Contactless & Tokenisation: Ghana’s Next Fintech Win

Verve just crossed 100 million cards issued across Africa—and instead of celebrating quietly, they’re doubling down on two things that actually matter for day-to-day payments: contactless tap-to-pay and tokenisation. That combo is a strong signal about where African fintech is headed next.

Here’s my take: cards aren’t “old fintech.” Cards are infrastructure. When a card scheme at Verve’s scale starts prioritising contactless and tokenisation, it’s not a side upgrade—it’s a foundation for what comes next: AI-driven fraud controls, automated reconciliation, smarter merchant tools, and cleaner mobile money integrations.

This post sits inside our series, “AI ne Fintech: Sɛnea Akɔntabuo ne Mobile Money Rehyɛ Ghana den”—because the future of Ghana’s payments ecosystem won’t be built by mobile money alone or cards alone. It’ll be built by interoperability + security + automation.

Why Verve’s 100M cards matter for Ghana’s fintech path

Answer first: Verve’s milestone matters because it proves mass adoption of digital payment rails is already happening in Africa—and Ghana can build smarter AI-powered services on top of similar rails.

A lot of fintech conversations in Ghana focus on mobile money (rightly so). But there’s another reality: customers increasingly expect choice—MoMo today, card tomorrow, QR the next day, and a tap-to-pay experience when they’re in a hurry.

Verve’s growth came from partnerships with banks and fintechs and showed usage across:

• ATM withdrawals
• POS transactions
• Online purchases
• Mobile payments

That mix is important. It signals that modern users don’t separate “card behavior” from “mobile behavior.” They just want to pay.

The Ghana connection: rails first, intelligence second

Ghana’s payment ecosystem already has key building blocks: mobile money adoption, increasing POS distribution, better APIs, and improving interoperability. What often lags is the intelligence layer:

• detecting fraud faster
• reconciling transactions automatically
• forecasting float and cash-out demand
• identifying merchant performance issues early

That’s where AI in fintech becomes practical—not hype.

Contactless payments: speed is the feature people feel

Answer first: Contactless wins because it reduces payment friction at the exact moment customers decide whether to pay digitally or switch to cash.

Contactless (tap-and-go) sounds like a small convenience until you watch a queue build up at a busy merchant. The customer experience difference is obvious:

• less time at checkout
• fewer “network is slow” complaints (because the process is shorter)
• improved throughput for merchants during peak hours

And December is peak reality. In Ghana, the final weeks of the year are a stress test: detty December spending, events, travel, last-minute shopping, family support transfers—payments volume climbs, and patience drops.

Where contactless can meaningfully help Ghanaian merchants

Contactless payments become especially valuable for:

1. Quick-service food spots (speed matters more than anything)
2. Pharmacies and convenience retail (high-frequency, low-to-mid ticket)
3. Transport and ticketing (time pressure + repetition)
4. Events and pop-up vendors (temporary setups need fast, reliable flow)

But contactless adoption only works when acceptance is reliable. Ghana’s real challenge isn’t explaining “tap”—it’s ensuring the ecosystem has:

• enough contactless-ready terminals
• merchant training that sticks
• dispute handling that doesn’t feel like punishment

Tokenisation: the security upgrade most users won’t notice (and that’s good)

Answer first: Tokenisation protects customers by replacing sensitive card details with a substitute value (a token), reducing fraud impact even if data is exposed.

Tokenisation is one of those security changes that customers rarely celebrate—because when it’s done well, nothing happens. And “nothing happens” is the goal: fewer fraudulent transactions, fewer compromised details, fewer scary SMS alerts.

In plain terms, tokenisation means:

• your real card number isn’t repeatedly exposed in online payments
• merchants store less sensitive data
• attackers get less useful information, even if they break in

Why tokenisation is also a mobile money story

Here’s the bridge that matters for this series: tokenisation isn’t only for cards.

The same security mindset applies to mobile money and wallet ecosystems:

• masking sensitive identifiers
• using one-time credentials for specific transactions
• limiting how much raw payment data flows through multiple systems

If you’re building or operating AI-enabled fintech tools in Ghana (like automation around reconciliation, collections, or payouts), tokenisation is a gift. It lets systems do their work without exposing raw sensitive data everywhere.

Security that reduces data exposure is the best kind of security—because it limits damage even when something goes wrong.

AI + tokenisation + contactless: what “modern fintech” actually looks like

Answer first: Contactless and tokenisation create cleaner, safer transaction data—AI then uses that data to automate ops, detect fraud, and improve customer experience.

People often talk about AI in fintech like it’s a chatbot answering questions. That’s the smallest use case. The bigger wins are operational and risk-related.

1) AI-driven fraud prevention that adapts in real time

When tokenisation reduces exposure and contactless reduces friction, fraud patterns shift. AI becomes useful because it can:

• detect unusual merchant velocity (sudden spike in value/volume)
• flag device/location anomalies
• catch “low-value testing” patterns before a major hit
• learn normal customer behaviors faster than static rules

A practical stance: rules alone won’t keep up with fast-changing fraud tactics. You need AI-assisted monitoring.

2) Automated reconciliation for merchants and fintech operators

Ghana’s merchants don’t just want to accept payments—they want clean books.

AI-supported reconciliation can:

• match POS settlements to sales in near real time
• identify missing settlements earlier
• auto-generate daily summaries per branch
• classify transactions by channel (card, wallet, bank transfer)

This is exactly where platforms like Sɛnea (within the theme of this series) can add value: automation that makes payment operations less chaotic.

3) Smarter credit and cash-flow decisions

When transactions become more reliable and data quality improves, AI can help with:

• merchant cash-flow forecasting
• inventory planning signals
• better underwriting using behavioral patterns (not just static history)

That’s how you build financial inclusion that isn’t based on guesswork.

What Ghanaian fintech teams should do next (practical checklist)

Answer first: The next step is operational: upgrade acceptance, reduce data exposure, and build AI around real payment pain points.

If you’re a fintech operator, a bank product team, or a growing merchant network in Ghana, these actions pay off quickly:

A. Treat contactless as an operational KPI, not a marketing feature

• Audit how many deployed terminals are contactless-ready
• Track “tap success rate” vs. fallback (chip/swipe)
• Retrain merchants where tap failures come from process errors

B. Reduce your sensitive data footprint aggressively

• Map where card/wallet identifiers are stored across systems
• Minimise raw PAN-like storage patterns
• Use tokens internally for analytics workflows where possible

C. Build AI where the money leaks: fraud, disputes, and settlement gaps

Start with boring, high-impact use cases:

1. Fraud anomaly detection (alerts + automated holds)
2. Chargeback/dispute triage (categorise, prioritise, recommend actions)
3. Settlement reconciliation (match, flag gaps, auto-report)

D. Design for interoperability between cards and mobile money

Most customers don’t care which rail you use. So your product shouldn’t trap them.

• enable multi-rail checkout experiences
• unify transaction history across channels
• standardise merchant reporting across MoMo and card payments

People also ask (and the direct answers)

Is tokenisation the same as encryption?

No. Encryption protects data by transforming it into unreadable form, while tokenisation replaces sensitive data with a non-sensitive token. They can be used together.

Does contactless increase fraud risk?

Not by default. Contactless can be safe when combined with limits, monitoring, and strong back-end risk controls. Tokenisation and AI monitoring strengthen the safety net.

Will cards replace mobile money in Ghana?

No. Ghana’s likely outcome is multi-rail payments: mobile money for many everyday transfers, cards for acceptance ecosystems, and both connected through smarter fintech layers.

The bigger picture for “AI ne Fintech” in Ghana

Verve’s 100 million cards milestone isn’t just a Nigeria story. It’s a signal that African consumers are adopting digital payments at scale, and they increasingly expect speed and safety as the default.

For Ghana, the opportunity is clear: pair contactless acceptance with tokenisation-grade security, then add AI automation to reduce fraud, reduce manual work, and give merchants cleaner visibility over their money.

If you’re building in this space, the most useful question isn’t “Should we add AI?” It’s this: Which payment pain are you eliminating first—fraud, reconciliation, or checkout friction?