Nigeria’s Top Fintechs: AI Lessons for Cameroon

Nigeria’s fintech scene isn’t big by African standards—it’s big by global standards. The country accounts for 28% of Africa’s fintech companies and captured roughly 36% of African fintech funding between 2020 and H1 2024. That concentration matters for Cameroon because it shows what happens when a mobile-first market combines payments infrastructure, agent networks, and relentless customer acquisition.

Here’s the part most teams miss: those numbers aren’t powered by “apps” alone. They’re powered by systems that learn—fraud engines that adapt, support channels that deflect repetitive questions, credit models that update weekly, and marketing that targets the right user at the right moment.

This post sits in our “How AI Is Transforming Telecommunications and Fintech in Cameroon” series, and the goal is simple: use Nigeria’s top fintechs as a practical mirror. What are they doing well? Where does AI actually fit? And what can Cameroonian fintechs and telecoms copy (without copying Nigeria’s exact market conditions)?

Nigeria’s top fintechs prove one thing: scale is operational, not cosmetic

Nigeria’s leading fintechs—OPay, Interswitch, Paga, Moniepoint, PalmPay, PiggyVest, FairMoney, Cowrywise, and Nomba—operate across different verticals. But they share a single obsession: high-volume execution.

When a platform processes billions in monthly transaction value or supports hundreds of thousands of agents and merchants, the bottlenecks are predictable:

• Identity and onboarding at scale (KYC, KYB)
• Fraud and risk controls that keep up with new patterns
• Customer support that doesn’t drown in tickets
• Credit decisions that don’t rely on slow manual reviews
• Merchant success workflows that don’t require a huge field force

AI in fintech isn’t a shiny add-on for these problems. It’s the only way to keep unit economics sane.

Cameroon’s equivalent reality: mobile money and digital payments are growing, but operational capacity (support, compliance, risk) doesn’t scale automatically. The fastest way to lose trust in a mobile-first economy is a fraud spike, an account lock with no resolution, or inconsistent agent liquidity. AI helps prevent that—if it’s deployed in the right places.

What Nigeria’s leaders do well (and where AI fits)

OPay and PalmPay: AI-driven customer engagement at mass-market volume

OPay reported 50+ million users and monthly transaction volume surpassing US$12 billion (as of 2024 claims). PalmPay reported 35 million registered users and a 500,000+ agent network, processing up to 15 million transactions daily.

At that scale, “customer engagement” stops meaning marketing slogans and starts meaning:

• Personalized in-app prompts that reduce failed transactions
• Intelligent routing to the right support channel (self-serve vs agent)
• Automated reminders tied to user habits (bill pay cycles, airtime patterns)
• Risk-based friction (when to add OTP, when to allow instant transfers)

Where Cameroon can copy the playbook:

1. Segment users by behavior, not demographics. “Salary earner,” “merchant,” “student,” and “diaspora recipient” are useful, but behavior wins. AI clustering on transaction sequences is often more predictive than age or location.
2. Local-language service automation. In Cameroon, this is a competitive edge because customer support is often bilingual by necessity (French/English) and sometimes needs Pidgin or local phrasing in informal channels. AI chat and agent-assist can reduce response times and keep tone consistent.
3. Reduce friction where trust is already high. A common mistake is adding the same controls to everyone. Mature fintechs use models to decide who gets extra steps.

Interswitch: infrastructure wins, but only if risk is intelligent

Interswitch’s strength is infrastructure—switching, processing, and broad merchant reach. It supports 8,000+ billers via Quickteller and has a Verve network with 70 million activated cards.

The AI angle here is less about “chatbots” and more about real-time anomaly detection:

• Detecting unusual merchant transaction patterns
• Identifying coordinated fraud attempts across channels
• Managing false positives so legitimate transactions don’t get blocked

Telecom-fintech overlap (Cameroon): telcos sit on network signals (device, SIM history, location stability) that can help fraud and onboarding decisions—if handled with strong privacy governance. Partnerships between telecoms and fintechs can improve risk scoring, reduce synthetic identities, and accelerate onboarding.

Moniepoint and Paga: agent networks are operational gold—and AI keeps them stable

Moniepoint claims 10 million businesses and individuals served and processes 1+ billion transactions monthly with total payments volume exceeding US$22 billion. Paga processed 335 million transactions totaling NGN 14 trillion (US$32 billion) and served 23 million users (as of 2024 reporting).

Agent and merchant networks win because they solve the last-mile trust problem. But they fail when:

• Float shortages become frequent
• Agents churn due to poor earnings predictability
• Fraud concentrates in a few “hot” locations
• Merchant support is slow

AI helps with:

• Liquidity forecasting: predict where float will run out, and when
• Agent health scoring: identify agents likely to churn and intervene early
• Geo-risk mapping: detect suspicious clusters by location and device patterns

Actionable idea for Cameroon: build a lightweight “agent cockpit” with three AI-powered scores:

• Float risk score (next 48 hours)
• Fraud risk score (last 7 days)
• Performance score (conversion, uptime, repeat customers)

That one dashboard can change how field teams prioritize visits and how operations allocate limited support capacity.

PiggyVest and Cowrywise: AI doesn’t replace trust—it manufactures consistency

PiggyVest claims 5 million users and reported reaching NGN 2 trillion (US$1.25 billion) in total payouts, with NGN 835 billion paid out in 2024 and a 53% YoY increase. Cowrywise claims 1,000,000+ users and operates as a regulated investment platform.

Savings and investing products live or die on consistency:

• Predictable user nudges
• Transparent performance reporting
• Frictionless deposits and withdrawals
• Minimal “surprises” in UX

AI here shows up as:

• Personalized saving plans based on income cadence
• Behavioral nudges that reduce withdrawals during short-term stress
• Customer support that explains products clearly and consistently

Cameroon-specific angle: many users treat mobile wallets as both bank account and emergency fund. A savings product that understands “school fees season” or “end-of-year family obligations” (hello, late December reality) can design nudges and lock features that respect local cashflow patterns rather than fighting them.

FairMoney: credit is where AI can help—or quietly destroy a brand

FairMoney reports 17 million app downloads, 5 million users, and 10,000 daily loan disbursements.

AI-based lending expands access, but it also creates reputational risk if the model is sloppy:

• Over-lending leads to defaults and aggressive collections
• Under-lending blocks good customers and slows growth
• “Black box” declines damage trust

My stance: if you can’t explain a loan decision in plain language, you’re not ready to scale it.

A practical approach for Cameroonian lenders:

• Use AI for ranking and risk bands, not absolute decisions at first
• Add human review for edge cases until you have enough data
• Provide a simple reason code: “insufficient repayment history,” “income volatility,” “unusual recent activity”

The Cameroon playbook: 6 AI use cases worth shipping in the next 90 days

Cameroon doesn’t need to “become Nigeria.” It needs to adopt what Nigeria’s winners already learned the hard way.

Here are six AI projects that are realistic, high-impact, and lead-friendly (they produce measurable results you can sell internally and externally):

1. Support deflection + agent-assist

   • Train on FAQs, policies, and transaction flows.
   • Goal: reduce first-response time and lower ticket backlog.

2. Fraud anomaly detection on transfers and cash-outs

   • Start with rules + anomaly scoring, then iterate.
   • Goal: fewer chargebacks, fewer account takeovers.

3. Smart onboarding (KYC triage)

   • Route users into “low risk” vs “needs review.”
   • Goal: faster activation without raising compliance risk.

4. Merchant/agent churn prediction

   • Look at inactivity patterns, failed transactions, float shortages.
   • Goal: retain distribution before it disappears.

5. Marketing segmentation based on behavior

   • Use clustering: airtime-heavy, bill-pay, cross-border recipients, merchant-like.
   • Goal: better conversion with less spend.

6. Network-aware experience for telecom-fintech bundles

   • Adapt flows for low bandwidth and device limits.
   • Goal: fewer drop-offs, higher transaction success.

A simple truth: in mobile-first Africa, the best product is the one that works on a bad connection and still resolves the user’s problem.

“People also ask” answers (the ones prospects bring to sales calls)

Is AI in fintech mostly about chatbots?

No. Chat is visible, so it gets attention. The bigger ROI usually comes from fraud prevention, onboarding automation, and risk scoring.

Can small Cameroonian fintechs use AI without huge budgets?

Yes—if they focus on narrow use cases. Start with one workflow (support, fraud flags, KYC triage) and measure impact weekly.

What’s the biggest risk when deploying AI in financial services?

Shipping models without governance. If you can’t audit decisions, handle complaints, and monitor drift, AI becomes a liability.

What to do next if you’re building in Cameroon

Nigeria’s top fintechs are a proof point: strong distribution plus high-frequency transactions creates massive value—but it also creates massive operational pressure. AI is how you absorb that pressure without breaking customer trust.

If you’re a Cameroonian fintech or telecom team planning 2026, I’d prioritize one AI project that reduces operational cost (support, KYC triage, fraud) and one that increases revenue (behavioral segmentation, merchant growth scoring). Shipping both will tell you more than months of strategy meetings.

Where do you see the biggest bottleneck right now in Cameroon—fraud, onboarding, agent liquidity, or customer support—and what would change if that bottleneck was cut in half?