Industries · Financial Services
AI that ships inside your core banking, not a sandbox demo
Banao builds and deploys AI for banks, NBFCs, lenders, insurers, and payments platforms — fraud scoring, document KYC, credit underwriting, and AML — wired into your core, not a standalone proof of concept.
Every system below runs with an audit trail, an explainability layer, and your compliance team's sign-off. We ship deployed software, not slide decks or Jupyter notebooks.
PhonePe— Banao engineering at payments scale, where fraud and uptime are the product.
The first call is free · 45 minutes · no obligation
What we build
What we deploy in financial services
Each of these maps to a number your board already watches — fraud loss, onboarding drop-off, default rate, or cost-to-serve. We start where the basis points are.
Fraud detection & AML scoring
ML fraud scoring and transaction anomaly detection that catch patterns a rules engine misses, with a case-management queue and an investigator dashboard your risk team works from.
Document KYC & onboarding
Document verification, face match, liveness, and address-proof OCR wired into your onboarding flow, with a compliance audit log on every decision.
Credit risk & underwriting models
Custom scoring on alt-data — UPI, GST, bank statements — with an explainability layer and bureau integration, so thin-file applicants get a decision without a black box.
Regulatory reporting & screening
Sanctions and PEP screening plus reporting automation that turns audit prep from a fire drill into a query, with the trail regulators ask for.
Collections prioritisation
Priority scoring over your loan book with multi-channel outreach — call, WhatsApp, email — and an ops dashboard, so agents work the accounts most likely to pay.
Document intelligence for finance ops
Invoices, statements, and contracts pulled out of PDFs into a searchable, chat-queryable store for finance and operations teams.
Receipts
Deployed in regulated finance
Metrics shown dotted (··) are being finalised in our case-study metrics pack — we will not publish a number before it is verified. Some clients in this vertical are named; others we describe without identifying them, as their contracts require.
Fraud and uptime held at payments scale
PhonePe runs payments and commerce for hundreds of millions of users, where a missed fraud pattern or a minute of downtime is measured in real money. Banao has contributed engineering at that scale, building to the latency, audit, and reliability bar that regulated payments demand.
Manual underwriting replaced by an explainable credit model
A digital lender underwrote by hand — slow, and inconsistent on thin-file customers the bureaus could not score. Banao built a credit model on alternative data — UPI, GST, and bank-statement signals — with an explainability layer, so every decline carries a reason the compliance team can defend.
Dogfooding
We run our own company on the AI we sell
Banao operates a ~300-person engineering company on its own AI products before any client sees them. InterviewGod screens our own hires. Vikaas runs our own demand generation.
That is the difference between a vendor who has read about production AI and one who depends on it every working day. For BFSI it also means our own systems already carry audit logs and access controls, because we answer to our own finance and security teams first.
Screens Banao's own engineering hires every week.
Runs Banao's own demand-gen pipeline end to end.
The honest version
When financial-services AI doesn't earn its keep
Most AI vendors will sell you a model regardless. We would rather tell you when not to build — it is why risk and compliance heads take our second call.
- Thin transaction volume: below a certain throughput, a fraud analyst and a good rules engine cost less than an ML pipeline to maintain. We'll say so.
- No labelled history: a fraud or credit model needs examples of what went wrong. If you have no chargeback, default, or claims history yet, week one is instrumentation, not modelling.
- A policy answer disguised as a model: if the real blocker is a regulator sign-off or an internal rule, software won't move it. We'll point you back to the cheaper fix.
How we start
How we start — fixed-price, low risk
You have been pitched by core-banking vendors and three fintech consultancies already. We start by pricing the problem, not by quoting a build — with compliance in the room from day one.
- 01
AI Discovery Sprint
2 weeks · fixed price
On-site or inside your VPC. You walk out with a prioritised list of AI opportunities, baseline ROI maths in basis points, a go/no-go per opportunity, and a compliance and security architecture note — yours to keep either way. If you proceed, the Sprint cost is credited against the build.
- 02
Build
Data engineering first, then the model, with your CISO's architecture review as the first deliverable. We integrate with your core — Finacle, BaNCS, Mambu, or custom — and build the cleaning pipeline as a deliverable, not a prerequisite.
- 03
Production & continuous learning
Deployment with audit logging, explainability, and access controls, plus a dashboard your risk and ops teams actually open. The model keeps improving as each month's fraud, default, and claims data comes in.
FAQ
Frequently asked questions
We're heavily regulated. Can you move at the speed you claim?
Yes, and the speed is the compliant posture. Slow multi-year builds let code rot and vulnerabilities accumulate. We ship smaller and more often, with full testing and an audit trail. The first deliverable in any BFSI engagement is a compliance and security architecture review co-signed by your team.
Our core banking vendor controls everything. Can you even integrate?
Every modern core has API gateways or middleware paths, and we have built around legacy cores too. Banao has integrated with the common platforms and worked alongside COBOL-era systems via retrofit. The integration audit is week one.
Our customer data is too sensitive to share.
Understood. We work on-prem, inside your VPC, or via secure clean-rooms. Our engineers sign NDAs and pass background verification, and we have run engagements where the team never touched live customer data — training happens entirely inside your perimeter.
How do we prove ROI before committing budget?
That is what the AI Discovery Sprint produces — fixed price, two weeks, you keep the ROI model in basis points whether or not you continue. Worst case you have a free assessment; best case you have the business case for your board.
We tried a fintech vendor and our compliance team killed it.
Most fintech vendors design for the product and bolt on compliance later. We design both together. No feature gets built until the compliance and security architecture is signed off by your CISO.
Get started
Find out where AI actually pays off in your book
Bring your biggest source of fraud loss, onboarding drop-off, or underwriting delay. In 45 minutes we'll map the AI opportunity and the basis points behind it.
Book a Discovery Sprint