Indian conglomerate lender unlocks ₹1,200 crore liquidity with 95% repayment and 3x productivity gains through SHG lending digitization

India's SHG lending ecosystem serves 9.1 million self-help groups and 100 million women. For this leading Indian conglomerate lender—managing ₹50,000 crore in SHG credit across 30,000 branches—approval cycles ran 10–15 days due to paper-heavy onboarding and inconsistent KYC processes. Without cross-bureau checks, hidden group overexposure accumulated silently in the portfolio. These compounding inefficiencies generated direct liquidity drag and elevated NPA exposure, and undercut trust.

The lender deployed ezee.ai's no-code loan origination system (LOS), purpose-built for SHG operations and rolled out across its 30,000-branch network without custom engineering. eKYC/CKYC/Aadhaar-based digital onboarding replaced paper workflows, while cross-bureau de-duplication and rule-based exposure limits blocked overexposure at origination. Predictive risk scoring continuously surfaced early warning signals across the live portfolio, enabling proactive intervention before delinquencies materialized. Collection workflows were automated via UPI/NACH, with geo-tagged field execution and purpose-tagged loan tracking. Live risk dashboards with geo-mapping gave real-time visibility into the portfolio. The no-code architecture allowed RBI/NABARD compliance configurations—including CKYC and Aadhaar verification—to be deployed at national scale.

The transformation compressed approval cycles from 10–15 days to 2–3 days, directly unlocking ₹1,200 crore in annual liquidity across rural markets. Collections stabilized at 95%+, sustained by automated digital reminders and UPI/NACH payment rails tied to group attendance discipline. Key outcomes across the ₹50,000 crore portfolio:

• NPAs reduced 15–20% through cross-bureau de-duplication and real-time scoring that pre-empted ~25% of potential delinquencies
• Staff productivity rose 2–3x as unified dashboards replaced manual bottlenecks
• Per-loan field costs fell 25–30% via mobile-first execution
• 100% RBI/NABARD alignment achieved with CKYC, Aadhaar, and geo-tag verification

• Embedding cross-bureau de-duplication and predictive risk scoring can intercept a material share of delinquencies at portfolio scale.
• UPI/NACH automation tied to group attendance discipline tightens the collection loop, improving both cost efficiency and repayment rates simultaneously.
• No-code LOS platforms can absorb complex regulatory requirements (RBI/NABARD) at national scale by treating compliance as a configuration parameter rather than an engineering rebuild.
• Geo-tagged field execution paired with live portfolio dashboards reduces information asymmetry between central risk teams and distributed branches—a critical control layer for large, geographically dispersed SHG books.