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AdmireTech helped a mid-sized Nigerian microfinance institution turn raw transaction data into personalised savings nudges and goal-based savings pots — helping customers with irregular income save more consistently.
The institution's name is withheld at its request to protect client confidentiality.
The Challenge
The institution serves salaried workers, informal traders, and micro-entrepreneurs whose income doesn't arrive on a fixed schedule. Savings products existed, but usage was uneven — many customers deposited only when they had surplus, others withdrew too early, and manual staff outreach couldn't shift behaviour at the scale the institution needed.
What We Built
AI analysed deposit frequency, repayment behaviour, and seasonal income patterns to understand each customer's real cash-flow rhythm — not a generic assumption of steady income.
SMS and mobile prompts timed to each customer's own cash-flow cycle, replacing generic blanket reminders with messages that matched when people actually had money to save.
Customers could save toward school fees, inventory restocking, emergency funds, or family and religious obligations — giving every deposit a clear, motivating purpose.
Every behavioural signal used for nudging was collected and processed under explicit customer consent, balancing innovation with privacy and trust.
Implementation
Small pilot group of active depositors grouped into behavioural segments: regular savers, salary earners, seasonal traders.
AI recommended save amounts, timing, and triggered nudges when behaviour signalled a likely lapse.
Consent-based data handling introduced across the pilot to balance personalisation with privacy.
Rollout extended with human support retained alongside digital nudges for customers who needed it.
Outcomes
Customer engagement with savings products improved noticeably after launch
Nudges matched each customer's income cycle and spending behaviour far more closely than generic reminders
Staff spent less time manually following up on inactive accounts
Institution gained much better visibility into customer saving habits
“I'll admit I was skeptical at first — could an algorithm really understand our customers the way our field officers do? What changed my mind was watching it work: traders who used to save only when they had extra cash finally building a rhythm, savings pots opened for school fees, emergencies, family obligations. The AI didn't replace how we serve people — it helped us finally see them clearly, and respond in a way that felt personal instead of generic. For an institution built on trust, that matters more than any efficiency number, and it's exactly the kind of step financial inclusion in Nigeria needs.”
Morayo Brown · Lead IT Manager
Lessons Learned
AdmireTech builds explainable, consent-first AI tools that respect how African customers actually manage money.