ABOUT THE COMPANY
Building India's lending operations network
This fintech operates as an RBI-licensed Loan Service Provider (LSP), connecting borrowers with a network of 200+ lending partners (banks, NBFCs, and peer-to-peer platforms). With a ₹950 crore loan book and 30% quarterly growth, they've built a distributed origination model. However, scaling the partner network required manual due diligence, CAM generation, and lender matching,bottlenecking their sourcing velocity.
INDUSTRY CONTEXT & DEMAND
The fintech aggregation race heats up
As P2P platforms, neobanks, and alternative lenders proliferate in India, lending-tech platforms compete on two fronts: borrower acquisition and partner density. LSPs that scale their lending partner network faster can absorb more loan volume per borrower and lower funding costs. RBI's lending guidelines (2024) also require stronger partner due diligence, but manual processes can't keep pace with growth. Fast-movers win market share.
THE CHALLENGE · BEFORE
7 days per partner, three teams doing manual work
Partner onboarding involved three manual workflows: (1) Partner due diligence with CIBIL checks and regulatory verification (2 days), (2) CAM document generation (3 days), and (3) Lender-borrower matching logic (2 days). The process was sequential, error-prone, and created friction with eager lending partners. Previous quarter, only 23 partners were onboarded despite 40+ applications.
- 7-day partner onboarding cycle blocked partner sourcing velocity
- 23 partners onboarded in previous best quarter; demand far exceeded capacity
- CAM documents generated manually by credit analyst; 5-6 hours per deal
- First-lender match rate only 22% (many borrowers rejected by first matched lender)
- Audit findings: 8 compliance gaps in partner KYC per quarter
HOW AICA HELPED · THE SOLUTION
Parallel AI processing: due diligence + CAM + matching in 6 hours
AICA's Partner Platform automated due diligence (RBI checks, director verification, bureau scoring) in parallel with CAM generation and lender matching. Instead of sequential days, the system ran all three in parallel and completed in 6 hours. Lender Match's AI scoring algorithm improved first-lender success rate by analyzing borrower-lender affinity, improving sourcing velocity.
- Partner Platform, RBI regulatory checks + director CIBIL + GST verification in parallel
- AI Underwriting, 360° partner risk report with 250+ checks in 6.2 seconds
- CAM Generation, Compliance and approval memo auto-drafted, 5h→4 minutes
- Lender Match, Borrower-lender affinity scoring; improved first-match approval rate
THE OUTCOME · AFTER
84 partners in one quarter; 2.4× margin improvement
In Q2 FY26, the platform onboarded 84 partners,a 265% increase from the previous quarter's record of 23. Sourcing velocity improved 208%, and first-lender match rate jumped from 22% to 45%, reducing rework and improving borrower experience. Each partner onboarding created standardized, audit-clean CAM documents. Additional lending partners unlocked ₹95 crore in new origination capacity.
- Partner onboarding: 7 days → 6 hours (99% reduction)
- Partners added Q2: 23 → 84 (+265%)
- Sourcing velocity: +208%
- First-lender match rate: 22% → 45%
- Audit findings: 8/qtr → 0
- CAM generation time: 5 hours → 4 minutes