Remittances First: Fintech Lessons for Ghana’s MoMo

DRC has a statistic that should make every fintech operator in Ghana sit up: over 80% of Congolese adults have never held a bank account. Yet money still moves every day—through traders, agents, and remittance corridors. That’s exactly why a Nigerian fintech, Nomba (previously valued at over $150 million), is entering the DRC through remittances first rather than launching with “full digital banking” on day one.

This matters for our series, “AI ne Fintech: Sɛnea Akɔntabuo ne Mobile Money Rehyɛ Ghana den”, because Ghana is already ahead on mobile money adoption—but we still struggle with the same stubborn realities: cash-out culture, trust gaps, fraud pressure, and MSMEs that want credit but can’t show clean data. Nomba’s DRC play isn’t just a Congo story. It’s a blueprint for how AI-powered fintech can use the money that already flows (remittances) to build trust, rails, and eventually deeper financial services.

Why “remittances first” works in cash-heavy markets

Remittances are the easiest trust-building product in a distrustful system. People don’t adopt financial products because you built an app; they adopt because the product solves a high-frequency pain point without embarrassing failure. In the DRC, Nomba’s team is betting that remittances—especially for traders connected to high-volume corridors like China and Dubai—offer a daily, measurable need.

The logic is practical:

• Remittances already have demand (you’re not trying to “create a habit”).
• Transactions happen repeatedly, so the customer learns to trust the rails.
• Agent networks get immediate volume, so they stay motivated.
• Compliance and monitoring get real data quickly, instead of theoretical risk models.

Nomba’s Congo manager describes the strategy as earning “transactional trust” before layering payments and credit. I agree with that sequencing. Most companies get this wrong by launching with an ambitious product bundle and then wondering why adoption stalls.

The Ghana connection: remittance corridors are underused as “rails”

In Ghana, we often treat remittances as a standalone service—someone receives money, then cashes out. The smarter play is to treat remittances as the start of a customer journey:

1. Receive remittance into a wallet
2. Keep value digitally (even partially)
3. Pay bills, suppliers, or savings goals
4. Build a transaction history
5. Unlock merchant tools and credit scoring

If you’re building in Ghana, don’t just chase “more remittance volume.” Chase remittance-to-wallet retention and remittance-to-merchant payments.

Agents are still the product (and AI should serve them)

In the DRC, people prefer in-person assurance. Nomba is recruiting physical agents to handle inflows, and the company admits its biggest operational challenges are trust and liquidity. That’s not a side note—it’s the core of scaling any cash-to-digital bridge.

Ghana’s mobile money ecosystem already proves the point: agent networks are the distribution engine. But agents are also where things break—float shortages, downtime, fake alerts, social engineering, customer disputes, and inconsistent KYC practices.

Where AI ne fintech fits: agent operations, not just chatbots

When people hear “AI in fintech,” they jump to customer service. That’s fine, but the real wins come from operational intelligence. Here are AI use cases that map directly to what Nomba is facing in the DRC—and what Ghana faces daily:

• Float prediction for agents: forecast cash/e-float needs by day-of-week, salary cycles, market days, and seasonality (December is a perfect example).
• Anomaly detection for fraud: flag unusual cash-in/cash-out patterns or rapid circular transfers common in scam chains.
• Smart routing for settlement delays: when bank settlement is slow, AI can recommend alternative settlement paths, partner banks, or liquidity hubs.
• Agent quality scoring: use transaction success rates, complaint ratios, and reversal patterns to identify training needs or risky behavior.

A blunt truth: if your agent network is bleeding trust, your app UI won’t save you.

What Nomba is really buying with remittances: data and permission

The DRC is mobile-money-driven, but many users withdraw immediately after receiving funds. That pattern shows a lack of trust and limited utility. Nomba’s stated plan is to start with remittances, then later add payments and credit.

Here’s what’s quietly powerful about that approach: remittances give you repeated, high-signal behavioral data—who receives money, how often, at what value, and through which agents. With the right permissions and compliance, that data becomes the foundation for responsible credit and merchant tools.

Translating this into Ghana’s MSME problem

Ghana’s MSMEs often can’t access credit because they lack formal records, not because they’re bad businesses. A remittance-first (or inflow-first) strategy can build alternative underwriting signals:

• Stability of inflows over 90–180 days
• Concentration risk (one sender vs many)
• Cash-out ratio (how much stays digital)
• Merchant payment behavior (supplier payments, bill payments)
• Seasonality patterns (school fees, Christmas trading)

AI makes this practical by turning raw transactions into predictive risk models—but only if the fintech earns customer trust first.

A reliable inflow history is more useful than a beautiful onboarding flow.

Competition is real—so differentiation has to be operational

Nomba is entering a market with:

• Banks with deep pockets, including Nigerian banks expanding into the DRC
• Four major mobile money operators with significant revenue
• A fast-growing agent race (one bank reportedly plans to reach 100,000 agents over the next few years)

That situation should sound familiar to Ghanaian fintech builders. Ghana’s mobile money space is mature, and customer switching costs are low. Agents are often non-exclusive. Users will keep multiple wallets. So “we’re cheaper” won’t hold for long.

The differentiation stack Ghanaian fintechs should copy

If you want a durable advantage, build in layers:

1. Reliability: uptime, fast confirmations, fewer failed transactions
2. Liquidity: fewer “no cash” moments for agents and customers
3. Trust: transparent dispute handling, clear receipts, consistent reversals
4. Usefulness: bills, merchant tools, payroll features, invoice collection
5. Intelligence: AI-driven fraud controls and personalized nudges

Nomba’s bet on “better product experience” for agents and end-users is the correct direction. But “experience” isn’t vibes. It’s measurable.

If you’re operating in Ghana, track metrics like:

• Transaction success rate by corridor and by agent
• Time-to-cash-out (or time-to-complete) for inbound remittances
• Dispute resolution time
• Fraud loss rate per 10,000 transactions
• Wallet retention (percentage not cashed out within 24 hours)

Regulation: growth without compliance is just a future shutdown

Nomba entered the DRC by partnering with banks and aligning with central bank expectations, KYC rules, and transaction monitoring. That’s not bureaucracy—it’s survival.

For Ghana, the lesson is straightforward: design compliance into the product, especially if you’re using AI.

Practical compliance patterns for AI-powered fintech in Ghana

• Risk-based KYC: simpler onboarding for low-risk tiers; stronger verification for higher limits.
• Explainable AI for flags: when you freeze or delay a transfer, you need a reason a human can review.
• Audit trails by default: every automated decision should be reconstructable.
• Model governance: retrain models carefully; document changes; test for bias and drift.

AI can reduce risk, but sloppy AI creates a different risk: unfair denial, false positives, or regulatory headaches.

A December reality check: seasonal volume is where systems break

We’re in late December 2025. Across Ghana, this is peak season for:

• diaspora inflows
• church conventions and events
• retail and market trading
• family support transfers

This is also when fraud spikes and agent liquidity is stressed. If you want to apply the “remittances first” lesson immediately, start here: prepare for seasonal volume as a product feature, not an operational surprise.

AI helps most during peak season because it can:

• forecast demand spikes by location
• detect new fraud patterns faster than rule-only systems
• prioritize support tickets and disputes based on value and risk

What Ghana can take from Nomba’s DRC strategy (actionable steps)

If you’re building or managing a fintech or mobile money product in Ghana, here’s a practical translation of the DRC playbook:

1. Pick one corridor and dominate it (diaspora city → Ghana region → agent clusters). Depth beats breadth early.
2. Invest in agent liquidity tooling before adding shiny features. If cash-out fails, trust dies.
3. Use AI to reduce fraud and failed transactions, not to add “smart” marketing copy.
4. Convert inflows into utility: bill pay, school fees, merchant payments, micro-savings.
5. Treat compliance as product design: clear KYC tiers, strong monitoring, fast human review.

If you only remember one line, make it this: Follow the money that already moves, then earn the right to offer more.

The bigger question for Ghana’s ecosystem—banks, telcos, fintechs, and regulators—is whether we’ll keep treating remittances as “cash that passes through,” or start treating them as the first step toward stronger digital financial lives.

Where do you think Ghana’s next big inclusion push will come from: smarter agent networks, better credit scoring with AI, or remittance-led merchant payments?