For NBFCs, digital lenders, wealth management firms, and payment businesses that need compliant, scalable platforms — without the overhead of building a full in-house engineering function.
Tools we wire together
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Live signal
Every card below is a working pattern we've shipped or scoped for a real finance & fintech client — not a wishlist.
Automated KYC, bureau pulls, and AI bank-statement analysis. Approvals in under an hour with full RBI audit trail.
Tamper-proof records and automated regulatory reports for RBI filings. Compliance shifts from a week of effort to a few clicks.
Real-time portfolio health dashboards with early-warning flags and automated collections workflows. Nothing slips into write-off.
Custom credit scorecards combining bureau data, bank flows, and alt-data — explainable, auditable, and tuned to your portfolio.
Self-service mobile app for EMI views, statements, top-ups, and grievance — cutting servicing call volumes 40–60%.
Real-time fraud scoring on transactions, applications, and account activity — with human-review workflows for borderline cases.
Wire to Setu, OneMoney, Finvu, NADL — pull consented bank, GST, and tax data in seconds. Underwriting decisions move from days to a single flow.
Plug into co-lender APIs (private and PSU banks, NBFCs) for split-disbursal, joint underwriting, and reconciliation. Co-lending becomes a real product, not an Excel-based hack.
RBI cybersecurity framework, SAR/IS audit readiness, secure SDLC, secrets management, and incident-response runbooks — built into the platform, not stapled on at audit time.
Tools typically used
AWSOpenAIPostgreSQLPythonRedisSeSetu (AA)These are the workflows that quietly drain margin, staff time, and patience. Every system we build starts from one of these.
Salaried, self-employed, business loans — all queued behind 10 staff manually reading PDFs. Customers churn while waiting. Competitors approve in minutes.
Quarterly returns, fraud monitoring reports, and CKYC updates assembled from three systems by one stressed analyst the night before deadline.
Field agents and tele-callers ping the same borrower thrice in a day. Complaints rise, recovery doesn't — and the regulator has been watching this closely.
First-payment-defaults and account takeovers spotted in monthly reviews — when the money is already gone and the customer is uncontactable.
Every new RBI circular means another emergency code change. Documentation is sparse. Knowledge sits with one engineer who is also on call.
EMIs, statements, foreclosure quotes, top-ups — all routed through call-centre queues. Servicing cost-to-income climbs while NPS sinks.
Specific, working uses of LLMs and ML in real finance & fintechoperations — not generic “AI-powered” marketing.
GPT + AWS Textract / Document AI extract income, transactions, and red flags from bank statements, pay slips, and ITRs — feeding underwriting in seconds.
Models blending bureau data, bank flows, and consented alt-data (utilities, employer, mobile) to extend credit to thin-file borrowers — explainable and auditable.
An AI agent handling EMI queries, top-ups, foreclosure quotes, and grievance intake on WhatsApp — cutting servicing volume 40–60% with full audit trail.
Real-time scoring on applications, logins, and transactions — surfacing patterns humans miss and routing borderline cases to review queues with reasoning.
Risk-tiered nudge plans (WhatsApp → voice → field) optimised by an RL policy on past response data — fewer calls, better recovery, lower complaint volume.
Automated assembly of regulatory returns from source data, with LLM-driven sanity checks against the previous quarter and circular text — analyst signs off in minutes.
A four-stage framework with AI capability called out at each step — so you can see exactly where machine learning earns its keep.
We map your products, partner bank stack, and reporting surface (RBI, FIU-IND, CKYC, CGTMSE). You leave with a written plan, not a brochure.
AI-assisted regulatory checklist generation against your product set.
We ship the one workflow that buys you the most margin first — usually AI document parsing for underwriting or AA-based eligibility. Live, audited, in production.
LLM-bootstrapped policy rules, scorecards, and reporting templates.
Branch / DSA / agent enablement, parallel-run for a cycle, and audit-trail validation. We're on the floor with risk and compliance during cutover.
Auto-classification of legacy customer files into the new schema.
Monthly review of TAT, approval rate, NPA roll-rates, fraud catch-rate, and cost-to-income. Quarterly compliance posture review with your audit team.
Anomaly alerts on credit drift, fraud spikes, and reporting variances.
Every system we ship comes with the controls and audit surface your inspectors will ask for — designed in from day one, not bolted on later.
Built to current RBI Master Directions on digital lending, KYC, fraud monitoring, and outsourcing. Architecture and audit trail align with the supervisory expectation, not the bare minimum.
Indian personal-data handling, explicit consent flows, data-principal requests, and STR/CTR pipeline to FIU-IND — designed in from day one.
Secure SDLC, secrets management, RBAC, encryption at-rest and in-transit, and audit logging — the controls auditors look for, in place by design.
Compliant with RBI's Account Aggregator framework and DPSS guidelines for prepaid instruments, wallets, and payment-system participation as relevant to your licence.
Concrete scenarios, scoped from real conversations. Each one is a pattern we'd execute on day one.
Tell us where you are. We'll scope it, estimate it, and walk you through exactly how we'd approach it.
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