Logix — Loan Automation (NJ Capital)
Client: NJ Group / NJ Capital
Led backend for a loan-automation platform serving 49,000+ partners and ~360,000 users, automating disbursal with full KYC integration.
Shared at a level that respects client confidentiality; internal details and credentials are omitted.
Deep dive
Logix was a loan-automation platform for NJ Capital, part of one of India's largest financial distribution networks. The scale was significant from the outset: over 49,000 partners and roughly 360,000 users, all needing fast, reliable loan origination and disbursal. At that size, small inefficiencies in the process multiply into enormous amounts of manual work and delay.
As project lead on the backend, the core problem I owned was replacing slow, manual verification with an automated disbursal pipeline that could still satisfy strict financial-compliance requirements. In Indian lending, you cannot simply trust a form — you have to verify identity, creditworthiness and bank details against authoritative sources before money moves. Getting that automated without cutting a single compliance corner was the whole game.
That meant integrating a demanding stack of Indian identity and credit APIs into one orchestrated flow: Aadhaar KYC for identity, DigiLocker for verified documents, PAN verification, CIBIL for credit history, CAMS/KFIN for financial data, and Penny-drop for bank-account validation. Each of these has its own contracts, failure modes, rate limits and latency characteristics, so the pipeline had to handle partial failures and retries gracefully rather than dropping an application whenever one upstream service hiccuped.
We also had to model the partner and user hierarchies of the distribution network accurately, because loans are originated, attributed and tracked through a multi-level partner structure. Getting that hierarchy right is what let the system route applications correctly and give every partner a trustworthy view of their own book of business.
The outcome was concrete: the platform processed around 430 loan applications per day through automated disbursal and cut manual verification effort by more than 60%. Turnaround times that used to depend on a human checking documents collapsed to the speed of an API call. It remains a clear, real-world example of the regulation-grade, high-integration fintech engineering Algoverse specialises in.
The problem
A large distribution network needed to move loan origination off manual processes — verifying identity, creditworthiness and bank details at scale while cutting turnaround time.
Our approach
- Led backend development of the automated disbursal pipeline.
- Integrated Aadhaar KYC, DigiLocker, CAMS/KFIN, PAN, CIBIL and Penny-drop APIs.
- Modelled partner and user hierarchies across the distribution network.
- Automated verification workflows to remove manual bottlenecks.
Outcome
- Served 49,000+ partners and ~360,000 users.
- Processed ~430 loan applications per day through automated disbursal.
- Reduced manual verification effort by 60%+.
The hard parts we solved
Six-way verification pipeline
Aadhaar, DigiLocker, PAN, CIBIL, CAMS/KFIN and Penny-drop integrated into one orchestrated KYC + credit flow.
Hierarchy-aware origination
Partner and user hierarchies modelled to route and attribute loans across a 49K-partner network.
60%+ less manual effort
Workflow automation removed the bottlenecks that previously slowed disbursal.
How it fits together
A simplified view of the system, layer by layer.
- Channels
- Partner portal
- User app
- Core
- Loan origination
- Disbursal pipeline
- Workflow automation
- Verification
- Aadhaar KYC
- DigiLocker
- PAN
- CIBIL
- Penny-drop
- Data
- Partner hierarchy
- Application store
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