BANKING (RETAIL) CASE STUDY
Cut transaction dispute resolution time by 40% for a regional retail bank
Delivered an AI-driven dispute resolution workflow that auto-retrieves data, checks policy, fills forms, tracks cases, and updates customers in real time.
40% faster
25% lower ops cost
30% higher CSAT
Banking (Retail) Case Study
THE CHALLENGE
What was holding them back
Operational pain
Manual investigations took too long across systems.
Business risk
Slow resolutions drove dissatisfaction and churn risk.
Why tools failed
Multi-step handoffs created delays, rework, and cost.
CLIENT SNAPSHOT
About the client
Industry
Banking (Retail)
Geography
Regional
Service
AI & Automation
Existing Tools
Multi-system, manual investigation flow
THE SOLUTION
Our Banking (Retail) Solution
Automated Evidence Collection
- Pulls transaction data from connected internal sources.
- Organizes evidence into case-ready summaries.
Policy and Eligibility Checks
- Matches dispute type to policy rules automatically.
- Flags exceptions early to reduce back-and-forth.
Assisted Form Filling and Submissions
- Auto-fills required dispute forms from retrieved data.
- Reduces manual entry errors and missing fields.
Case Tracking and Workflow Orchestration
- Moves cases through stages with clear ownership.
- Maintains timestamps for every step and action.
Customer Updates and Communication
- Sends real-time status notifications during investigation.
- Keeps customers informed with fewer inbound follow-ups.
THE IMPACT
Measurable Results
40%
Speed
faster dispute resolution from intake to closure
25%
Cost
lower operational cost per dispute case
30%
Customer Experience
higher post-resolution satisfaction score
100%
Transparency
real-time status updates during case progress
✓
Time to Value: 4–6 weeks to first measurable improvements (benchmark)
TECH STACK
Technologies Used
Agentic AI
AI + Automation
Integrations
Role-based access
