For banks, co-op banks and NBFCs
One borrower, one file: from the branch to the credit desk to the first warning sign, in their language, on your bank's own systems.
AiBanker is software for banks and regulated lenders. It is not a bank or a lender.
Lenders, investors and programmes that work with Altiora, the team behind AiBanker. Hover a logo to see the relationship.
Paisa247, Client. Paisa247 uses Dhana, AiBanker's voice agent, to call its new leads.
Kerala Bank, Partner. Dhana's voice agents will serve Kerala Bank.
Mayyanad Regional Co-operative Bank, MoU. Mayyanad Regional Co-operative Bank has an MoU with Altiora.
Group Meeran, Investor. Group Meeran is an investor in Altiora, which builds AiBanker.
JAIN University, Investor. JAIN University is an investor in Altiora, which builds AiBanker.
Innovation Incubator, Incubator. Altiora is incubated by Innovation Incubator.
IIT Madras, Incubator. Altiora is incubated at IIT Madras.
Kerala Startup Mission, Recognised startup. Altiora is a startup recognised by Kerala Startup Mission.
Startup India, DPIIT recognised. Altiora is a DPIIT-recognised startup under Startup India (DIPP230717).
Amazon Web Services, Cloud. Dhana, AiBanker's voice agent, runs on AWS, in Mumbai.
Google Cloud, Cloud. Some of Dhana runs on Google Cloud.AiBanker carries each customer's story through your lending, on the core banking, loan system and credit policy you already run. Replace nothing. Re-do less.
Reads your core banking, loan system and bureau data, and writes tasks and notes back into them. No new screen for your staff.
Dhana talks to each applicant in their language, by voice or WhatsApp, runs your checklist and logs consent and the KFS explanation.
Fetches documents via DigiLocker and Account Aggregator, books video KYC with your official, and logs a complete file in your loan system.
Drafts the credit memo in your template, every number traced to its source. Recommends with reasons; your officer decides.
Sorts files and accounts into your queues and risk buckets, and keeps each borrower's credit memory on your servers for renewals.
Spots stress before a missed EMI and explains it in plain reason codes. A help call in their language, then your RM follows up.
Runs on your servers or your own cloud in India. The file, and anything that learns, stays with your bank.
/Decision-ready file/
UPI lines carry shop takings, rent, chit funds and informal loans. A basic statement parser files most of them under 'others'. AiBanker reads every line and traces each figure to it – and the picture changes.
Illustration · made-up statement
Bank statement · October ↓
| Narration | Amount | Read as |
|---|---|---|
| NEFT-HDFC0004127-ACME TEXTILES PVT LTD/SALARY OCT | +₹ 32,000 | Income · salaryIncome · salary |
| UPI/CR/402211874/SRI DURGA STORES/QR SETTLEMENT | +₹ 18,500 | Transfer / othersIncome · shop sales |
| UPI/DR/398812301/RAJESH K/RENT NOV | −₹ 9,000 | Transfer / othersObligation · rent |
| ACH-DR-NBFC LOANS LTD-EMI-55102 | −₹ 6,200 | Obligation · EMIObligation · EMI |
| UPI/DR/771203990/KAVITHA M/CHITTY 12 | −₹ 5,000 | Transfer / othersObligation · chit fund |
| IMPS/DR/556677/GOLD LOAN INT/ACC 8841 | −₹ 2,400 | Transfer / othersObligation · gold loan |
Monthly income
₹50,500
Monthly obligations
₹22,600
Debt-to-income (FOIR)
45%
Stretched. Flagged for the credit officer, with reasons.
Same applicant, two credit pictures: the basic reading missed ₹18,500 of income and ₹16,400 of obligations.
For their customers
In your app, on WhatsApp or on the web – one agent that knows the customer, speaks their language and gets things done, in chat or voice, under your bank's own security.
01 · On App
“Pay Rahul 2,000 for rent”
Rahul Menon, two thousand rupees, from Savings ••4821. Approve it with your UPI PIN in your bank app.
₹2,000 to Rahul · approve with your PIN
02 · On WhatsApp
“See where my salary went”
₹46,320 spent this month. Rent is the biggest item, at ₹18,000.
Spending explained · ₹46,320
03 · On Web
“Move 5,000 to savings every payday”
Ready: ₹5,000 moves to your emergency fund on the 1st of every month, once you approve it in your bank app.
₹5,000 every payday · approved in app
04 · On App
“I have 20,000 spare. Any ideas?”
Three of your bank's own options for a medium-risk, three-year goal, with the facts for each. You decide.
3 options · from your bank
05 · On WhatsApp
“Do I need term insurance?”
With a home loan, many people choose cover that clears the loan. Two of your bank's plans to compare; you buy with your bank's staff.
2 term plans · compare, then buy at the bank
Sample conversation with made-up data. Payments are approved with your bank's own PIN or OTP. Guidance covers your bank's own products; the customer decides.
Who it's for
One file per borrower, shaped to how your institution lends.
Your model, your officer, your data, your premises.
Big platforms connect the lending cycle if you replace your systems with theirs. AiBanker connects it on the systems you already run – one borrower at a time. Here's how it compares.
AiBanker recommendsScore 82 / 100
Renew Lakshmi Stores' ₹6,00,000 working-capital limit
Made-up borrower. Nothing moves without the officer.
Compare AiBanker with
| AiBanker | General-purpose AI | |
|---|---|---|
| Your systems | No change to your core, your loan system or your credit policy | An API you build around your systems |
| One borrower's thread | Onboarding notes reach the credit memo; credit reasons shape the warning call | Each task is a separate prompt |
| Who decides | Recommends with reasons. Your officer decides, and the record shows what they saw | Not by default – the audit trail is yours to build |
| Your data | On your servers or your cloud in India. Your bank's model learns, on your servers | Depends on the vendor's cloud and terms |
| The customer's language | 20+ Indian languages, AI disclosed, a person one tap away | Many languages; banking tone and disclosure are up to you |
| Proof | Measured on your own book: first-time-right files, days of warning, roll rates | Generic benchmarks, not your book |
| Compliance | A compliance pack with every pilot: model card, kill switch, audit rights | Your team writes the model documentation |
Compares approaches in general, not named products.
A human-like, emotion-aware voice in 20+ Indian languages, hosted in India, that talks like your branch and says it's an AI.
Onboarding, credit, warnings and service share one file, with every fact traced to the system it came from.
Past memos, conditions and notes stay on your servers, so a renewal reviews only what changed.
Every recommendation keeps its reasons and what the officer checked. The file is decision-ready; the decision is defensible.
The same file serves your customers: service, payments under your own security and your bank's products, in their language.
Our conversational banking is the subject of patent application 202641000710 (published, not yet granted).
Request a pilot
Start with the whole stack, one journey, or a free read-only early-warning backtest on your own repayment data.
You're chatting with an automated assistant, not a person. Your details are used only to contact you about AiBanker. Privacy notice