API-Driven Fintech Platform for Automated Credit Scoring & Real-Time Banking Sync
Client Overview
A growing fintech startup providing digital lending and micro-finance services to underserved SMEs and individuals across three countries. The platform supports 150,000+ active borrowers and processes loan applications worth over USD 50 million annually.
Engagement model: Dedicated Team
The Challenge
As lending volumes increased, the client’s underwriting and data infrastructure struggled to scale.
- Manual credit scoring relied on outdated financial statements, delaying decisions by 2–5 days
- Fragmented banking integrations led to disjointed account data and reconciliation issues
- No real-time financial health indicator for evaluating borrower risk
- Rising loan default rates due to limited predictive analytics
The client needed a real-time, API-first lending platform that could automate credit decisions, unify bank data across geographies, and remain compliant with financial regulations.
Our Solution
Automated Credit Scoring Engine
AI-driven scoring using alternative data sources such as utility payments, mobile transactions, and behavioral signals, combined with traditional financial inputs for balanced risk assessment.
Digital Loan Origination Workflow
End-to-end automation from application to approval, including configurable risk rules and e-signature-enabled approvals.
Real-Time Banking Sync
Secure APIs aggregating transaction history, balances, and repayment patterns from multiple banking partners to provide a unified borrower financial view.
Predictive Risk Intelligence
ML-based probability models to anticipate default risk early and support proactive portfolio management.
Technologies Applied
- AWS
- Node.js
- Python
- REST APIs
- Machine Learning
The Outcome
The platform delivered measurable improvements in speed, accuracy, and operational efficiency:
- Loan approval time reduced from 3–5 days to under 30 minutes
- 18% reduction in loan default rates within six months
- 35% reduction in underwriting operational costs through automation
- Improved borrower risk profiling and healthier loan portfolios
- Platform scalability validated with five additional banking integrations added without major rework
The result was a faster, data-driven, and scalable lending operation capable of supporting cross-border growth with confidence.