M-PESA Daraja 3.0: API-First Blueprint for Ghana

About 25% of all M-PESA transactions now flow through APIs—not the consumer app. That single stat should make every Ghanaian fintech founder, bank product lead, and mobile money aggregator sit up straight. It means the “real” product is no longer only what customers tap on their phones; it’s the software plumbing that lets businesses embed payments into everything else.

Safaricom’s response was practical: upgrade Daraja (its developer portal and payments API platform) to Daraja 3.0, because the old way—slow onboarding, shaky documentation, unclear support channels—doesn’t survive when developers become part of your core operations.

This post is part of our “AI ne Fintech: Sɛnea Akɔntabuo ne Mobile Money Rehyɛ Ghana den” series. The point isn’t to admire Kenya from afar. It’s to pull out a clear model for Ghana: API-first mobile money is the foundation that makes AI automation in fintech actually work—fraud detection, smarter credit scoring, reconciliation, customer support, and real-time compliance.

Why “API-first mobile money” matters more than app features

API-first matters because businesses drive volume, and businesses need software-to-software reliability. When payments become a background action inside merchant POS systems, lending apps, logistics platforms, school fee portals, and public services, the user interface shifts. The payment experience is “invisible,” but the technical expectations are higher.

Safaricom shared scale numbers that clarify what’s at stake: M-PESA processes 100+ million transactions per day, peaks around 6,000 transactions per second, and its upgraded core is designed to support up to 12,000 TPS (with a 10,000 TPS milestone targeted for January 2026). That’s not marketing fluff. It’s a statement that mobile money is critical infrastructure.

Ghana’s mobile money ecosystem is already infrastructure too. If your platform is part of salary payments, micro-merchant collections, school payments, church offerings, transport, remittances, and agent networks, then downtime isn’t “a bad day.” It’s a national headache.

The myth to drop in Ghana: “APIs are for big tech companies”

APIs aren’t a fancy add-on. They’re how you:

• onboard merchants at scale without manual support queues
• automate reconciliation across banks, telcos, and aggregators
• power recurring payments for subscriptions and SME invoicing
• give fintech partners predictable, auditable transaction flows

Once APIs carry a meaningful share of transactions—as M-PESA’s 25% shows—developer experience becomes product experience.

Daraja 3.0’s real lesson: developer experience is operational risk

The strongest takeaway from Daraja 3.0 isn’t the version number; it’s the admission that friction hurts growth. Safaricom is upgrading because developer complaints were consistent: setup delays, documentation gaps, and messy communication.

If you’re building for Ghana, treat this as a warning label: when developers can’t integrate quickly, they don’t just get annoyed—they redesign their product roadmap around alternatives.

Here’s what “good” looks like for an API-first platform (and what Ghanaian providers should demand from themselves):

1) Fast, predictable onboarding

If onboarding requires multiple email threads, unclear compliance steps, and human gatekeeping, your sales pipeline becomes your bottleneck. A modern API program needs:

• self-serve test keys in a sandbox
• clear go-live checklist (KYC/KYB, security review, limits)
• transparent approval timelines and escalation paths

2) Documentation that matches reality

Most fintech teams don’t abandon integrations because the API is “hard.” They abandon it because docs are wrong, error messages are vague, or edge cases (timeouts, reversals, duplicate callbacks) aren’t addressed.

A practical standard is: if your support team has answered the same question three times, it belongs in docs with an example payload.

3) Support that treats integrators as partners

Safaricom signaled “more transparent governance and better support.” That’s overdue across many African fintech ecosystems. The reason is simple: once developers run a chunk of your transaction volume, support is a revenue-protection function, not a cost center.

APIs are the gateway to AI automation in fintech (Ghana edition)

AI in fintech doesn’t start with chatbots. It starts with clean, consistent, high-volume data flows. API-first infrastructure creates the event streams AI needs—transaction metadata, timestamps, merchant identifiers, device signals, reversal patterns, and customer behavior over time.

In Ghana’s mobile money context, here are high-impact AI use cases that become much easier when your APIs are solid.

AI use case 1: Fraud detection that reacts in seconds, not days

Fraud is pattern-driven. The faster you can detect patterns, the smaller the loss.

With an API-first platform, you can build risk checks around:

• velocity rules (too many transfers in a short window)
• abnormal amounts relative to customer history
• merchant anomalies (sudden spikes, refund loops)
• agent network outliers (cash-in/cash-out irregularities)

AI helps when rules get too complex. But AI needs structured data, stable identifiers, and consistent error handling. If callbacks fail randomly or references aren’t unique, you can’t train reliable models.

AI use case 2: Smarter credit scoring for micro and SME lending

Ghana’s digital lending is often limited by thin credit files. Transaction-based scoring fills that gap—if the data is trustworthy.

An API-first payments backbone makes it feasible to score based on:

• cashflow regularity (daily/weekly inflows)
• customer concentration risk (one payer vs many)
• seasonality (December spikes vs off-season lows)
• repayment behavior on previous advances

This aligns directly with our series theme: AI ne fintech can strengthen akɔntabuo (accounting) by turning payment history into usable financial intelligence.

AI use case 3: Automated reconciliation that finance teams actually trust

Ask any fast-growing fintech or merchant in Ghana what quietly eats time: reconciliation.

API-first systems enable automated matching using:

• consistent transaction references
• idempotency keys (so retries don’t create duplicates)
• webhook event logs (authoritative timeline)
• standardized reversal and dispute events

Once reconciliation is structured, AI can help classify exceptions (bank delay vs customer error vs fraud) and route them to the right queue.

AI use case 4: Customer support that resolves issues without “send screenshot”

A lot of mobile money support in West Africa still depends on screenshots and manual tracing. That’s a choice, not fate.

If your API platform logs every step—initiation, authorization, callback, settlement, reversal—support tools can:

• pull transaction status instantly
• detect missing callbacks
• trigger automated reversals when conditions are met

AI then becomes useful for triage and suggested resolutions, because the underlying data trail is complete.

What Ghanaian fintechs should copy (and what they should avoid)

Copy the “platform thinking,” not the telco dominance. M-PESA’s scale is unique, but the architectural direction is widely applicable: treat payments as an ecosystem with developers at the center.

A practical Daraja-style checklist for Ghana (operators, banks, aggregators)

If I were assessing a Ghana mobile money or payments API program heading into 2026, I’d look for these non-negotiables:

1. Clear API governance

   • published change logs
   • versioning policy with deprecation timelines
   • status page and incident postmortems shared with partners

2. Performance and resilience targets

   • stated TPS capacity and real-world tested limits
   • retry guidance and rate limits that don’t punish growth
   • disaster recovery expectations (what happens when a region fails)

3. Integration quality controls

   • sandbox that mirrors production behavior
   • webhook signature verification
   • idempotency support across key endpoints

4. Partner-centric support

   • defined SLAs for production incidents
   • escalation paths that work after hours
   • active developer community channels with real engineers

What to avoid: “API theater”

API theater is when a platform advertises APIs but:

• onboarding takes weeks due to unclear compliance steps
• documentation is outdated or missing edge cases
• support responses are inconsistent
• reversals and disputes are handled manually outside the API

The reality? If businesses can’t automate the full lifecycle—pay, confirm, settle, reverse, dispute—they’ll treat your API as unreliable and build workarounds that increase failure rates.

December in Ghana: why this timing matters

Late December is when payment systems face stress: higher volumes, more merchant activity, more social spending, and more operational pressure on support teams. It’s also when many businesses close their books and finally feel the pain of messy reconciliation.

That seasonality makes Daraja 3.0’s story especially relevant right now. Scaling isn’t only a “next year” problem. If your rails can’t handle peaks, your brand takes the hit—even when the issue was a technical debt decision made months earlier.

For Ghana’s fintech ecosystem going into 2026, the priority should be blunt: invest in API reliability and developer experience first, then layer AI automation on top. Doing it in reverse creates impressive demos and disappointing operations.

People also ask: What does an “API-first” strategy actually change?

It changes who you build for first. You still care about end users, but you design your payment product so that:

• developers can integrate in days, not weeks
• businesses can automate flows end-to-end
• internal teams can monitor and troubleshoot via logs and events

It also changes your data quality. With consistent API events and references, AI tools can detect fraud, predict cashflow, and automate accounting with fewer false alarms.

The next step for Ghana: build the rails that make AI useful

Daraja 3.0 is Safaricom admitting a modern truth: developers aren’t “external.” They’re part of the platform. Once a quarter of your transactions move through APIs, you either professionalize your developer ecosystem or you accept chronic friction as your operating model.

If your goal is AI-driven fintech in Ghana—better fraud controls, faster support, smarter credit, cleaner akɔntabuo—start with the rails: stable APIs, strong governance, and scalable capacity planning.

If you’re building or upgrading payments in Ghana and want a practical roadmap (API program design, automation priorities, and where AI delivers real ROI), what part of your stack is currently the weakest link: onboarding, reliability, reconciliation, or fraud controls?