Liquidity-as-a-Service & Automated Payroll Settlement Engine
Zofi Cash Salary Advance (EWA) Platform
A full-stack EWA ecosystem that calculates “earned but unpaid” wages in real time and settles advances automatically—built for payroll correctness and bank-grade security.
The Challenge
In emerging markets, 70% of the workforce faces high-interest predatory lending between pay cycles. Employers needed a way to offer Earned Wage Access (EWA) without impacting their own cash flow or creating manual accounting overhead.
The technical hurdle was building a real-time accrual engine that can calculate “unpaid but earned” wages across disparate payroll systems with varying tax brackets—while staying correct under edge cases (time corrections, partial periods, and payout failures) and keeping HR out of the loop.
Quick Stats
- Compliance: KYC / AML
- Payments: Mobile Money + Bank rails
- Security: AES-256 + MFA
- Impact: 10,000+ users; 98% repayment
The Solution
A full-stack FinTech ecosystem that enables instant wage withdrawals. We engineered a proprietary accrual logic layer that syncs with employer attendance data to compute a “Safe-to-Withdraw” limit—preventing over-drafting and payroll discrepancies.
The platform is designed to be operationally invisible: advances are calculated deterministically (net of taxes and contributions), disbursements are handled through integrated payout rails, and settlement is automated via bank/ERP-compatible files so HR and payroll do not reconcile transactions manually.
Technical Approach
- Deterministic accrual logic: Formula-based engine calculates net pay (after taxes/social contributions) on a per-diem basis.
- Automated batch settlement: Middleware generates ISO 20022-compliant settlement files for employer banking at month-end.
Technical Details
Architecture
Flutter (Mobile) → Node.js (Microservices) → PostgreSQL (High-Availability RDS)
Integrations
Plaid/Okra (bank verification), M-Pesa/Airtel Money (disbursement), SAP/Oracle ERP connectors.
Security
KYC/AML screening via Jumio, AES-256 encryption, and multi-factor authentication (MFA).
AI Features
Repayment predictor adjusts risk-based withdrawal limits using attendance and withdrawal frequency signals.
Results & Impact
- 10,000+ active users reached within the first 6 months.
- 98% repayment rate due to at-source automated payroll deductions.
- Zero manual HR work across the advance-to-repayment lifecycle.
Ready to build something similar?
We’ll design your payout + payroll settlement flows for correctness, auditability, and scale.
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