Industries · BFSI

Faster loan files and calmer collections, inside the rules you already follow

Name: AksharAI
Brand: AksharAI
Price: 7500 INR

Banks, NBFCs, insurers and brokers run on documents and follow-ups: KYC papers, bank statements, claim forms, collection calls. AI is useful for reading and checking those documents, preparing call notes and answering routine customer questions. Credit decisions, claim decisions and anything a regulator expects a person to own stay with your staff.

Book a demo See the agents

A bank teller at a desk assisting customers inside a bank branch

Where agents help

Five places to start in BFSI

Loan file checks

Document extraction agent

The agent reads salary slips, bank statements, GST returns and ITRs, fills the credit memo fields and lists what is missing or inconsistent. The credit officer reviews and decides.

Collections call preparation

Finance copilot

Before each call, an NBFC's collections team sees the borrower's dues, past promises to pay and last conversation in one short note, with a script that stays inside the fair practices code.

Customer service on chat and WhatsApp

Support agent

Statement requests, EMI dates, branch timings and document status are answered from your systems. Complaints and anything involving money movement go to a person.

Claim intake for insurers

Document extraction agent

Claim forms, hospital bills and survey reports are read and checked against the policy terms, and the claims handler gets a summary with the gaps already marked.

Circular and policy lookup

Research assistant

Compliance and operations staff ask what an internal policy or a regulator's circular says on a point, and get the relevant passage with its reference so they can read it in full.

Watch one at work

The document extraction agent in a working day

Reads scanned forms and documents and fills the fields your system needs

About the document extraction agent

AksharAI / list

AksharAIKYC extraction queue, 22 Sep 2026SearchAK

KYC extraction queue, 22 Sep 2026

Application	Applicant	Documents	Check	Status
TW-26-08841	Hetal Parmar	PAN, Aadhaar, 3 slips	All fields read	Posted
TW-26-08842	Imran Shaikh	PAN, Aadhaar, statement	Name spelling differs	Review: Rakesh
TW-26-08845	Kavita Joshi	PAN, statement	July salary missing	On hold
TW-26-08847	Suresh Vaghela	PAN, Aadhaar, 3 slips	All fields read	Posted
TW-26-08850	Pooja Rana	Aadhaar photo	Image too blurred	Re-upload asked

Representative screen with sample data. Client screens stay private.

Step 1Document arrivesScan, photo, PDF
Step 2Text readOCR and layout
Step 3Fields extractedInto your format
Step 4Checked against rulesLow confidence to a person
Step 5Sent to your systemAfter approval

An example scenario

An NBFC's two-wheeler collections desk

Agents in a Surat branch start each morning with a list of overdue accounts and little context. An agent prepares a short note for each call: amount due, last promise, preferred language and the approved script. After the call, the agent drafts the call record and the team lead reviews any account flagged for hardship before the next step is decided.

Illustrative example. It describes no real customer.

Data and rules to respect

Follow the RBI directions that apply to your entity, including those on outsourcing, digital lending and fair practices in recovery. An agent is part of your process, so the same rules cover it.
Insurers and intermediaries work within IRDAI regulations, including how customers are told about claims and grievances.
Customer data is personal data under the DPDP Act. Purpose, consent and retention are set before an agent reads a single file.
Report cyber incidents under the CERT-In directions, and keep logs of what each agent read, wrote and sent.
Where data must stay in India or inside your network, use private cloud or on premise deployment.

A plain summary for general guidance. Your counsel gives legal advice and decides how these apply to you.

Questions

From BFSI teams

Can an agent approve a loan or a claim?

We do not set it up that way. The agent prepares and checks the file. The decision, and the reason recorded for it, belong to your credit officer or claims handler.

How do we show an auditor what the agent did?

Every run is logged: the inputs it read, the output it produced, who approved it and when. You can export these logs for internal audit or an inspection.

Which AI model does it use?

AksharAI works with leading model providers, such as OpenAI, Anthropic Claude and Google Gemini, and with open models you can host yourself. The choice is made per project, often driven by where your data may go.

Agents used here