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Banking, NBFC & lending

Every enquiry called back. Every overdue instalment reminded.

One bounded loop runs the repetitive contact across the loan lifecycle, from a new enquiry to an early-stage reminder. Credit, hardship and settlement never enter it.

Incoming event

  • New loan enquiry
  • KYC document missing
  • Instalment overdue

Orkivanta agent

AI Voice Dialer

  • Qualify
  • Chase
  • Remind

Connected system

CRM · loan system

Scored · promise-to-pay logged

Human owner

Adviser desk / collections supervisor

Decides credit, hardship & settlements

  • Incoming event
  • Orkivanta agent
  • Connected system
  • Completed update
  • Human owner

One bounded loop in Banking, NBFC & Lending, drawn as an example to tune to your own process — not a published client result.

A day in the operation

Four or five moments, one bounded loop.

Leads go cold in the queueApplications stall on paperworkServicing lines clog with simple questionsEarly-stage collections run by handNo single view of the lifecycle
  1. 01 · Acquire

    Qualify the enquiry

    Call a new enquiry back in minutes, work your eligibility questions, and book the qualified ones with an adviser.

  2. 02 · Onboard

    Chase KYC & documents

    Track what a file is missing and nudge for it on a schedule until it completes or times out to a person.

  3. 03 · Serve

    Answer servicing questions

    Look up an EMI date or balance in your system, relay the real figure, and escalate anything that isn't a straight lookup.

  4. 04 · Collect

    Remind, early-stage

    Place a polite, frequency-capped reminder on an overdue instalment and log the promise-to-pay.

  5. 05 · Retain

    Follow up & feedback

    Run a feedback or eligibility-check call from a list you approve and book interested customers back in.

Six agents for Banking & lending

What each one would be configured to do here.

The same six agents we ship, read against this industry. Each panel is an example fit to tune to your process — including the ones where the honest answer is that this is not the workflow to automate first.

  • AI Voice Dialer

    Responds, qualifies and books

    Example fitCall a new loan enquiry back, work your eligibility questions, book the adviser slot

    Works on CRM · loan system · calendar

    Adviser desk takes every booked conversation

    No advice, no quoted terms, no credit decision

    Detail

    Configured against the eligibility questions you define, it qualifies and books. Anything that reads as advice or a credit call routes to a named specialist instead.

    Wrong for If your product needs a human to build trust over several long conversations — a big enterprise sale, a clinical consultation — the agent should qualify and hand off, not close. Point it at volume, not at the relationship.

    See AI Voice Dialer
  • AI Marketing Agent

    Drafts, schedules and reports

    Example fitAn approved content calendar for a product or eligibility campaign

    Works on Content calendar · traffic and ranking data

    Your marketing owner holds the review gate

    Nothing publishes without an approval you control

    Detail

    It drafts and schedules to positioning you have already decided, and reports what each piece did. It will not invent a position for a regulated product, and nothing goes out unapproved.

    Wrong for This is a marketing engine, not a brand strategist. If you have a capable CMO already, it makes them faster — it does not replace their judgement. And it will not invent a positioning you have not decided.

    See AI Marketing Agent
  • AI Meeting Notes Agent

    Captures decisions, closes the loop

    Example fitAdviser meeting notes, action items with an owner, and the CRM record after

    Works on CRM · email draft

    The adviser approves the follow-up before it sends

    Not in a conversation that forbids recording

    Detail

    Routine adviser and internal review calls are where it earns its keep. Keep it out of any conversation your policy says may not be recorded.

    Wrong for If your meetings are confidential in a way that forbids recording — some legal, medical, or HR conversations — do not put an agent in the room. It earns its keep on the routine calls that create follow-up nobody has time to do.

    See AI Meeting Notes Agent
  • AI Data Entry Agent

    Does the work between the work

    Example fitChase a missing KYC document, then move the approved status between your systems

    Works on CRM · loan system · spreadsheets · email · internal APIs

    Onboarding officer receives the file or the stalled exception

    Verifies nothing, approves nothing, changes no terms

    Detail

    It tracks what a file is outstanding, nudges on the schedule you set, and re-keys a status a person already approved. Genuine edge cases escalate with full context rather than being guessed at.

    Wrong for If the task changes shape every single time and has no repeatable pattern, an agent has nothing to learn — a person is cheaper. This pays off on the work that is dull precisely because it repeats.

    See AI Data Entry Agent
  • AI Data Analyst

    Answers questions of your data

    Example fitAsk how the application and collections pipeline is moving, and read the query behind the answer

    Works on Your warehouse, read-only

    Operations or QA lead audits the working

    Sets no policy, no pricing, no limit

    Detail

    Answers arrive with the exact query that produced them, so a number can be checked rather than trusted. Trust here rests on your tables agreeing with each other.

    Wrong for Trust here depends on clean data. If your source tables contradict each other and nobody owns the definitions, the agent will answer faithfully from a mess. Fix the warehouse first, or scope the work to the tables you trust.

    See AI Data Analyst
  • AI Resume Screener

    Ranks resumes with reasons

    Example fitShortlist collections and branch-role applications, with a written reason for each ranking

    Works on Your applicant records

    A recruiter reviews the shortlist and every reason

    Never auto-hires and never silently rejects

    Detail

    It screens against the spec you give it and writes out why each candidate placed where it did. The final call, and the accountability for it, stays with a person.

    Wrong for It shortlists; it does not hire. Screening is where bias and legal exposure live, so the final call — and the accountability for it — stays with a person. If you want a tool that auto-rejects to zero human involvement, we will not build it.

    See AI Resume Screener

Where the boundary sits

Human decides here.

Orkivanta agent

The agent prepares the work

  • Call a new enquiry back
  • Work the eligibility questions you defined
  • Chase a missing document on a schedule
  • Answer a servicing lookup from your system
  • Place a frequency-capped reminder
  • Log the promise-to-pay and route the exception

Human owner

Decisions that stay with your adviser desk

  • Credit decisions and underwriting
  • Settlement negotiation
  • Hardship and disputed cases
  • Anything that reads as advice
  • Identity verification and approval

The loop stops and routes the full context to adviser desk / collections supervisor the moment it reaches credit decisions, underwriting, settlements & hardship.

What changes operationally

What stops depending on somebody remembering.

  • Visibility

    Every action is logged with the reason behind it, so a supervisor can read back what happened and why rather than take an outcome on faith.

  • Less repetitive follow-up

    The callback, the missing document, the reminder — the contact that only works if it happens every time stops depending on somebody remembering.

  • Clear human ownership

    The sensitive decision has a named owner before anything runs, and the agent stops and hands over the full context instead of pressing on.

The detail, in full

Everything above, spelled out.

Open any of these for the long form — the worked examples, the comparison, an estimate of what the work costs today, and the exact wording of what a person keeps.

Every example configuration, stage by stage

Acquire

Qualify the enquiry

Lead qualification

AI Voice Dialer
  1. Trigger

    A new loan enquiry lands from a form

  2. Agent action
    • The Calling Agent calls back within minutes
    • Works the eligibility questions you defined
    • Scores intent 0–100
  3. Systems & record

    CRM · calendar

    Action logged with its reason
  4. Human owner

    Adviser desk

    Owns what happens next

Stops here — It does not advise on products, quote terms, or make an eligibility decision

The full configuration, in words
Trigger
A new loan enquiry lands from a form, portal, or missed call.
Agent action
The Calling Agent calls back within minutes, works the eligibility questions you defined, scores intent 0–100, and books qualified prospects onto an adviser's calendar.
Human owner
Adviser desk — takes every booked, qualified conversation.
Honest limit
It qualifies and books; it does not advise on products, quote terms, or make an eligibility decision. Anything that reads as advice or a credit call routes to a named specialist.
See the AI Voice Dialer

Onboard

Chase KYC & documents

KYC & document chase

AI Data Entry Agent
  1. Trigger

    An application is missing a KYC document

  2. Agent action
    • The Employee Productivity Agent tracks what's outstanding
    • Sends the request through the channel you approved
    • Re-checks the folder
  3. Systems & record

    CRM · spreadsheets · email · internal APIs

    Action logged with its reason
  4. Human owner

    Onboarding officer

    Owns what happens next

Stops here — It does not verify identity or approve an application

The full configuration, in words
Trigger
An application is missing a KYC document, a signature, or a mandate step.
Agent action
The Employee Productivity Agent tracks what's outstanding, sends the request through the channel you approved, re-checks the folder, and nudges on a schedule until the file is complete or times out to a person.
Human owner
Onboarding officer — receives the completed file or the stalled exception.
Honest limit
It chases and files; it does not verify identity or approve an application. Verification and approval stay inside your existing process.
See the AI Data Entry Agent

Serve

Answer servicing questions

Servicing questions

AI Data Entry Agent
  1. Trigger

    A borrower asks about an EMI date

  2. Agent action
    • The Employee Productivity Agent looks the answer up in the system you connected
    • Replies with the real figure
    • Confirms it
  3. Systems & record

    CRM · spreadsheets · email · internal APIs

    Action logged with its reason
  4. Human owner

    Service desk

    Owns what happens next

Stops here — Read-and-relay of information already in your system only

The full configuration, in words
Trigger
A borrower asks about an EMI date, an outstanding balance, or a statement.
Agent action
The Employee Productivity Agent looks the answer up in the system you connected, replies with the real figure, confirms it, and logs the interaction — escalating anything that isn't a straight lookup.
Human owner
Service desk — takes disputes, restructure requests, and anything non-standard.
Honest limit
Read-and-relay of information already in your system only. It does not change a loan, waive a charge, or negotiate terms.
See the AI Data Entry Agent

Collect

Remind, early-stage

Early-stage payment reminders

AI Voice Dialer
  1. Trigger

    An instalment passes its due date in your ledger

  2. Agent action
    • The Calling Agent places a polite
    • Frequency-capped reminder call — or hands off to WhatsApp — confirms intent to pay
    • Captures a promise-to-pay date
  3. Systems & record

    CRM · calendar

    Action logged with its reason
  4. Human owner

    Collections supervisor

    Owns what happens next

Stops here — Early-stage reminders only

The full configuration, in words
Trigger
An instalment passes its due date in your ledger.
Agent action
The Calling Agent places a polite, frequency-capped reminder call — or hands off to WhatsApp — confirms intent to pay, captures a promise-to-pay date, and logs it back to the system.
Human owner
Collections supervisor — owns any dispute, hardship, or repeated non-contact.
Honest limit
Early-stage reminders only. It will not negotiate a settlement, threaten, restructure, or handle a disputed or hardship case — those are not bounded jobs for an agent.
See the AI Voice Dialer

Retain

Follow up & feedback

Re-engagement & feedback

AI Voice Dialer
  1. Trigger

    A loan closes

  2. Agent action
    • The Calling Agent runs a feedback or eligibility-check call from a list you approve
    • Captures the response
    • Books interested customers with an adviser
  3. Systems & record

    CRM · calendar

    Action logged with its reason
  4. Human owner

    Relationship / sales owner

    Owns what happens next

Stops here — It does not cross-sell on advice or make an offer

The full configuration, in words
Trigger
A loan closes, or a lapsed customer becomes eligible for a new product.
Agent action
The Calling Agent runs a feedback or eligibility-check call from a list you approve, captures the response, and books interested customers with an adviser.
Human owner
Relationship / sales owner.
Honest limit
It gathers feedback and books conversations; it does not cross-sell on advice or make an offer. Product recommendations stay with a person.
See the AI Voice Dialer

Across the lifecycle

Measured, not decided

Collections & sales call QA

AI Data Analyst
  1. Trigger

    A batch of recorded collections or sales calls closes for the day

  2. Agent action
    • The Data Analysis Agent reads every transcript against your script and conduct rules
    • Flags the calls that need a human listen
    • Shows the exact lines behind each flag
  3. Systems & record

    Your warehouse, read-only

    Action logged with its reason
  4. Human owner

    QA lead

    Owns what happens next

Stops here — It does not decide misconduct or discipline anyone

The full configuration, in words
Trigger
A batch of recorded collections or sales calls closes for the day.
Agent action
The Data Analysis Agent reads every transcript against your script and conduct rules, flags the calls that need a human listen, and shows the exact lines behind each flag.
Human owner
QA lead — reviews the flagged sample, not the whole day.
Honest limit
It surfaces calls for review; it does not decide misconduct or discipline anyone. That judgement, and the record of it, stays human.
See the AI Data Analyst
  • Incoming event
  • Orkivanta agent
  • Connected system
  • Human owner
  • Where the agent stops
Before, and with Orkivanta

Before

Manual, fragmented — every step waits for a person to get to it.

Before: Loan enquiry, then Manual callback, hours later, then Spreadsheet triage, then KYC chased by hand, then Follow-up missed, then CRM updated late. The gaps between those steps: Waits in the queue; Worked in whatever order it opened; One missing document freezes the file; Nobody notices until the weekly review; Depends on someone remembering.

With Orkivanta

One connected route, ending on a named person.

With Orkivanta: Loan enquiry, then Agent callback in minutes, then Intent scored 0–100, then KYC gap chased on a schedule, then Promise-to-pay logged, then Human handoff on any credit or hardship call, then your adviser desk owns the decision.

Illustrative workflow, not a customer result. Actual outcomes depend on your process, the system access you grant, and execution.

Plan a workflow estimate

A repetitive-work cost estimate from your own numbers — the same transparent arithmetic as the full calculator, not an ROI and not a saving. The defaults are placeholders; replace them with yours.

Estimate this Banking & lending workflow
Monthly repeatable-work cost

₹14,548.80

Annual repeatable-work cost
₹174,585.60
Repeatable hours / month
41.568 hrs

Planning estimate from your inputs — not a quote or expected saving.

See the Calling Agent

What to baseline first

Candidates to scope against on your own systems — not promised uplift.

  • Lead-to-qualified ratio and callback time
    BaselineTarget you set
  • KYC / document completion rate
    BaselineTarget you set
  • Application drop-off before disbursal
    BaselineTarget you set
  • Early-stage promise-to-pay and cure rate
    BaselineTarget you set
  • Servicing contacts deflected from staff
    BaselineTarget you set
  • Cost per interaction
    BaselineTarget you set
You stay in control, and when not to automate this

You set the boundary before anything runs: which numbers it can call and how often, what it is allowed to say, and the exact point at which it must stop and fetch a person. The high-stakes parts of lending — advice, underwriting, credit decisions, settlement negotiation, identity verification — sit outside that boundary by design, not by accident.

Every action is logged with its reason, and a hard kill-switch stops every line at once. In a high-stakes workflow that audit trail is the point: you can show what the agent did, why it did it, and where a human took over. You set the rules the agent runs inside, every action is logged, and sensitive cases route to a named person — we do not make promises about your rules and controls on your behalf.

When not to automate this

Underwriting, credit decisions, settlement negotiation, and hardship or disputed cases stay with trained people. These agents handle the early, repetitive contact and the paperwork around it. The moment a case turns on a credit judgement or a contested balance, a person should already be holding it — and the agent is built to hand it over, not to press on.

Next step

See it on your workflow.

Tell us which workflow you would point an agent at and roughly how much of it there is. We will come back on whether it is a fit — including when the answer is that you should not build it.

  • A demo is a working walkthrough on a scenario like yours, not a deck.
  • A free POC is scoped to one workflow so you can watch it run first — request one and we will agree what it covers.
  • Prefer to check yourself first? The readiness test scores your workflow in six questions and asks for no email.
What would you like?

A working walkthrough against a scenario like yours — not a deck.

This sends a request; it does not book a slot or start a POC. We read every message and reply ourselves.