In January 2025, Alerzo, one of Nigeria’s most prominent B2B e-commerce startups, secured a ₦5 billion (~$3.6 million) working capital loan from Moniepoint Microfinance Bank.
The logic was sound. Alerzo delivered goods to thousands of small retailers across Southwest Nigeria. Moniepoint processes over 80% of in-person payments nationwide. Its point-of-sale (POS) terminals sit inside thousands of shops that Alerzo supplies. The fintech could see the merchants’ cash flows in real time: revenue, frequency, velocity, seasonality.
If data ever guaranteed a loan, this was it.
Twelve months later, Moniepoint was in Federal High Court Lagos seeking permission to freeze Alerzo’s accounts. The outstanding balance stood at ₦4.38 billion (~$3.2 million), with interest still accruing. The court granted a Mareva injunction restraining every Nigerian bank from releasing funds linked to the company or its principals.
Videos surfaced online showing rows of Alerzo-branded vehicles parked at its Ibadan facility, reportedly being prepared for asset liquidation. As TechMoonshot reported last week, Alerzo’s collapse is now Nigeria’s highest-profile B2B e-commerce default, exposing structural problems in a sector that raised hundreds of millions on the promise of digitizing informal retail.
But Alerzo wasn’t alone.
Around the same time, Moniepoint’s microfinance arm quietly went to court seeking an order restraining every bank from dealing with funds held by Retail Supermarkets Limited, owners of the ShopRite franchise in Nigeria, over a ₦2.4 billion (~$1.7 million) working capital facility that had gone unpaid.
That case, which unfolded late last year with far less public attention, targeted one of the country’s most recognizable retail chains — physical stores, steady foot traffic, and years of operating history.
Two major defaults. Two borrowers with completely different profiles. Same lender. Same lending model. Same outcome: data-driven underwriting met the messy, unpredictable reality of Nigerian business and lost.
Moniepoint’s position is complicated. The unicorn, which raised over $200 million in its Series C round last year from investors including Development Partners International, Google’s Africa Investment Fund, and Visa, has built its lending model around payment data. It disbursed more than ₦1 trillion (~$735 million) in loans to 70,000 small businesses in 2025, targeting provision stores, supermarkets, and building material traders.
That’s 99.4% repayment success, if you assume the two publicized defaults are the only major failures. But the existence of two high-profile defaults — totaling ₦6.78 billion — suggests that knowing everything about a business except what happens next is not the same as controlling risk.
And if Moniepoint, with 80% market share in POS payments and real-time visibility into 6 million active businesses, can’t predict which loans will blow up, then what does that say about the entire fintech lending thesis?
The ₦1 Trillion Bet on Data-Driven Credit
Let’s start with what Moniepoint actually built, because the scale is staggering.
Founded in 2015 as TeamApt by Tosin Eniolorunda and Felix Ike, Moniepoint initially provided payment infrastructure for Nigerian banks. In 2019, it pivoted to serve small businesses directly, deploying POS terminals and offering digital payments, banking, and credit.
By 2025, Moniepoint had become Nigeria’s largest merchant acquirer, processing:
- 14 billion transactions (169% increase from 2023)
- ₦412 trillion in transaction value ($297 billion)
- 38.5% of Nigeria’s total payment volume (compared to NIBSS, the national clearing system, which processed ₦1.07 quadrillion in 2024)
- 6 million active business accounts
That transaction data became the foundation for Moniepoint’s lending business. In 2023, it disbursed $71 million in working capital loans. By 2025, that figure exploded to ₦1 trillion ($720 million) — a 10x increase in two years.
The pitch was compelling: traditional banks require collateral, audited financials, and formal credit histories that 94% of Nigerian SMEs don’t have. According to a 2017 SMEDAN survey, less than 6% of MSMEs in Nigeria had accessed financing.
Moniepoint solved that by using alternative data:
- POS transaction frequency (how often does the shop receive payments?)
- Average transaction size (what do customers spend?)
- Velocity (is revenue growing, stable, or declining?)
- Seasonality (does the business have predictable cycles?)
- Payment patterns (are bills paid on time?)
From that data, Moniepoint’s algorithms generate credit scores, approve loans within 24-72 hours, and disburse capital without requiring traditional collateral. For informal businesses — neighborhood kiosks, building material shops, pharmacies — it’s transformative.
And it worked. According to Moniepoint’s 2025 Year in Review, businesses that accessed credit experienced an average 36% increase in transaction value. That’s not hype. That’s real growth — inventory expansion, equipment purchases, working capital to stock high-demand products.
Felix Ike, Moniepoint’s CTO, told The Fintech Times: “30% of businesses which receive working capital loans from Moniepoint say it is the first time they’ve ever been able to access credit. For the other 70%, Moniepoint often provides them two to three times the last loan they could obtain from typical financial institutions.”
The model looked perfect. Real-time data. Instant credit decisions. Rapid disbursement. Tangible impact. 99%+ repayment rates.
Until Alerzo and ShopRite defaulted.
The Alerzo Default: When B2B E-Commerce Structural Problems Met Debt Obligations
Alerzo launched in 2018 as one of Nigeria’s most promising B2B e-commerce platforms. It raised over $20 million from Nosara Capital, Capria Ventures, and others to deliver fast-moving consumer goods (FMCG) directly to small retailers.
The business model: aggregate demand from thousands of small shops, negotiate bulk discounts from suppliers, and deliver inventory directly using Alerzo’s logistics fleet. Margins on FMCG are razor-thin — 2-5% — but at scale, the theory goes, you can build a profitable distribution business.
The reality: those margins never materialized. Warehouse costs, fuel, driver salaries, spoilage, and inventory financing consumed gross margins. Alerzo burned cash on every delivery, hoping scale would eventually bring profitability.
When Moniepoint extended a ₦5 billion loan in January 2025, Alerzo’s POS transaction data likely looked strong. The company was processing payments across thousands of retail partners. Revenue was flowing through Moniepoint’s terminals. The data said: creditworthy.
But the data couldn’t see:
- Unit economics that didn’t work — 2-5% margins couldn’t cover operating costs
- Competitive pressure — rivals like Wasoko, MaxAB, TradeDepot, and MarketForce were all fighting for the same low-margin business
- Structural cash burn — B2B e-commerce in Nigeria is capital-intensive and unprofitable at current scale
- Inventory risk — Alerzo was carrying inventory on credit, and when suppliers demanded payment, cash flow collapsed
By December 2025, Alerzo couldn’t service the loan. Moniepoint filed suit. By January 2026, a Mareva injunction froze Alerzo’s accounts. By February, the company was liquidating its fleet of buses and motorcycles.
As TechMoonshot reported, Alerzo’s default is now the highest-profile B2B e-commerce failure in Nigeria, joining Sabi (pivoted away from retail), MarketForce (shut down RejaReja platform), and others in the graveyard of companies that couldn’t make 2-5% margins work.
The lesson: Real-time payment data shows you what’s happening. It doesn’t show you why it’s happening. And it definitely doesn’t predict what happens when a fundamentally unprofitable business runs out of runway.
The ShopRite Default: When Even Physical Retail Giants Can’t Pay
If Alerzo’s default exposed the limits of data-driven lending in speculative startups, the ShopRite default exposed something even more uncomfortable: even established retailers with physical footprints can fail to repay.
ShopRite is one of Africa’s largest supermarket chains, operating across Nigeria, South Africa, Ghana, and other markets. In Nigeria, Retail Supermarkets Limited owns the franchise, operating stores in Lagos, Abuja, and other major cities.
ShopRite has:
- Physical stores (not just a digital platform)
- Steady foot traffic (customers walk in daily)
- Years of operating history (not a 3-year-old startup)
- Predictable cash flows (groceries are recession-resistant)
On paper, ShopRite is exactly the kind of borrower that payment data should underwrite confidently. And yet, Moniepoint’s ₦2.4 billion working capital facility went unpaid.
What happened?
Nigeria’s retail sector has been under enormous pressure:
- Currency depreciation: The naira lost significant value against the dollar in 2024-2025, making imported goods expensive
- Inflation: Over 30% inflation eroded consumer purchasing power
- Power costs: Unreliable grid electricity forced retailers to run expensive diesel generators
- Competitive pressure: Hypermarkets face competition from informal markets, where prices are lower
Even with strong transaction data showing daily revenue, ShopRite’s costs outpaced income. Working capital loans that looked safe when extended became unserviceable when macro conditions deteriorated.
The lesson: Payment data captures what customers are spending. It doesn’t capture whether the business is profitable. And it definitely doesn’t predict macroeconomic shocks that erode margins faster than revenue can grow.
The Data Paradox: Knowing Everything Except What Matters Most
Moniepoint’s lending model is predicated on a simple thesis: if you have enough transaction data, you can predict creditworthiness better than traditional banks.
Traditional banks use:
- Collateral (property, assets)
- Credit history (formal borrowing records)
- Financial statements (audited P&L, balance sheets)
Moniepoint uses:
- Real-time POS transaction data
- Payment velocity and frequency
- Merchant cash flow patterns
- Seasonality and growth trends
The data Moniepoint sees is granular, real-time, and comprehensive. It knows:
- How much revenue a shop generates daily
- How many customers walk in
- What products sell fastest
- Whether payments are declining or growing
What it doesn’t know:
- Why revenue is growing or declining (new competitor? Supply chain disruption? Macro shock?)
- Whether the business is profitable (high revenue doesn’t mean positive cash flow)
- What the borrower will do with the loan (inventory? debt repayment? personal expenses?)
- How the business will respond to external shocks (currency crisis, inflation spike, regulation change)
This is the data paradox: you can have perfect visibility into what’s happening and still have no idea what happens next.
And when you’re lending ₦1 trillion across 70,000 businesses, even a 1% default rate means ₦10 billion in losses. If the Alerzo (₦4.38B) and ShopRite (₦2.4B) defaults represent just the publicly visible failures, the actual NPL (non-performing loan) rate could be higher.
The Structural Risks Nobody’s Pricing In
Moniepoint’s lending model works — until it doesn’t. And the conditions that make it fail are systemic, not idiosyncratic:
1. Macro shocks
When inflation spikes, currency depreciates, or power costs surge, businesses struggle to service debt even if transaction volumes stay stable. Payment data can’t predict macro shocks.
2. Sector-wide failures
B2B e-commerce in Nigeria is structurally unprofitable at current unit economics. If Moniepoint lent to multiple B2B platforms (Alerzo, Wasoko, TradeDepot), all of them face the same margin compression. That’s correlated risk, not diversified risk.
3. Information asymmetry
Borrowers know their businesses better than lenders. A retailer might see transaction data declining and decide to take one last loan before shutting down. The lender sees steady transactions and approves.
4. Liquidity vs. solvency
Payment data measures liquidity (cash flow). It doesn’t measure solvency (assets vs. liabilities). A business can have strong daily revenues and still be insolvent if liabilities exceed assets.
5. Regulatory intervention
Nigeria’s Central Bank (CBN) has tightened regulations on fintech lending, POS transactions, and digital payments. If CBN caps interest rates, mandates cooling-off periods, or restricts POS deployment, Moniepoint’s business model shifts.
The Verdict: Data Wins Until It Loses
Moniepoint’s ₦1 trillion in loans to 70,000 businesses in 2025 is a landmark achievement. It proves that alternative data can unlock credit for Nigeria’s informal economy — the 94% of SMEs that traditional banks ignore.
The 99%+ repayment rate (assuming the two publicized defaults are the only major ones) proves the model works at scale.
But the Alerzo and ShopRite defaults prove something equally important: data-driven underwriting has limits.
Real-time payment data shows you what’s happening. It doesn’t show you why. It doesn’t predict macro shocks, sector-wide failures, or borrower behavior under stress. And it definitely doesn’t guarantee repayment when structural business problems meet debt obligations.
For Moniepoint, the question isn’t whether the lending model works. It’s whether it can scale to ₦5 trillion, ₦10 trillion, ₦20 trillion without accumulating unmanageable default risk.
For Nigeria’s fintech ecosystem, the lesson is clear: payment data is powerful. But it’s not magic. And betting everything on transaction history as collateral is betting that the future looks like the past.
Which, in Nigeria’s volatile economy, is the one bet you can’t afford to make.
