Meet the top fintech VCs in Africa and what they look for in AI-driven fintech. Practical lessons for Cameroon’s mobile-first telco and fintech market.
Top Fintech VCs Backing Africa’s AI Payment Boom
African fintech took US$1.3 billion in equity funding in 2024—about 60% of the continent’s total—and still posted 131 deals (29% of all transactions). That dominance isn’t trivia. It’s a signal that investors are paying for one thing: distribution at scale in a mobile-first economy.
And distribution in 2025 increasingly means AI—not as a buzzword, but as the machinery behind fraud prevention, customer support, credit decisions, agent network growth, and the marketing automation that turns installs into loyal users.
This post is part of our series on How AI Is Transforming Telecommunications and Fintech in Cameroon. The angle here is practical: if you’re building (or partnering with) a fintech in Cameroon, understanding who funds African fintech and what they look for helps you design AI capabilities that attract capital, shorten sales cycles, and make telco partnerships easier.
Why top fintech VCs in Africa care about AI (even when they don’t say “AI”)
VCs don’t fund “AI.” They fund measurable outcomes—lower loss rates, higher approval rates, cheaper customer acquisition, faster support, better retention. In African fintech, AI is often the most direct route to those outcomes because:
- Fraud scales with growth. When mobile money usage grows, fraud attempts grow faster. AI-based anomaly detection and device intelligence quickly become non-negotiable.
- Manual operations collapse under volume. Human-only KYC review, customer service, and collections don’t survive 10× growth.
- Mobile-first customers expect instant answers. If a user can’t reset a PIN or confirm a transfer in 30 seconds, they churn.
- Agent networks need precision. AI helps decide where to recruit agents, how to price commissions, and how to prevent agent-side fraud.
For Cameroon specifically, this sits right on top of the telco-fintech overlap: mobile money rails, USSD onboarding, SIM registration realities, multilingual support (French/English + local languages), and the day-to-day economics of agent networks.
A simple truth: the fintechs that win funding are the ones that can grow without breaking. AI is how you grow without breaking.
The investor shortlist: who’s actively backing African fintech
A lot of founders waste time pitching the wrong firms. The faster move is to start with VCs that already have pattern recognition in African fintech—especially those that back seed and pre-Series A, where most Cameroonian startups realistically play.
Below are some of the most active fintech-focused investors operating across Africa (and often globally). I’m not listing them to name-drop. I’m listing them because their portfolios tell you what they reward.
Accion Venture Lab: inclusive fintech with a strong “unit economics” lens
Accion Venture Lab has US$475M+ in impact assets under management and a clear focus: fintech that reaches underserved users while still building a sustainable business.
What this means for AI: they’ll care about cost-to-serve and risk controls.
AI signals that fit their mindset:
- Automated underwriting for thin-file customers (with explainability)
- Customer support automation that reduces cost per active user
- Agent liquidity tooling that predicts float needs and reduces downtime
Flat6Labs and Disruptech: MENA-to-Africa momentum and real appetite for AI
Flat6Labs runs large seed programs and reports US$85M+ AUM, with fintech strongly represented. Disruptech is explicitly fintech-first and has backed major winners in Egypt.
Why it matters to Cameroon: North Africa investors increasingly look south when they see repeatable rails—payments, credit, regtech, embedded finance.
AI plays they tend to like:
- Fraud detection for insurance and payments
- AI-led onboarding/KYC flows that improve conversion
- Risk engines that can expand credit safely
Launch Africa Ventures: the “many bets” pan-African seed machine
Launch Africa Ventures invested US$31M into 133 startups across 22 countries since 2020, with a notable fintech count.
These funds often reward:
- Clear go-to-market motion
- Low burn with quick learning loops
- Founders who can show momentum in 90-day cycles
AI in this context isn’t about research; it’s about automation that moves metrics:
- Marketing personalization that reduces CAC
- Collections workflows that increase repayment
- Business dashboards that reduce churn for merchants
Flourish Ventures, Future Africa, Ventures Platform: operator-friendly capital
These firms are known for backing mission-driven fintech and supporting founders beyond the cheque.
Their portfolios reflect where AI is already showing up:
- API-first banking infrastructure
- Embedded finance platforms
- Digital banking for underserved users
For Cameroonian fintechs, that’s a reminder: investors love startups that can integrate with telcos, banks, and payment rails through clean APIs—and use AI to make those integrations profitable.
Microtraction, Voltron Capital, Ajim Capital: early cheques and strong taste for execution
If you’re early-stage, these are the kinds of funds that can be realistic targets because they play pre-seed/seed and care about speed.
Ajim Capital, for example, backs startups up to US$250K cheques with clear traction and a working product.
AI signals that help at this stage:
- A working fraud stack (even if simple) that prevents obvious losses
- A support assistant that reduces backlog and improves response time
- A basic scoring model that shows better-than-random risk separation
What this means for Cameroon’s telco + fintech reality
Cameroon is a mobile-first market where fintech success is tightly coupled to telco distribution. That changes how you should think about AI.
AI use case #1: fraud prevention that respects mobile money realities
Fraud in mobile money isn’t only “stolen cards.” It’s SIM swap attempts, social engineering, mule accounts, and agent-side abuse.
Practical AI building blocks:
- Device fingerprinting and session risk scoring
- Transaction anomaly detection (velocity, geography, network behavior)
- Merchant and agent risk tiers (dynamic limits and delayed payouts)
What VCs want to see: loss rate trends and proof you’re not buying growth by accepting fraud.
AI use case #2: multilingual customer engagement that actually reduces churn
If your support is slow, you’ll pay for it twice: in churn and in chargebacks.
A strong approach in Cameroon:
- Tier-1 chatbot (French + English) for repetitive issues: PIN reset, failed transfers, chargeback status
- Human handoff with full context
- Intent tracking to find product bugs faster
What VCs want to see: lower time-to-first-response, higher ticket resolution rate, and better retention cohorts.
AI use case #3: smarter credit in thin-file environments
Lending works when your risk engine is honest. The goal isn’t “approve more.” The goal is approve the right people.
AI inputs that are common in African fintech:
- Repayment behavior and wallet flows
- Merchant sales patterns (for SME credit)
- Airtime/data purchase consistency (when compliant and permitted)
What VCs want to see: stable repayment curves across cohorts and evidence you can tighten policy without killing growth.
AI use case #4: automated marketing that fits a telco distribution model
Most companies get this wrong. They pour money into acquisition and underinvest in lifecycle.
For telco-linked fintech growth, AI can drive:
- Next-best-action messaging (USSD prompts, in-app nudges, SMS)
- Offer optimization (what bundle, which segment, what timing)
- Merchant activation sequences (education + first transactions)
What VCs want to see: improving CAC payback and higher activation-to-retention conversion.
How to pitch AI to fintech VCs (and not get eye-rolls)
Investors have heard “we use AI” a thousand times. You win by being specific.
The pitch framework that works
Lead with outcomes, then mechanics.
- Problem + cost: “Fraud losses were 1.8% of volume; we reduced to 0.9%.”
- What changed: “We introduced real-time anomaly scoring and device risk checks.”
- Proof: Show before/after charts and a clear timeline.
- Moat: “Our model improves with our agent network data and transaction graph.”
Metrics that make VCs lean in
Pick 5–7 and track them obsessively:
- Fraud loss rate (% of volume)
- Approval rate vs. default rate (by cohort)
- Time-to-first-response and cost per ticket
- Activation rate (first meaningful transaction)
- 30/90-day retention
- CAC payback period
- Gross margin per user/merchant
If you operate in Cameroon, add a telco-friendly metric: USSD completion rate and drop-off points.
A realistic roadmap for Cameroonian founders (next 90 days)
You don’t need a giant AI team to get investable. You need repeatable processes and clean data.
Week 1–2: instrument everything
- Define events: signup, KYC step completion, first cash-in, first transfer, failed transfer
- Centralize logs for fraud and support
Week 3–6: automate the obvious
- Tier-1 support assistant with strict guardrails
- Rule-based fraud checks (velocity, IP/device reuse, agent anomalies)
Week 7–12: add models where they move money
- Simple risk scoring for credit or merchant limits
- Propensity model for marketing (who’s likely to activate next)
The best part: this roadmap also makes telco partnerships easier because you can show predictability and control, not just growth.
What to do next if you’re building in Cameroon
Top fintech VCs in Africa are backing companies that treat AI as an operating system for scale—fraud control, customer engagement, credit, and automation. Cameroon’s opportunity sits right at the intersection of telecommunications and fintech, where mobile distribution can move fast but only if operations are strong.
If you’re a founder or operator, your next step is simple: pick one high-impact AI use case (fraud, support, credit, or marketing), attach it to a hard metric, and improve that metric for 8–12 weeks. That’s the kind of evidence that gets meetings—and follow-on interest.
Where do you see the biggest bottleneck in Cameroon right now: trust (fraud), growth (marketing), or service (support)? Your answer should decide which AI investment you make first.