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Case study · Banking · Conversational AI

Retail banking self-service at a regional bank — conversational AI across servicing journeys

A regional bank wanted to move balance, transfer, card-controls and dispute-intake calls to self-service without hurting NPS or falling out of FFIEC posture. pronix.ai deployed Kore.ai Agent Platform on voice and mobile — 36% containment and clean audit.

Client
Regional bank, 2.3M retail customers
Industry
Financial Services
Platform
Kore.ai Agent Platform · Amazon Connect · Fiserv DNA
By pronix.ai Strategy Practice8 min readQ1 2026
36%
Containment on top-4 servicing intents
-52%
Dispute intake AHT
0
enterprise-security / FFIEC findings
+8
Digital NPS

*Representative outcome; results vary by client, scope and platform configuration.

The challenge

Retail servicing was 62% of contact volume with four repetitive intents. Prior IVR self-service capped at 14% containment. FFIEC and enterprise-security posture meant every new self-service intent had to be reviewed for authentication rigor and dispute-window handling.

Our approach

Step 01

Strong-auth first

Voice biometrics with device-signal step-up, KBA fallback, and hard escalation on any dispute involving fraud — never a self-serve path around a fraud claim.

Step 02

Core banking tool layer

Idempotent tool calls into Fiserv DNA for balances, transfers and card controls with full audit journaling.

Step 03

Dispute intake as guided form

Bot captured structured dispute intake to Reg E timing, then handed to a specialist queue with all fields pre-filled — cut intake AHT in half.

Step 04

Model risk management pack

Documented prompts, evaluation harness and change-log delivered to model risk before go-live — approved in one cycle.

For Head of Digital BankingFor Head of Contact CenterFor CISO

Illustrative case study. Scenarios, metrics, quotes and client details are representative composites based on Pronix engagements and industry benchmarks unless a named client is shown with written consent. Outcomes vary by client, scope, data quality and platform configuration. Nothing on this page is a guarantee, warranty or professional advice. See our Terms of Use for the full disclaimer.

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