AI CUSTOMER AGENTS, BUILT AROUND YOUR BUSINESS
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HOME/INDUSTRIES/BANKING/FRAUD AND DISPUTE INTAKE
FINANCIAL SERVICES / WORKFLOW GUIDE
BANKING & LENDING

Fraud and dispute intake
with an AI agent.

Explain published reporting steps and capture context for a secure review by the fraud or disputes team.

See the sample chat Back to Banking
WORKFLOW / FINANCIAL SERVICESFraud and dispute intake
CUSTOMER AGENT / CHATBHIDU
THE CUSTOMER MOMENT

A repeatable question.
A considered response.

Explain published reporting steps and capture context for a secure review by the fraud or disputes team. The agent should answer from the organization’s approved material, show where its answer came from, and route anything it cannot safely resolve.

HOW THE WORKFLOW CAN RUNHUMAN OVERSIGHT / BUILT IN
01
Understand the request

Identify intent, gather only the context the workflow needs, and avoid asking for sensitive details in an unsecured chat.

02
Use approved business knowledge

Retrieve relevant information from sources such as Approved product terms and Application checklist, with a clear citation or next step.

03
Resolve, guide, or hand off

Follow the organization’s defined procedure. Leave decisions, exceptions, and live-system actions to authorized people unless a verified integration permits them.

BUSINESS OUTCOMESMEASURE THE CHANGE ↘
WHAT THIS CAN HELP IMPROVE

Make the work
more measurable.

These are goals to test in a pilot, not guaranteed results. Your baseline, content quality, channel mix, integrations, and handoff rules all matter.

  • 01Make published product and process information easier to navigate.
  • 02Route personal, sensitive, and decision-dependent requests to secure channels.
  • 03Give service teams a consistent intake summary for follow-up.
TRACK THESE SIGNALSFirst-contact resolutionSecure handoff completionRepeat contacts for policy/process questions
ILLUSTRATIVE ROI PLANNEREDIT EVERY ASSUMPTION ↘
YOUR VOLUME / YOUR COSTS

Model the capacity
this workflow could return.

Adjust the assumptions to match your operation. The output is a planning scenario—not a promise of savings.

YOUR ASSUMPTIONSEDIT TO MODEL
ILLUSTRATIVE MONTHLY MODEL BASED ON YOUR INPUTS
Potential service capacity returned40.0 hours / month
Potentially agent-resolved conversations400
Estimated capacity value$1,200
Estimated net capacity value after platform costAdd monthly fee
Modeled ROIAdd monthly fee

Planning estimate, not a savings promise. Assumes the selected share is fully resolved without agent handling. Capacity value is not guaranteed cash savings; excludes implementation, AI usage, support, and integration costs.

TRY THE INDUSTRY SCENARIOGUIDED CHAT / SOURCE / HANDOFF ↘

See the response
in context.

This sample uses illustrative industry content. It is not connected to a live customer system.

GUIDED AI AGENT DEMO
INDUSTRY / FINANCIAL SERVICES

Banking
customer agent

A sample conversation plays when you reach this panel. Pause it, ask your own question, or listen to an agent reply.

0 / 4Guided demo paused
TRY A QUESTION
Sample company and content. Not connected to live systems.
b.
ChatBhidu AI agent Banking & lending / sample scenario
PREVIEW
TODAY · SAMPLE CONVERSATION
b
CHATBHIDU AIAGENT

Hello. I can help explain products and published service processes.

CHATBHIDU AGENT PREVIEWANSWER SOURCE HANDOFF
← Return to Banking use casesDiscuss a pilot for this workflow