Seven of Africa’s top 20 fastest-growing companies are fintechs. Here’s the AI playbook behind that growth—and how Cameroon can apply it in 2026.
Africa’s Fastest-Growing Fintechs: The AI Playbook
Seven of Africa’s top 20 fastest-growing companies are fintechs. That’s not hype—it’s a scoreboard. A recent ranking of the continent’s fastest growers (measured by revenue CAGR from 2020–2023) shows fintech taking 35% of the top 20 and placing 14 fintechs among the wider list.
Here’s the part that matters for Cameroon: these growth rates don’t come from “more ads” or “more branches.” They come from mobile-first distribution + data. And in 2025, the most practical way to turn mobile data into growth is AI—especially for customer engagement, risk decisions, fraud control, and automated marketing.
This post sits inside our series on how AI is transforming telecommunications and fintech in Cameroon. I’ll use the African fintech growth numbers as the headline, then break down the AI tactics behind the winners—and what Cameroonian telcos, mobile money teams, and fintech operators can apply in 2026.
What the fastest-growing fintechs have in common
Answer first: The fastest-growing fintechs scale when they can acquire customers cheaply, trust users quickly, and monetize repeatedly—without human-heavy operations. AI helps with all three.
Across the top performers (payments, digital lending, neobanking, merchant services), you see the same operating model:
- Mobile-first onboarding that minimizes friction (fewer steps, faster verification)
- Agent and merchant networks that push distribution to the edge
- Always-on engagement (notifications, in-app prompts, WhatsApp/SMS journeys)
- Data-driven pricing and risk that adapts as users behave
The ranking highlights fintechs growing revenue at 151% to 583% per year. That’s the pace you get when your product is “software + distribution,” not “paper + queues.”
For Cameroon, the parallel is obvious: mobile money is already a daily habit. The next growth wave comes from AI-driven personalization, smarter fraud controls, and credit decisions that work for informal and semi-formal customers.
The growth numbers are real—so is the AI behind them
Answer first: When revenue grows 10x–100x in a few years, manual decision-making collapses. AI becomes the only scalable way to manage risk, marketing, and support.
A few standout datapoints from the fastest-growing group show what “scale” actually means:
- A leading payments-and-neobanking player grew from US$200k (2020) to US$63.9m (2023) while claiming 35m+ users and up to 15m transactions per day.
- A major merchant payments platform processes 1b+ transactions monthly and serves 10m businesses and individuals.
- Digital lenders and MSME financing apps are approving unsecured credit fast enough that the experience feels like “tap → money,” not “forms → waiting.”
To run businesses like that, teams typically apply AI in four places:
1) AI for customer acquisition and lifecycle marketing
Answer first: The cheapest customer is the one you retain, and AI is how you decide who to message, when, and with what offer.
High-growth fintechs don’t blast generic promos. They run automated journeys based on behavior:
- New user deposits for the first time → prompt bill pay setup → then savings nudges
- Merchant receives a spike in transaction volume → pre-approve working capital offer
- User shows churn signals (stops opening app, reduced transactions) → win-back flow
In Cameroon, this is where telcos and fintechs can collaborate aggressively: telcos have reach and messaging rails; fintechs have product triggers. AI sits in the middle to select:
- next best action (what to offer)
- next best channel (SMS, WhatsApp, push, USSD)
- best time to send (based on response patterns)
A practical stance: if your marketing team still relies on “monthly campaign calendars,” you’re leaving revenue on the table.
2) AI for underwriting in a mobile-first, informal economy
Answer first: AI underwriting works best when it uses alternative signals that reflect real behavior, not just bank statements.
Cameroon’s credit gap isn’t about demand—it’s about missing documentation. The fastest-growing lenders in Africa typically build models on signals such as:
- transaction patterns (frequency, stability, seasonality)
- merchant sales velocity (for MSMEs)
- repayment micro-behaviors (partial payments, timing)
- device and account integrity signals (to reduce identity abuse)
This isn’t “AI for AI’s sake.” It’s how you safely approve more customers—especially those who are excluded by classic credit scoring.
If you’re a Cameroonian fintech operator, the non-negotiable is governance: you need clear policies on what data is used, how it’s explained, and how customers can appeal decisions. Fast growth with opaque models creates regulatory and brand risk.
3) AI for fraud detection and trust at scale
Answer first: Trust is a growth feature. AI fraud systems reduce losses without blocking legitimate customers.
When transaction counts climb into millions per day, fraud patterns change weekly. Rule-based systems alone can’t keep up. High-growth platforms combine:
- anomaly detection (unusual transaction graphs)
- device fingerprinting and behavior biometrics
- risk-based step-up verification (challenge only when needed)
- network analysis (links between accounts, agents, devices)
This matters for Cameroon because mobile money and agent ecosystems can be targets for social engineering, SIM swap attempts, and mule-account behavior. The goal isn’t “zero fraud”—it’s fraud controls that don’t punish good users.
4) AI for support, collections, and operations
Answer first: AI reduces cost-to-serve, which lets fintechs price products more competitively.
As fintechs grow, support and collections can become the profit killer. The most scalable operators automate:
- first-line customer service with multilingual chatbots (and fast human escalation)
- ticket triage (classify issues, route to the right team)
- repayment reminders personalized to ability-to-pay signals
In Cameroon, multilingual support isn’t a “nice-to-have.” It’s part of retention. If your customer gets stuck and can’t resolve an issue quickly, they don’t complain—they churn.
What Cameroon can learn from the top performers (without copying them)
Answer first: Cameroon doesn’t need the same products as Nigeria or South Africa; it needs the same growth mechanics: distribution, trust, and repeatable engagement.
The African leaders in the ranking span different models—payments apps, merchant POS ecosystems, earned wage access, MSME working-capital lending, and retailer supply platforms. The unifying pattern is repeat transactions.
Here’s what I’d prioritize for a Cameroonian fintech or telco-fintech partnership going into 2026:
Build around daily-use payments, then attach credit
Payments create data, and data makes credit safer. Start by owning:
- merchant payments and reconciliation
- bill pay and airtime/data purchases
- P2P transfers and savings habits
Then attach:
- short-term working capital for merchants
- salary-linked advances where payroll partnerships exist
- inventory financing tied to merchant sales
Treat telco rails as a growth engine, not just a channel
Telcos can contribute more than USSD. When structured well, telco collaboration provides:
- identity and SIM tenure signals (for risk)
- messaging reach for lifecycle campaigns
- agent networks for cash-in/cash-out and onboarding
The strongest teams set this up as shared KPIs: activation rate, 30-day retention, fraud loss rate, and customer support resolution time.
Design for December and “back-to-school” seasonality
We’re writing this in late December 2025, and seasonality is a real growth lever. Transactions spike around:
- end-of-year travel and gifting
- school fee periods
- holiday merchant activity
AI helps here by forecasting demand and staffing support, but also by adjusting fraud thresholds (attackers like peak seasons) and targeting merchant credit offers at the right time.
A practical AI checklist for Cameroonian fintech teams
Answer first: If you want growth like the continent’s fastest fintechs, implement AI in a sequence that improves revenue and reduces risk—not as a random “AI project.”
Here’s a clean order of operations that I’ve found works:
- Instrument your product: event tracking for onboarding steps, failed KYC attempts, transaction drop-offs, churn signals.
- Segment users with simple models first: rule-based cohorts are fine to start; graduate to ML when data volume is stable.
- Launch automated lifecycle journeys: onboarding, activation, retention, reactivation. Keep message frequency controlled.
- Add fraud scoring before adding aggressive growth: scaling acquisition without fraud controls is expensive.
- Pilot credit with narrow use cases: merchants with consistent sales, repeat customers with stable behavior.
- Measure model outcomes like a business: approval rate, default rate, false positives in fraud, support deflection, retention lift.
A line I repeat to teams: AI isn’t the strategy. AI is the system that keeps the strategy running when volume hits.
People also ask: “Is AI worth it for smaller fintechs in Cameroon?”
Answer first: Yes—if you focus on narrow, high-impact workflows and don’t overbuild.
Smaller teams get the biggest wins from:
- AI-assisted customer support (ticket categorization + chatbot)
- churn prediction for high-value users (who needs intervention)
- fraud anomaly alerts (even basic models beat static rules)
The mistake is trying to build a full in-house “AI lab” before you have clean data and stable product funnels. Start with one workflow, prove ROI, then expand.
Where this goes next for telecoms and fintech in Cameroon
Africa’s fastest-growing fintech companies show what happens when digital finance meets execution discipline. The numbers—seven fintechs in the top 20, revenue growth as high as 583.6% per year—aren’t a curiosity. They’re a signal that customer expectations have shifted permanently toward speed, convenience, and personalization.
For Cameroon’s telcos and fintechs, the next advantage is simple: use AI to make mobile money smarter—smarter engagement, smarter risk, smarter support. That’s how you grow without burning cash on acquisition or losing trust to fraud.
If you’re planning your 2026 roadmap, pick one high-friction journey (onboarding drop-off, merchant activation, collections, or fraud losses) and design an AI-assisted fix. Then measure it like your business depends on it—because it does. What would change in your growth numbers if your customers got help in under 60 seconds and the right offer in under 24 hours?