Reconciling thousands of M-Pesa payments a day

A national distributor collects most of its payments from retailers through M-Pesa Paybill.

Use case · how we solve it
01 · The challenge

What holds organisations back.

  • Finance teams matching payments by hand
  • Customer credit held up for days
  • Month-end close stretching over a week
02 · The solution

PayLink: M-Pesa & bank reconciliation.

M-Pesa and bank payments matched to invoices and posted to your ERP automatically.

03 · How it works

The architecture.

About PayLink
SOLUTION ARCHITECTURE · PAYLINK REFERENCE DESIGN · v1.0 01 PAYMENT CHANNELS 02 INTEGRATION 03 PROCESSING 04 CORE & INSIGHT M-Pesa Daraja C2B · Paybill Bank feeds Host-to-host · MT940 API gateway OAuth2 · TLS 1.3 Event stream Kafka topics Matching engine Rules + ML scoring Payments ledger PostgreSQL · audit SAP S/4HANA Finance · OData Exceptions console Power BI · alerts 1 2 3 4 5 6 7 PLATFORM, SECURITY & OPERATIONS Azure / AWS Key vault Monitoring WAF & IAM
  1. 1M-Pesa notifies the gateway of each paymentHTTPS callback · JSON
  2. 2Bank statements arrive every 15 minutesSFTP / H2H · MT940
  3. 3Payments are published as eventsKafka · at-least-once
  4. 4The matching engine consumes each eventConsumer group
  5. 5Every decision is stored for auditSQL · immutable log
  6. 6Cleared items post to the general ledgerOData · idempotent
  7. 7Exceptions surface for finance reviewNear real time
04 · How we deliver

Our lifecycle, step by step.

  1. Understand

    Map payment flows and matching rules

  2. Design

    Connect M-Pesa Daraja and bank feeds

  3. Develop

    Automate matching and ERP posting

  4. Review & test

    Test with months of historical transactions

  5. Deploy & manage

    Go-live with hypercare, then 24×7 support and monthly reviews.

05 · What changes
Automaticmatching, instead of days by hand
Same daycustomer credit release
1 queuefor true exceptions only
Target outcomes for this scenario. Actual results depend on each organisation's volumes and systems.
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