The verdict in three sentences
Closing a mobile money point of sale means verifying that cash till + e-value float = recorded transactions + opening float. Gaps almost always come from three causes: double credit, unrecorded cash-out, or misposted commission. An alert threshold of 0.5% plus a strict checklist turns an invisible leak into a traceable anomaly.
The three balances to reconcile
Each evening the agent compares what they hold physically and digitally against what the system recorded. Here is the structure.
| Balance | Source | Role |
|---|---|---|
| Cash till | note/coin count | real cash |
| E-value float | MTN / Airtel agent app | real e-money |
| Day's transactions | receipts / software | what should have come in |
| Opening float | start-of-day amount | starting base |
| Discrepancy | (cash + e-value) - (transactions + float) | anomaly to explain |
If the discrepancy is zero, the day is clean. If it exceeds the threshold, investigate the cause before closing.
Discrepancy causes and alert thresholds
Not all anomalies are equal. Here are the most frequent 2026 causes and their trigger threshold.
| Cause | Typical sign | Alert threshold | Action |
|---|---|---|---|
| Double credit | e-value too high | > 0.3% | reverse the duplicate |
| Unrecorded cash-out | cash high, transactions low | > 0.5% | log the cash-out |
| Misposted commission | e-value net below expected | > 0.3% | reclassify to expense |
| Wrong change given | cash low | > 0.5% | train the team |
| Unticketed transaction | transactions below collections | > 0.5% | re-enter the receipt |
A gap that always leans the same way is never random: it is a process to fix, not a one-off error.
The 8-step closing checklist
- Count the cash till and note the total. 2. Read the MTN and Airtel e-value float. 3. Pull the day's transaction total. 4. Subtract the opening float. 5. Compute the discrepancy. 6. Check the day's commission postings. 7. Investigate any gap above threshold. 8. Sign the closing report and archive the export. The routine takes 10 minutes and makes every shilling traceable.
Mini case study
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Grace runs an MTN/Airtel agent kiosk in Kampala. One evening in 2026 she processes UGX 2,800,000 in transactions and starts with a UGX 200,000 float. At close, her cash till shows UGX 1,450,000 and her e-value float UGX 1,522,000, a total of UGX 2,972,000. The expected balance is 2,800,000 + 200,000 - commission (~UGX 28,000) = UGX 2,972,000. Discrepancy: UGX 0, well inside tolerance. The prior month, with no routine, she accumulated UGX 25,000 of daily gap from commission never reclassified, distorting profit by UGX 750,000 over the month.
FAQ
What discrepancy should I tolerate before investigating?
Set 0.5% of processed volume as the alert threshold, and 0.3% for systemic causes like double credit. Below that, a sample check is enough.
How do I detect a double credit?
The e-value float sits higher than recorded transactions. Look for two transactions of the same amount and counterparty seconds apart, then reverse the duplicate.
Should I close even with a small gap?
Yes, but document it. A gap under threshold is noted and monitored; a gap above it is resolved before closing. Never close on a large unexplained shortfall.
How often should I archive exports?
Every evening. The day's MTN/Airtel export, attached to the signed closing report, is your audit trail for any control or dispute.
Can this closing be automated?
Yes, a simple sheet or a till system connected to operator APIs computes the discrepancy automatically and alerts beyond the threshold, removing manual math.
Let's talk about your project. We equip your point of sale with automated mobile money closing and gap alerts. WhatsApp +221 77 596 93 33.
Mohamed Bah
Fondateur, Kolonell
Passionate about digital and entrepreneurship in Africa, Mohamed has been helping Sénégalese businesses with their digital transformation since 2020. Founder of Kolonell, he believes every SME deserves a professional and accessible online présence.
