API-First Mobile Money: Lessons Ghana Can’t Ignore

25% of all M-PESA transactions now happen through APIs—not inside the consumer app. That single statistic should make every Ghanaian fintech founder, bank product lead, and MoMo aggregator sit up straight.

Because it confirms something many teams still underestimate: the next phase of mobile money growth isn’t happening on the front-end. It’s happening in the backend—inside business software, merchant systems, and automated workflows. And once transactions move into APIs, AI becomes far easier to apply at scale: fraud controls, smart routing, automated reconciliation, credit scoring, and customer support can all run as “invisible” services.

This post is part of the AI ne Fintech: Sɛnea Akɔntabuo ne Mobile Money Rehyɛ Ghana den series—where we focus on practical ways AI and modern infrastructure make Ghana’s fintech and mobile money operations faster, safer, and easier to run. Safaricom’s Daraja 3.0 upgrade is a strong case study for Ghana: it shows what happens when a mobile money platform treats developers as first-class customers.

What M-PESA’s 25% API share really means

It means businesses, not just individuals, are now driving a major chunk of transaction volume. When 1 out of every 4 transactions is executed via an API, you’re no longer talking about “people sending money to people.” You’re talking about payroll runs, merchant checkouts, ticketing platforms, loan repayments, utility payments, logistics collections, and government services—all wired directly into the rails.

Safaricom shared that M-PESA processes 100+ million transactions per day and can peak at 6,000 transactions per second (TPS). After core improvements, the platform is positioned to support up to 12,000 TPS, with a 10,000 TPS milestone targeted for January 2026. That scale matters for one reason: APIs don’t forgive downtime or inconsistent behavior. If your API is unreliable, every connected business breaks.

For Ghana, the lesson is blunt: mobile money is becoming infrastructure. And infrastructure only wins when it’s dependable, well-governed, and easy to integrate.

Why API growth is a big deal for AI in fintech

AI works best where data is structured and events are predictable. APIs create exactly that. Once transactions are flowing through APIs, you can:

• Detect fraud in near real time (pattern detection on transaction events)
• Automate reconciliation (match payments to invoices instantly)
• Trigger customer communications (smart SMS/WhatsApp notifications)
• Run smarter credit decisions (cashflow-based underwriting)
• Predict failures before they happen (anomaly detection on TPS, error rates, latency)

In other words: APIs are the pipes; AI is the intelligence you run through the pipes. If you skip the pipes and only “do AI,” your impact stays small.

Daraja 3.0: the boring upgrade that creates real growth

Safaricom upgraded Daraja (its M-PESA developer platform) to version 3.0 to reduce friction and increase speed of onboarding and rollout. That sounds like internal plumbing, but it’s how ecosystems scale.

Daraja already supports 66,000+ integrations and 105,000+ developers. When you’re operating at that level, the biggest enemy is rarely “competitors.” It’s:

• unclear documentation
• slow support escalation
• inconsistent governance
• onboarding delays
• unpredictable changes

Safaricom publicly acknowledged developer complaints about delays, documentation gaps, and inconsistent communication—and promised more transparent governance and better support.

I’m strongly in favor of this stance: if your platform depends on developers for growth, then developer experience is not a side project. It’s revenue infrastructure.

The hidden business model: developers are now your distribution

Here’s the reality behind the 25% API statistic: Safaricom doesn’t own all those product surfaces anymore. Businesses build the checkout pages, the payroll tools, the lending flows, the agent apps, the POS experiences. M-PESA provides the rails and trust.

That shift changes how a mobile money operator grows:

• Growth comes from making it easy to build
• Revenue comes from volume created by integrations
• Stickiness comes from businesses embedding you in operations

For Ghana’s ecosystem—telcos, banks, payment service providers, aggregators—the same dynamic is already unfolding. The winners will be the ones who treat the integration layer like a product, not “documentation on a PDF.”

What Ghana’s MoMo ecosystem should copy (and what to improve)

Ghana doesn’t need to copy Kenya’s market structure; it should copy the infrastructure mindset. API-first thinking is relevant anywhere mobile money is central to daily payments.

Below are practical, Ghana-focused takeaways you can apply whether you’re building a fintech product, managing a bank channel, or operating a payment gateway.

1) Build for peak season, not average days

December in Ghana is not a normal month. Consumer spending rises, events spike, merchant payments increase, and support queues swell. If your APIs only perform well on “average” days, you’ll lose trust during the exact period when people are most active.

A useful internal benchmark to adopt:

• define your peak TPS target (based on historical spikes)
• test for peak + buffer (at least 2× your current peak)
• measure not just uptime, but latency and error rates per endpoint

Safaricom’s TPS numbers are a reminder that scale isn’t a bragging right; it’s a planning discipline.

2) Treat API governance as risk management

When more transactions move via APIs, the platform’s risk surface expands:

• keys leak
• integrators mis-handle callbacks
• idempotency is ignored (double charges)
• error retries spam systems
• reconciliation breaks silently

That’s why Safaricom’s promise of clearer governance and escalation paths matters. Ghanaian platforms should formalize:

1. Versioning rules (no breaking changes without deprecation windows)
2. Credential hygiene (rotation, scopes, environment separation)
3. Incident communication (status pages, partner alerts, postmortems)
4. Dispute workflows (clear SLAs for reversals and charge disputes)

If you want AI-driven fintech automation, start here. AI can’t fix messy governance.

3) Fix onboarding: it’s your real “customer acquisition”

Most fintech teams obsess over marketing funnels. But in B2B payments, onboarding is the funnel. The time from “we want to integrate” to “we’re live” is what determines adoption.

Here’s what strong onboarding looks like in practice:

• sandbox keys in minutes, not days
• clean, tested sample code
• predictable KYC/KYB requirements for merchants
• a human escalation path that actually works
• dashboards for logs, webhooks, and transaction traces

Daraja 3.0’s focus on smoother onboarding is a clear admission: friction was costing volume. Ghanaian providers should assume the same.

Where AI fits: practical use cases once APIs are solid

AI in fintech becomes valuable when it reduces operational cost and prevents losses. Once your MoMo payments are API-driven, you can deploy AI in targeted ways that show results quickly.

AI use case #1: Fraud detection on transaction events

API transactions create structured event streams: amount, time, merchant, device, account, location hints, failure codes. That’s ideal for models that flag anomalies.

A practical approach many teams can execute:

• start with rules + anomaly detection (cheap, fast)
• graduate to supervised learning once you label outcomes (fraud/not fraud)
• keep a human-in-the-loop review queue

The win: fewer fraud losses and fewer “false declines” that annoy customers.

AI use case #2: Automated reconciliation for merchants and platforms

Reconciliation is where many Ghanaian businesses bleed time—especially SMEs managing MoMo sales across multiple channels.

With clean APIs and stable callbacks/webhooks, AI can:

• match payments to invoices even when references are messy
• detect missing callbacks and prompt requery
• categorize transaction types for accounting

This is exactly the kind of “akɔntabuo automation” that fits the series theme: AI makes the books less painful.

AI use case #3: Smart support and dispute handling

As API volume grows, support tickets shift from “I sent to the wrong number” to “callback not received” or “transaction stuck in pending.” AI can triage:

• classify incident type from logs + customer message
• suggest next action (requery, reversal path, escalation)
• detect widespread issues early by clustering similar tickets

But it only works if your platform has consistent error codes and traceable transaction IDs.

People also ask: API-first mobile money in plain terms

“Does API-first mean the app doesn’t matter?”

No. The consumer app still matters for acquisition and trust. But the largest growth in volume often comes from businesses embedding payments into their operations.

“What should a Ghanaian fintech measure to know if its API platform is healthy?”

Track these weekly:

• API uptime and p95 latency per endpoint
• webhook delivery success rate
• time-to-first-successful-transaction for new integrators
• dispute resolution SLA performance
• percentage of transactions via APIs vs app/USSD

“What’s the fastest way to prepare for AI in mobile money?”

Standardize your data and events. Clean APIs, strong logging, consistent references, and reliable webhooks create the dataset AI needs.

The stance Ghana should take in 2026

Ghana’s mobile money future will be decided by who builds the easiest rails for businesses—and who adds intelligence on top of those rails. Safaricom’s Daraja 3.0 story isn’t about a version number. It’s proof that once APIs become a major channel (25% and rising), developers become the growth engine and governance becomes non-negotiable.

If you’re building in Ghana’s fintech ecosystem, don’t wait until API transactions quietly become 25% of your volume before you get serious about developer experience, scaling, and automation. By then, your biggest customers will already be integrated somewhere else.

If you want your mobile money product to support AI-driven fintech solutions—fraud prevention, automated accounting (akɔntabuo), smarter lending, better merchant tools—start with the foundation: stable APIs, clear governance, and onboarding that doesn’t waste people’s time.

Where do you see the biggest friction in Ghana’s MoMo integrations right now: onboarding, reliability, disputes, or reconciliation—and what would you fix first?