay you back. This is where the famous “5 Cs of credit” come in: character, capacity, capital, collateral, and conditions. Some add two more Cs, like credit history and cash flow, but the principle is the same. You’re looking for proof that the borrower is both willing and able to repay.

All these Cs rely on some form of documentation. You want to verify income? Ask for a payslip. You want to assess cash flow? Ask for a bank statement. You want to confirm employment? Ask for an offer letter. The problem is that AI can now generate all of these with such convincing detail that lenders no longer know what’s real and what’s fiction. We’re entering a world where evidence can no longer be trusted at face value. And once that happens, the entire framework of credit decisioning starts to wobble.

I’ve seen the fakes, and they’re getting smarter

In the last year alone, through my interactions with Lendsqr lenders and the credit ecosystem in general, I’ve observed a noticeable spike in suspicious documentation submitted by borrowers, especially in markets where traditional credit bureaus are weak and lenders rely heavily on self-reported data. Many of these documents, bank statements, payslips, and offer letters arrive with formatting and language that appear flawless on the surface. But when verified against actual data sources, like payroll systems, the discrepancies become clear.

While I can’t say for sure AI was used in all of these forgeries, the quality and speed at which they’re produced point strongly in that direction. It’s no longer uncommon to see identical documents submitted across unrelated loan applications or to find income claims that don’t align with transactional patterns. These trends suggest borrowers are increasingly relying on tools that automate and enhance the forgery process, making manual review almost pointless.

And that’s not even the worst part. We’re now seeing attempts to spoof video verifications, with deepfakes and synthetic selfies passing rudimentary liveness checks. These aren’t people wearing masks or hiding in shadows. These are full-on facial overlays using open-source tools that can mimic blinking, head movements, and even speech. 

And no, your “move-your-head-left-and-smile” liveness prompt isn’t saving you. These deepfakes are trained to mimic those exact cues. In fact, researchers from Sensity AI flagged over 1,000 deepfake identity attacks between 2022 and 2024, targeting financial services and crypto platforms specifically.

In other words, a fraudster can show up to your KYC process looking like a totally different person, and you won’t know unless you have military-grade detection tools.

And I wish I could say this is a niche problem, but it’s not. From Lagos to Copenhangen, from Sao Paulo to Kuala Lumpur, we’re seeing a pattern. AI isn’t just making fraud easier. It’s making it scalable.

The traditional defenses are no longer enough

It’s tempting to believe that better fraud teams or more document reviewers will solve the problem. But that’s like bringing a water pistol to a forest fire. This isn’t about human error anymore. It’s about systemic failure. The old model of “submit your documents and we’ll review them” is collapsing. In the face of AI-powered forgery, trusting user-submitted documents is becoming a liability.

This means the only way forward is to remove the borrower from the equation, at least when it comes to submitting proof. Allow me to elaborate. Consider bank statements. Instead of requesting a borrower to send a downloaded PDF (which AI can forge), it’s preferable to connect directly to their bank. If the bank confirms a monthly income of $3,000, that’s credible information. Banks have no incentive to lie.

Payslips? Let’s dig deeper. Soon, lenders will only accept payroll information that comes directly from either the employer, an HR SaaS platform, or the government. If you received payment, let’s examine your tax records or pension contributions.

This is already happening through open banking frameworks in countries like Australia, Brazil, and the UK. The lender accesses real-time financial data through regulated APIs, removing the guesswork and eliminating the potential for fraud. In this new world, if I can’t trace it to the source, I won’t believe it.

No more PDFs. Only verified data.

This is the new normal. If your underwriting system still relies on PDF uploads, you’re building on sand. In this new world, we only trust what can be verified at source. Open banking is the clearest path forward, but it’s not the only one. Employers can be looped in through payroll APIs. Government databases can verify identity, address history, and tax records. Telecoms can provide behavioral credit scoring. In short, we are moving from a document-based system to a data-based system. And in a data-based system, forgery becomes nearly impossible, because the data is verified in real time and signed digitally.

It won’t be perfect. Fraudsters will try to spoof integrations, intercept API calls, or manipulate phone numbers. But these are harder to scale, and much easier to detect, than a well-crafted PDF forgery. With the right audit trails and cryptographic verification, we can catch these attempts before they do damage.

The war on AI fraud will be fought at the hardware level

And what about video verification? If AI can fake faces, are we doomed? Not necessarily. The next frontier of trust will happen at the hardware level. Just like Apple uses its Secure Enclave to store biometrics, we’ll soon need secure chips that can vouch for the authenticity of camera input. In other words, the device itself will sign off on whether a selfie or video came from a real user in real time, without being tampered with.

This is already being explored in the mobile security space. Trusted Execution Environments (TEEs) and Secure Elements can confirm that the image you’re seeing is unaltered, captured from a real device, and not replayed or synthesized. It’s not cheap tech, and it won’t roll out overnight, but it’s inevitable. And frankly, it’s the only way to stop the flood of synthetic identities before it becomes a full-blown crisis.

If you’re still using 2021 tools in 2025, you’re already cooked

Let’s be honest. The tools most lenders are using today were built for a pre-AI world. They were never designed to detect generative forgeries or deepfakes. If your fraud detection system hasn’t been updated since the pandemic, you’re already obsolete. This is not the time to be complacent or nostalgic about how things used to work.

At Lendsqr, we’ve been investing aggressively in fraud detection, real-time data verification, and AI counter measures. Not because it’s trendy, but because we don’t have a choice. We work with lenders across geographies where fraud levels are not just high, they’re innovative. The fraudsters are evolving faster than most regulators, and definitely faster than most banks. We can’t afford to wait.

AI won’t kill lending. But it will kill lazy lenders.

AI isn’t evil. It’s just powerful. And like any powerful tool, it can be used for good or bad. The responsibility lies with us: the builders, the lenders, the operators. If we sit back and wait for someone else to solve this, we’ll be wiped out. Not just in reputation, but in losses, defaults, and regulatory blowback.

But if we act now, build the right verification infrastructure, and stay a step ahead, we can not only survive, we can thrive. Lending will always be a business of trust. The difference now is that trust must be verified, not assumed.

I’ve staked my career, my company, and my sanity on helping lenders succeed. I’m not going to let generative AI wipe out the progress we’ve made. Not on my watch. Because I still believe in the power of credit to change lives. But I also believe in meeting challenges head-on, not pretending they don’t exist.

Let’s fight smart, build resilient systems, and ensure that the future of credit is still human, just a bit more skeptical, and a lot more secure.

I’m building Lendsqr to be the world’s best loan management ecosystem

If credit is ever going to be truly transformational, someone has to build the infrastructure that makes lending safe for lenders, efficient, and scalable. Someone has to create a foundation that lenders, big or small, can rely on. And after years of watching the gaps in the system, I decided that someone had to be me.

But let’s be honest, building a loan management system isn’t exactly the sexiest thing in fintech. Payments? Sure. Digital banking? Of course. But lending infrastructure? That’s the unglamorous, behind-the-scenes work that no one really wants to do. 

And this isn’t an African or Asian problem. It’s a global problem for every lender from Argentina, all the way to Canada. From New Zealand, all the way up to Japan. The cost and the complexity of tech needed by aspiring lenders is just unattainable for most.

And yet, without it, there’s no credit system. No way to support small businesses. No true financial inclusion.

When I started Lendsqr in 2018, it was just a side project. You know how it goes, tinkering with an idea, running small tests, and pushing it forward when time allows. The first iterations with good friends, Chioma Ukariaku and Ridwan Olalere (founder and CEO of LemFi) didn’t go anywhere. 

But at some point, I hit a crossroads. I had to decide whether to keep doing this halfway or go all in. That decision wasn’t easy, but it became clear after a conversation with my bosses at the time, Aigboje Aig-Imoukhuede and the late Herbert Wigwe. They gave me their full blessings to chase this vision.

And so, I jumped in. Headfirst. With no safety net and no parachute. Just an irrational belief that this had to be done and that we were the ones to do it.

The moment I knew Lendsqr had to be the best in the world

Growth wasn’t immediate. Numbers didn’t skyrocket overnight. Some days, it felt like we were grinding endlessly with little to show. But one day, it hit me. If I was going to build something worthwhile, why stop at “good enough”? Why not aim for the absolute best?

That realization was both exciting and daunting. No African company had ever built a world-class loan management system before. Sure, we’ve seen incredible companies like Paystack making strides with Stripe globally, but a lending infrastructure company fully founded in Africa, serving African lenders first and then scaling worldwide? That felt like an impossible mission. And yet, that’s exactly why I wanted to do it.

So, how have we done so far? Well, we’ve made significant progress with over 6,000 lenders serving 2.4m customers. We’ve benchmarked ourselves against other competitors on the continent. We’re doing quite good

Yet, when you compare us to global giants like Finastra, HES Fintech, DigiFi, and Turnkey Lender, we’re not there. Not yet. But that’s fine because the goal isn’t to catch up. It’s to surpass them.

The plan: How we’ll beat the global leaders

Lendsqr is not trying to be just another loan management system. We’re here to be the absolute best. And we’ll get there by focusing on three core pillars:

Creating the most user-friendly loan management system

Most loan management systems are a nightmare to navigate for an average human, including Lendsqr, at this time. They’re clunky, overwhelming, and require an engineering degree just to run a simple operation. That’s not how lending should work. We are committed to making Lendsqr intuitive and so easy that a lender can get up and running in minutes without needing extensive training or technical expertise.

Offering the most cost-effective solution

The big players charge exorbitant fees for their systems, making them inaccessible to many lenders, especially in emerging markets. Our approach is different. We are delivering a world-class system at a fraction of the cost, ensuring that businesses of all sizes can afford a reliable loan management platform without compromising quality. While we are still pricey, we offer value for money but can only get cheaper for non-enterprise customers – those who need us the most.

Building a feature-complete system that solves their problems

Lenders don’t need bloated software with features they’ll never use. They need a system that actually works for them. That’s why we’re focused on building exactly what matters: factoring and mortgage support are coming soon, multi-user applications for lending teams are already in development, and while full-scale accounting and CRM aren’t here yet, they’re on our roadmap. We know what needs to be done, and we’re making it happen.

The African advantage: Building with what we have

There is a misconception that only teams from Silicon Valley can build world-class products. That’s simply not true. While we don’t have the luxury of hiring foreign engineers with sky-high salaries, we see this as an opportunity rather than a setback.

Look at India. Just a decade ago, who would have thought they’d be home to world-class companies like Postman, Zoho, and Freshworks? Now, they’re global benchmarks. China, once dismissed as unoriginal, has become a powerhouse of AI and EV innovation. Even LG from South Korea, which was once considered a cheap brand, now makes some of the best consumer tech out there. The world moves fast, and perceptions change even faster.

Africa is full of brilliant, driven, and resourceful talent. We hire smart, ambitious people and train them to be highly technical, regardless of their department. At Lendsqr, marketing, HR, and operations teams learn how to analyse data, write SQLs, automate tasks, and contribute technically. Next quarter, every single person in my team will be learning Python.

We also keep costs insanely low. No flashy events. No wasteful spending. We run fully remote because, frankly, I have expensive taste, and renting an office would be an unnecessary burn. Every penny is reinvested into building the best product possible.

And yes, I haven’t paid myself in a long time. People assume I’m living large, but the reality is I am putting everything back into this company. This isn’t a vanity project. It’s a long-term vision.

The challenges we’ve faced (and how we’re overcoming them)

Building something this ambitious has not been easy. We’ve faced obstacles at every turn, but instead of seeing them as setbacks, we treat them as lessons that push us forward. Here’s how we’re tackling the biggest challenges head-on:

Finding the right talent

Hiring for technical skills is one thing, but hiring for the right mindset is another. We’ve had to be extremely selective, bringing in only those who have both the intelligence and the resilience to build something great. Our team isn’t just made up of employees; it’s a group of problem-solvers who believe in our mission and are ready to push boundaries. Our solution? A rigorous hiring process that prioritizes adaptability, technical curiosity, and a willingness to learn. And once they’re in, we invest heavily in their growth, ensuring they develop into world-class professionals.

Automating sales for scalability

Building a great product is only a tenth of the battle. Selling it efficiently is just as critical. We are continuously refining our strategies to automate sales, ensuring we acquire and retain customers without relying on expensive and ineffective marketing campaigns. This includes refining our onboarding flows, data-driven research and outreach, and ensuring our product speaks for itself. The goal is to make customer acquisition a repeatable and cost-effective process. To make this happen, we’ve doubled down on automation of all kinds, enhancing in-app guidance, and optimizing every touchpoint for conversion. If a lender can discover, try, and love our product without needing hand-holding, we know we’ve done it right.

Growing with the right partnerships

Success doesn’t happen in isolation. We’ve been fortunate to receive support from AWS, Microsoft, and Google, which has significantly reduced our infrastructure costs. But beyond cloud providers, strategic partnerships with financial institutions like Sterling Bank, who, by the way, irrationally believes in us. Industry leaders like Ope Adeoye of OnePipe who has been instrumental in some of our infrastructure play. These partnerships are not just about financial backing. They are about aligning with organizations that see the future of lending the way we do.

What success looks like to us

There’s no grand speech about changing the world here. Just a clear goal: build a loan management ecosystem that does the job better than anyone else. That means focusing on what actually moves the needle; shipping a solid product, hiring the right people, and growing sustainably.

We’re not burning money on fancy marketing. Instead, every penny goes into making Lendsqr the best it can be. While others are downsizing, we’re still hiring engineers, interns, and product owners because the work isn’t done.

This isn’t about quick wins or short-term hype. It’s about proving that an African company can set the global standard for fintech infrastructure. If we succeed, we will redefine lending for businesses worldwide. And if we don’t? It won’t be for lack of effort.

But let me be clear; My team and I have no intention of failing.

Paying with cards online in Africa is a nightmare and it won’t get better anytime soon

Online payments should be simple. Navigate to merchant checkout, enter your card details, hit pay, and boom, the transaction is completed! That’s how it works in Asia, Europe, Mars, North America, Venus, and basically every developed market. But in Africa? Good luck with that.

If you’re an investor from Silicon Valley mapping out your million-dollar fintech strategy, thinking, Oh, Africa has 1.5 billion people, so surely millions of them use cards, right? Calm down. It doesn’t work like that. Cards are a disaster here, and if you’ve ever tried to make an online payment in Africa, you already know the struggle.

Let’s be honest, paying online with a card in Africa is like an obstacle course, and not the fun kind. It’s the kind where every hurdle is higher than the last, and by the time you think you’ve won, someone moves the finish line. Even as fintechs and banks try to push online card payment, reality has other plans. People either don’t have them, can’t get them, or find them useless when they finally do. And the worst part? None of this is going to change anytime soon. Here’s why.

The “everyone has a bank account” myth

Let’s start with the basics. Not everyone in Africa has a bank account. And even if they do, that doesn’t mean they have a card. In Nigeria, for instance, only about 50 to 70 percent of bank account holders even bother getting one. Why? Because getting a card is too much trouble.

Think about it. Cards are physical. You have to go to a bank branch (not exactly fun), stand in long queues, and pray that the network is working that day. Sure, some banks now issue instant cards, but rewind just five years ago, and you’d have to wait weeks. And let’s be honest, if you had to leave your business or daily hustle just to get a card, you probably wouldn’t bother either.

And even if you somehow manage to get a card, guess what? It doesn’t guarantee smooth payments. In fact, the headache is just getting started.

Even when people have cards, they can’t use them online

Okay, let’s say you finally get a card. Fantastic. But what happens next?

First, not everyone is sophisticated. Inserting a card into an ATM and punching in a PIN is easy. It’s the same interface across Africa. But try making an online payment, and you’re in for a different experience. Every website and payment provider has a different flow. What you see on Paystack isn’t what you get with PayFast. So even if you’ve memorized how one platform works, that knowledge won’t help you elsewhere.

Now, add to that the fact that the quality of cards here isn’t even great to start with. They wear out fast. if you’ve used an ATM in Africa, you’ve seen those cards with numbers completely rubbed off. Now imagine trying to make an online payment when you can’t even read your own card details. Some people forget their cards entirely, leaving them at home or buried in some wallet no one can find. Others walk around with expired debit cards, completely unaware.

And even when the card is in perfect condition, it still might not work. Some banks require customers to “activate” their cards before they can make online payments. No activation, no transaction. Then there’s fraud protection, which often kills transactions before they even begin. Many African banks insist on sending OTPs (one-time passwords) for security. The problem? Mobile networks here are unreliable. Sometimes the OTP never arrives, sometimes it takes forever, and sometimes the bank just blocks the transaction for fun.

By the time you go through all this trouble, only about 10 to 20 percent of banked customers can actually make online payments with their cards. And those 10 to 20 percent? They’re just lucky.

Even when cards work, they don’t work

So you’ve got your card, and miraculously, it’s in your hand, activated, and ready to use. You go to an e-commerce site, enter your details, and… nothing. The transaction takes forever to process or the internet connection fails midway. Perhaps, the bank’s system crashes. Or you feel you refresh the page by mistake, and the payment vanishes into thin air.

E-commerce businesses in Africa learned this the hard way. In the early days, they relied on card payments, until they realized that customers just couldn’t complete transactions. That’s why “payment on delivery” became a thing, and that, too, turned into a nightmare when customers ghosted on payments.

Even when a payment miraculously goes through, there’s no guarantee the merchant will actually receive the money. Failed settlements, chargebacks, and fraud disputes mean that even businesses are skeptical of cards. So, what’s left? A whole lot of frustration and some seriously angry customers.

Addressing in Africa is a mess

Let’s say a bank wants to solve this card problem by delivering them straight to customers. Well, good luck with that, because address systems in most African cities are a joke. Unless you’re in a few select parts of South Africa, good luck finding a street number that actually exists. So banks can’t even mail cards efficiently.

Ever tried directing a delivery guy to your house over the phone? “Take the third right, pass the big tree, then turn left at the yellow gate.” That’s how addresses work here. Now imagine a bank trying to mail you a sensitive financial document like a debit card. It’s just not happening.

Sure, fintechs like Moniepoint, Kuda, Sterling Bank, and Tyme are trying to deliver cards directly to customers. But it’s expensive, and no one wants to absorb the cost. So, mass adoption? Not happening anytime soon.

Cards are dying, and honestly, no one will miss them

Here’s the truth. Cards have overstayed their welcome. They are clunky, outdated, and impractical for the African market. Mobile money, bank transfers, and virtual accounts are already replacing them. And honestly, good riddance.

I spent years selling cards across African markets, and if there’s one thing I’ve learned, it’s this. Cards are simply not the future here. And that’s okay. Because the next wave of payments in Africa will be faster, more reliable, and most importantly digital.

The best part? Africans have already figured it out. Mobile wallets, USSD transfers, QR codes, and instant bank transfers are the real MVPs here. Who needs plastic when you can pay with your phone in two seconds?

So, if you’re still wondering why cards aren’t taking off in Africa, here’s your answer. We skipped that step. And honestly, we’re better off without them.

The global card giants are catching on

Even Visa and Mastercard are adjusting to this shift. They’ve started partnering with fintechs to push virtual cards, QR payments, and mobile-based solutions instead of traditional plastic. In Kenya, Mastercard has integrated with M-Pesa to facilitate digital transactions, while Visa is working with Nigerian banks to enhance mobile-based cardless payments. The message is clear. Africa is moving beyond plastic, and the big players are following suit.

So, the next time a fintech startup pitches a grand plan to “revolutionize” Africa with cards, tell them to save their breath. We’ve moved on. And anyone still clinging to plastic is living in the past.

Why time to first utility is critical for African SaaS

If your SaaS product does not deliver value instantly, your users will leave faster than a bad date. That is not an exaggeration, it is a fact backed by numbers: 55% of users spend less than 15 seconds on a new website before deciding if they will stay or leave. Now imagine how little patience they have for a slow, complicated software onboarding process.

When you buy something, you expect it to work as soon as possible. If you take a painkiller, you expect relief fast. Nobody wants to wait forever to get value from something they just paid for. Software is no different. People want to get value from it immediately. That “immediately” part? That’s what time to first utility (TTFU) is all about.

What is time to first utility (TTFU)? 

Time to First Utility (TTFU) is the time it takes from when a user discovers your software to when they experience their first real moment of value, also known as the “aha” moment. The shorter this time is, the more likely users are to stay. The longer it takes, the more likely they are to leave. It is one of the most critical factors in user retention, especially in SaaS, where first impressions can make or break adoption.

Customers don’t give a damn about your “standards”

When a user first interacts with software, they are making a quick decision. Does this work for me or not? If they hit a roadblock before even getting a taste of what the software can do, they will leave. It does not matter how great the software is if the first experience is a mess.

This is where many African SaaS companies are getting it wrong. We build fantastic products, but we also put up barriers that slow users down. Regulation, KYC requirements, licensing restrictions. All these things are important, but they should not be the first thing a user experiences.

You think users care about why your onboarding is complex? No one is sitting around thinking, “Oh wow, this company must have valid reasons for making sign up so difficult.” They just leave. People expect to try your software immediately. That’s why products like remove.bg kill it. You upload an image, and boom, background removed. No drama. No fucking around. Just instant gratification. That’s what we need to replicate in African SaaS.

At Lendsqr, we know this struggle well. Lending is a regulated business. You cannot just let people in without verifying them. But at the same time, we realized that if we make people jump through too many hoops before they even see what the software can do, they will never come back.

Too bad that many have run away, but I’m getting y’all back! 

African founders are getting TTFU wrong

One thing is clear: Africa’s SaaS market is on the right trajectory, and it is projected to hit $10 billion, with startups springing up across Lagos, Nairobi, Cape Town, and Cairo. The talent is there, the demand is growing, and the innovation is undeniable. Yet, we have a serious problem, too many hoops before users get to experience value.

And here’s the hard truth: users don’t care. They’re not going to sit around and wait. They’re not going to fight through layers of friction just to see if your software is worth it. They’ll leave.

In Africa, where internet costs are high and digital trust is still fragile, users are even less patient. If they struggle to access your product in the first few minutes, they’re more likely to churn permanently.

And it’s not because the software is bad. In fact, a lot of African SaaS products are brilliant. The issue is the barriers we throw in front of users before they can even experience the value. Too much KYC upfront is a major culprit. Yes, regulations matter, but if a user has to submit their ID, utility bill, and a small goat (okay, maybe not that far) before they can even try your software, they’ll bounce. 

Onboarding is another headache. If it takes days for someone to get access or approval, they’re already gone. Then there’s the problem of integrations. Too many SaaS products exist in isolation, forcing users to manually transfer data between platforms, which is frustrating and inefficient. And let’s not forget pricing. If users have to email support just to figure out how much they need to pay, they’ll move on to something simpler. Every extra step is a chance for them to leave, and they do.

The solution is simple: reduce friction, deliver value faster, and make it ridiculously easy for users to get started.

My experience with TTFU at Lendsqr

I’ll be the first to admit that we’ve made this mistake at Lendsqr, and it cost us. When we first started, we assumed that anyone who wanted to use our platform would be willing to go through the necessary regulatory steps first. After all, lending is a regulated business, right? You need a license, you need KYC, you need a payment provider, you need this, you need that.

But here’s the thing, when people first discover a product, they don’t care about any of that. They just want to see it work. And instead of giving them that quick win, we were hitting them with roadblocks: Sign up? Great. Now, go get a payment provider. Want to test out the system? Sorry, you need a lending license. Oh, you’re from Zambia? Oops, no SMS provider for your country.

It was a disaster. We spent time, resources, and money bringing people in, only to have them leave disappointed. We were failing on a fundamental level. We had to rethink everything. And here’s what we did:

First, we ditched SMS authentication in favor of WhatsApp. SMS requires setting up providers for each country. WhatsApp works everywhere. Problem solved.

Second, we stopped blocking users from signing up just because there was no payment provider in their country. If there is no payment provider, fine. Let them proceed and figure it out later. At least they get to see how the platform works.

Third, we started pre-integrating with key providers upfront in our priority markets. This means when lenders from those countries sign up, they don’t immediately hit a wall.

We also relegated some requirements to come in later. For example, Nigerian lenders no longer have to provide their bank account and BVN upfront. That only matters when money actually needs to move. Why make them do it before they even see what the platform can do?

And to simplify setup, we built a golden path. Instead of overwhelming users with a million settings, we set smart defaults so they can issue their first loan without configuring every little detail.

The result? Less friction, faster time to first utility, and a much better chance of turning new signups into active lenders.

The one minute rule we must all follow

If you’re building a SaaS product in Africa, you need to ask yourself one question: how fast can a user see value? If the answer is anything more than a minute, you have work to do. Because if you don’t fix it, your users will find a competitor who has.

Sometimes, that competitor is them “doing nothing” or some low key manual process. Who cares who the competitor is if the customers dump your ass? Either way, you lose.

At Lendsqr, we’re making sure that users can get their first taste of value in under a minute. We’re not all the way there yet, but we know that if we don’t nail this, we don’t stand a chance. And neither do you.

So, if you’re building SaaS in Africa, do yourself a favor, cut the friction, make it work instantly, and watch your business take off.