Africa’s Fastest-Growing Fintechs: Lessons for Cameroon

Seven of Africa’s 20 fastest-growing companies are fintechs. That’s not a vibe or a trend—it's a measurable signal that payments, digital lending, and mobile-first banking are where Africa is scaling revenue the quickest.

The numbers behind that signal are hard to ignore: the Financial Times and Statista ranking (based on revenue CAGR from 2020–2023) shows fintech firms growing between 151.2% and 583.6% annually. PalmPay alone went from US$200,000 in revenue in 2020 to US$63.9 million in 2023.

If you’re building or running a fintech, mobile money business, or telco-led financial service in Cameroon, this matters because the path to growth is becoming clearer: mobile distribution + trust + operational automation, with AI increasingly sitting underneath all three. And as we close out December 2025—when budgets reset and product roadmaps get approved—this is the right moment to decide what you’ll automate, measure, and ship in Q1.

Why fintech is dominating Africa’s growth rankings

Fintech dominates because it scales with software but earns with transactions. That combination is rare. In many African markets, financial services demand is huge, traditional banking penetration is uneven, and mobile rails (USSD, apps, agent networks) already exist.

The FT/Statista list ranks the 130 fastest-growing African companies by revenue compound annual growth rate (CAGR) from 2020 to 2023. Across that list:

• 26 companies come from fintech, finance, and insurance
• 14 are fintechs, representing 10.8% of the whole ranking
• 7 fintechs land in the top 20, representing 35% of the top 20

The simplest explanation is also the most useful one: fintech revenue is tightly linked to usage. If you can acquire users cheaply and keep fraud low, revenue growth follows.

For Cameroon specifically, the implication is direct: the market doesn’t need “more apps.” It needs more trusted rails—and rails run on telecom infrastructure, smart risk controls, and fast customer support. That’s where AI shows up.

What the top fintech performers are doing differently (and what AI has to do with it)

The shared playbook is operational intensity at scale. These companies are not growing because they post more on social media. They’re growing because they can process more transactions, underwrite more loans, onboard more merchants, and resolve more customer issues without their cost base exploding.

Here’s what stands out from the seven fintechs in Africa’s top 20, and the AI-adjacent capabilities that typically power these outcomes.

Payments + agent distribution: PalmPay and Moniepoint

Payments winners build distribution first, then expand into financial products.

• PalmPay (Nigeria, #2) reported 583.6% annual revenue growth, scaling from US$200,000 (2020) to US$63.9M (2023). It claims 35M+ app users and up to 15M transactions daily.
• Moniepoint (Nigeria, #16) posted 160.3% annual revenue growth, growing revenue from US$15M (2020) to US$264.51M (2023), and processes 1B+ transactions monthly.

AI typically supports this model in four practical ways:

1. Fraud detection in real time (pattern recognition across devices, agents, transaction velocity)
2. Merchant/agent risk scoring (flagging unusual cashout patterns and synthetic identities)
3. Customer support automation (triage, self-serve issue resolution, chargeback workflows)
4. Smart segmentation (predicting who will adopt savings, credit, or insurance next)

Cameroon parallel: if you’re riding mobile money or building a wallet, the fastest growth lever is usually not another feature—it’s lower failed transactions, fewer reversals, and faster dispute resolution. AI helps because it reduces the human workload in high-volume operations.

Digital lending: Numida and eShandi

Lending leaders win by underwriting the “invisible” customer. MSMEs and informal businesses often have thin credit files. That doesn’t mean they’re uncreditworthy; it means they’re under-measured.

• eShandi (Zambia, #4) recorded 276.4% annual revenue growth, and positions itself around last-mile inclusion with digital loans and agency banking. It says it has served 1M+ individuals and SMEs.
• Numida (Uganda, #17) posted 151.2% annual revenue growth, providing unsecured working-capital loans via mobile app with fast underwriting and mobile wallet disbursement.

AI’s role in lending is not “magic approvals.” It’s disciplined prediction and controls:

• Alternative data underwriting (cashflow proxies, merchant behavior, repayment patterns)
• Collections intelligence (best time/channel to contact, repayment likelihood modeling)
• Early warning systems (detecting distress before default through behavior change)

Cameroon parallel: the winners in digital credit will be the ones who treat underwriting as a product, not a policy document. If your credit team can’t explain why the model approves or declines, regulators and partners will eventually force a reset.

Embedded finance for retailers: Chari

B2B retail platforms scale because they sit inside daily commerce.

• Chari (Morocco, #14) grew revenue from US$4.04M (2020) to US$74.7M (2023) with 164.4% annual revenue growth, serving traditional retailers and extending microloans.

In practice, this is a data flywheel: frequent orders and delivery patterns become signals for working-capital credit. AI supports:

• Demand forecasting for inventory and delivery
• Dynamic credit limits based on observed turnover
• Pricing optimization for merchant financing

Cameroon parallel: think beyond “merchant QR.” Merchants care about stock, cashflow, and reliability. The fintech that wraps payments + supply + credit becomes sticky.

Earned wage access (EWA): Paymenow

EWA grows when it’s safer than payday lending and easier than HR payroll changes.

• Paymenow (South Africa, #6) posted 237.8% annual revenue growth, offering employees access to earned wages plus savings and financial wellness tools.

AI tends to help here via:

• Anomaly detection in wage access patterns
• User nudges that increase savings behavior and reduce churn
• Support automation (EWA products generate high-volume, repetitive questions)

Cameroon parallel: EWA is a quiet opportunity in sectors with predictable payroll (retail chains, security firms, call centers). It requires strong compliance posture, clear pricing, and a customer support system that doesn’t collapse on payday.

What Cameroon can copy immediately (even without a huge AI budget)

You don’t need a massive research team to use AI in fintech operations. Most practical wins come from applied automation and better data discipline.

Here are five moves I’d prioritize for Cameroonian fintechs and telcos building financial products in 2026.

1) Build an “AI-ready” data foundation

If your data is messy, your models will be confidently wrong. Start with:

• A single customer identifier across channels (app, USSD, agent)
• Clean event tracking (failed tx, reversals, support tickets, KYC steps)
• A fraud and risk label taxonomy (what counts as confirmed fraud vs suspected)

This is unglamorous work. It’s also where speed comes from later.

2) Automate the top 20 customer issues first

Customer engagement in fintech is mostly customer support. In mobile money and wallets, the bulk of tickets tend to cluster around:

• “Transfer failed but wallet debited”
• “Cashout pending”
• “Wrong number”
• “KYC rejected”
• “Card/OTP issues”

A well-designed AI support layer can:

• Identify intent from short messages (English, French, Camfranglais patterns)
• Pull transaction context automatically
• Offer self-serve flows for reversals and status updates

This is where telcos in Cameroon have an advantage: they already run high-volume support operations and can operationalize automation faster than smaller startups.

3) Use AI to reduce fraud before you use it to “grow sales”

Fraud is a growth tax. When fraud rises, transaction costs rise, partner trust drops, and regulators pay attention.

Start with AI models (or rules enhanced with ML) that detect:

• Device and SIM swap anomalies
• Transaction velocity spikes
• Agent collusion patterns
• Synthetic identity clusters

The growth outcome is indirect but real: fewer losses means more room to invest in acquisition and better pricing.

4) Treat marketing as a conversion system, not content volume

Most fintech marketing fails because it measures reach instead of deposits, transactions, and retention. AI helps when it’s tied to revenue:

• Predict who will become active after signup
• Trigger onboarding sequences based on drop-off stage
• Personalize offers by behavior (not demographics)

If you’re in Cameroon’s mobile-first economy, SMS, WhatsApp, USSD prompts, and in-app messaging still outperform flashy campaigns—when they’re timed and targeted properly.

5) Build partnerships that match the telco-fintech reality

Cameroon’s fintech trajectory is inseparable from telecommunications. The strongest products will be the ones that integrate with:

• Mobile money rails
• Agent networks
• Merchant acquisition teams
• Device distribution channels

AI becomes the glue: it can unify customer insights, reduce operational load, and coordinate engagement across channels.

Common questions teams ask before adopting AI (and the straight answers)

“Should we build AI in-house or buy tools?”

Buy first, build later—unless AI is your core differentiator. Most teams should start with reputable tooling for support automation, analytics, and fraud monitoring, then bring models in-house once they have clean data and clear ROI.

“What’s the first AI use case that pays back quickly?”

Support automation + dispute triage usually pays back fastest because it reduces headcount pressure and churn at the same time.

“Will regulators accept AI-driven credit decisions?”

They’ll accept it when it’s explainable, auditable, and fair. If your team can’t document decision logic, monitor bias, and handle appeals, you’re creating future risk.

Where this is heading for Cameroon in 2026

The fastest-growing fintechs in Africa aren’t winning with hype. They’re winning with scale discipline: transaction reliability, risk controls, and customer engagement that doesn’t melt down when volume doubles.

For Cameroon, the opportunity sits right at the intersection of this series’ theme—AI + telecommunications + fintech. Telcos have reach and infrastructure. Fintechs have product speed. AI is what makes the combined system efficient enough to grow without breaking.

If you’re planning your 2026 roadmap, pick one operational bottleneck—fraud, disputes, onboarding drop-off, or collections—and automate it end-to-end. Then measure the result weekly. The teams that do this consistently won’t just keep up with Africa’s growth curve; they’ll help define it.

If your wallet can’t explain a failed transaction in 30 seconds, your customer will find another wallet in 30 minutes.

If you want a practical plan, start with a simple audit: Which three processes consume the most staff time per 10,000 transactions? That answer will tell you exactly where AI will pay for itself first.