Zigment
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Case Study
Trust & security
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Jana Small Finance Bank

₹2,50,000, approved and disbursed without leaving the chat.

How Jana Small Finance Bank closed a pre-approved personal loan end to end on WhatsApp, replacing the branch visit and the hundred-field form with an agent that negotiates the terms, computes the EMI, takes the signature and confirms the credit, in the borrower's own language.

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Abstract coral gradient artworkJana Small Finance Bank

3X

Onboarding cost cut threefold, WhatsApp in place of physical meetings

56%

Increase in loan disbursals, from the same approved cohort

9 min

Broadcast to money in the account, without leaving the chat

Jana Small Finance Bank is a scheduled commercial bank in India running roughly nine asset products and ten liability products, sold largely through people rather than through forms. A pre-approved loan still meant a branch visit, a stack of paper and somebody's follow-up list before the money moved.

The slow part started after the credit decision

A customer checking a loan approval on a phone

01

The whole workflow was coordinated by hand.

Calling, SMS and WhatsApp fallbacks were run manually, so an approved customer's next step depended on whether somebody remembered to take it.

02

The context died between three separate systems.

03

Onboarding still lived in a hundred-field form.

An agent that could open the offer, and then close it.

The agent was wired into Jana's core banking system, so the pre-approved amount, the rate and the customer's history were in hand before the first message went out and every step wrote back to the bank's own record, and it had to do six things.

Omnichannel Agents

Broadcast + Consent.

Name, amount and eligibility pre-populated from account data, with opt-in gating built in for RBI and TRAI.

Conversational Intelligence

Loan Term Negotiation.

Terms surfaced live from core banking, with the tenure selector inline and the agent matching the borrower's Hinglish.

Conversational Intelligence

Real-time EMI Calculation.

Monthly EMI, total interest and first payment date computed on the spot, in the thread, never as a PDF redirect.

Omnichannel Agents

Hindi Voice Note.

The borrower asks about prepayment in a voice note and the agent transcribes it, then answers in the same register.

Workflow Orchestration

e-Sign via WhatsApp.

Sanction letter and loan agreement arrive in the chat, signed with an Aadhaar OTP, and the loan enters the disbursal queue.

Workflow Orchestration

Multimedia Documents.

A three-page sanction letter delivered as a PDF the borrower can open without leaving the conversation.

Before Zigment · After Zigment

An approval that used to wait for someone now arrives as a conversation.

USE CASE

The offer

Before Zigment

Sat in a campaign list

With Zigment

Lands as a conversation

USE CASE

The terms

Before Zigment

Explained at a branch counter

With Zigment

Negotiated in the thread

USE CASE

The question

Before Zigment

Waited on a callback

With Zigment

Voice note, answered in Hindi

USE CASE

The signature

Before Zigment

A form, a queue, a wait

With Zigment

Verified inside chat

The approvals were done and the disbursals caught up.

3X

Onboarding cost cut threefold, from moving borrowers onto WhatsApp instead of putting a person in front of them

56%

More loans disbursed from the same approved cohort, on the same credit decisions the bank had already made

9 min

From the broadcast landing to the money hitting the account, start to finish inside WhatsApp

Broadcast at 10:02, terms at 10:04, signature at 10:09, credited at 10:11.

Takeaways

01

A pre-approved offer already belongs to the customer, and sent as a conversation rather than a campaign, the same approved book disburses more on credit decisions the bank has already made.

02

The borrower asked about prepayment in a Hindi voice note and got a Hindi answer in the same thread, with nothing routed to a callback.

03

What made lending expensive was everything bolted on after the credit call, and almost all of those steps came down to somebody waiting for somebody else.

  • Banking and Fintech
  • Onboard and Activate
  • Omnichannel Agents
  • Conversational Intelligence
  • Workflow Orchestration

Your approvals are done, so make them land

A live demo on your own book, with your pre-approved cohort, your rate card, your e-Sign and your core banking.

A bank representative in conversation on a laptop