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Industry solution — Financial Services

Handle 15K+ Daily Account Inquiries Autonomously

Eliminate tier-1 support bottlenecks with a conversational AI agent for balance checks, transaction history, and account management — fully self-hosted in your cloud.

Intelina Voice· Phone

Balance, transaction and card actions over the phone, with identity verified before any account data is read out.

Intelina Desk· Web chat

In-app chat answering statement and fee questions from live account APIs, with disputes raised as tickets for a human.

85%+
Support Reduction
$2M+/yr
Potential Savings
100%
24/7 Availability

Figures on this page are planning targets and typical volume distributions for the sector, not measured results from a named customer. We size them against your own numbers during the demo.

The Tier-1 Support Overload

  • Repetitive balance and transaction queries
  • 24/7 support requirement across time zones
  • Compliance-heavy authentication flows
  • Agent burnout from monotonous tasks
Customer
Menu or queue
Dead end
Contact mix

Where the volume actually goes.

Before deciding what to automate, it helps to see what people are actually contacting you about — and which module is the right home for each slice.

31%Balance and transaction lookupsBoth modules

TodayTier-1 agent reads it off a screen

19%Card actions — freeze, replace, activateIntelina Voice

TodayAuthenticate, then transfer

17%Statement and fee explanationsIntelina Desk

TodayLong chat with a human

14%Payment scheduling and confirmationsBoth modules

TodayManual, error-prone

11%Disputes and fraud reportsBoth modules

TodayShould reach a specialist fast

8%Product and rate questionsIntelina Desk

TodayAnswered inconsistently

The approach

Secure self-service that never sleeps

01

Verifies identity safely

Built-in, configurable authentication flows confirm the caller before any account data is shared.

02

Answers from live account data

Balances, transactions, and statements are retrieved in real time — accurate to the second.

03

Runs entirely in your cloud

No third-party AI vendors. Sensitive financial data never leaves your own infrastructure.

04

Flags and escalates exceptions

Disputes and fraud signals are routed to the right team with the full context attached.

What the agent handles

  • Balance & transaction lookups
  • Card activation, freeze & replacement
  • Payment scheduling & confirmations
  • Fraud reporting & dispute intake
Playbooks

What each module actually does here.

Not capabilities in the abstract — the specific flows, in order, with the primitives each one relies on.

Intelina Voice

Phone · AI voice agents + customer CRM

Authenticate before a single number is spoken

TriggerAny request that touches account data

  1. 1The caller is matched against your customer records by number
  2. 2Your verification step runs as a tool call before the agent reads anything back
  3. 3Failed verification routes to a human rather than degrading to partial answers
read_customerhttp_webhook → verificationescalate

Card actions completed on the call

TriggerCaller wants a card frozen, replaced or activated

  1. 1The agent confirms which card from the customer record
  2. 2It calls your card platform and reads the result back
  3. 3The action is deduplicated by conversation, so a retry cannot issue two cards
http_webhook → card platformidempotent execution

Fraud goes straight to a specialist

TriggerFraud, dispute or unauthorised-charge language

  1. 1Escalation fires immediately instead of continuing self-service
  2. 2The specialist picks up with the transcript and the account context already loaded
  3. 3The intent and the escalation are both recorded on the call log
escalatecall logs

Intelina Desk

Web chat · AI chat + ticketing tool

Statement questions from the real ledger

TriggerCustomer asks about a charge in the app

  1. 1A registered endpoint returns the transaction history for the signed-in user
  2. 2The whitelist keeps everything except the fields you named out of the model
  3. 3The answer cites the actual line item rather than describing fees generically
data endpointsfield whitelist

Rates and terms, grounded in your documents

TriggerProduct, rate or eligibility question

  1. 1The knowledge base is searched over the terms and product sheets you uploaded
  2. 2Answers stay inside what those documents say
  3. 3Anything unanswerable is logged as a knowledge gap for your team to close
knowledge baseknowledge gaps

Sensitive actions wait for a supervisor

TriggerA request the AI could action but shouldn't unilaterally

  1. 1The action enters the approval queue instead of executing
  2. 2A supervisor approves or denies with the full conversation in view
  3. 3Both the request and the decision land in the audit log
approval queueaudit log
Integrations

What it plugs into.

Every connection is something you register in the dashboard — no bespoke integration work on our side.

Core banking / ledger

Registered data endpoint over HTTPS with a short-lived signed token

Card management platform

HTTP webhook tool with idempotency keys

Identity verification

HTTP webhook tool called before any data is read out

Fraud and dispute case system

Escalation plus webhook to open the case

Mobile and web app

Widget script tag reading your existing session

Guardrails

What it refuses to do.

The limits that matter in this sector, enforced by configuration rather than by prompt wording.

Verification before disclosure

Account data is only read back after your own verification step returns success as a tool call.

No payment data stored

Card and payment values are fetched live and never persisted; audit entries record the call, not the payload.

Actions run exactly once

Payments, freezes and disputes are deduplicated per conversation, so a retry replays the original result.

Approvals on the sharp edges

Any action you classify as sensitive routes through a supervisor before it executes.

Rollout

How this actually goes live.

Read-only first, writes behind approvals, then widened once the record justifies it. No big-bang cutover.

  1. 01Days 1–3

    Wire identity and verification

    Register the verification endpoint and connect customer identity — imported records for voice, your session endpoint for chat.

  2. 02Week 1

    Read-only first

    Go live answering balance, transaction and statement questions. No mutating actions are enabled yet.

  3. 03Week 2

    Add the safe writes

    Enable card freeze and payment scheduling behind the approval queue, with idempotency keys on every submit.

  4. 04Weeks 3–4

    Security review

    Walk your reviewer through tenant isolation, token lifetimes, field whitelists and the audit trail before widening access.

  5. 05Ongoing

    Relax deliberately

    Use the approval history to decide which actions have earned automatic execution, and which stay gated.

Measurement

What to hold it accountable to.

Each target maps to something the product already reports, so nobody has to build a spreadsheet to find out whether it worked.

Metrics, current typical state, target, and where each is reported
MetricTypically todayTargetReported by
Tier-1 volume deflectedAgents handle most of it85%+ of routine inquiriesTicket volume by category, plus call log escalation rate
Average handling timeMinutes, including holdSeconds for lookupsCall duration and ticket time-to-resolution
Data exposure surfaceAgents see whole recordsOnly whitelisted fields reach the modelPer-endpoint field configuration and audit log
Duplicate or double-executed actionsA real risk on retriesZeroIdempotency replays recorded on the action
Projected outcomes

What success looks like

85%+
Tier-1 volume deflected

Routine inquiries handled end to end by the agent.

$2M+/yr
Projected savings

From reduced agent load and faster handling.

100%
Self-hosted & compliant

Data stays in your cloud, under your controls.

Customers get instant, secure answers — and your agents stop drowning in repetitive balance checks.

Financial Services questions

What buyers in this sector ask first.

Yes. Every service is containerised and the voice module deliberately runs its own speech model rather than renting one, so self-hosting stays a real option rather than a slide.

See this running on your own financial services data.

Bring one line or one queue and your real numbers. We will size the plan against them on the call rather than quoting the targets on this page back at you.