AI customer support agent for banking that resolves tickets — not just routes them
Production AI support agent case study: Solace Bank cut average resolution from 18 hours to under 2 minutes for 40% of volume with compliance guardrails and core banking API integration.
Key outcome
9×
Faster average resolution
40%
Autonomous resolution
9×
Faster resolution
4.7/5
CSAT
0
Compliance violations
Before
18-hour average first-response time across 2,400 monthly tickets, rising abandonment, and Tier-2 costs of $40–$80 per escalation.
After
Sub-2-minute AI-first resolution for 40% of tickets, CSAT 4.7, zero compliance violations, and 38% lower Tier-2 cost.
01 — Problem
The challenge
Solace Bank’s digital support volume was growing 22% per quarter while headcount lagged. First-response times stretched to 18 hours. Customers abandoned chats; agents burned out on repetitive work — balance inquiries, statement requests, card freezes, and PIN resets — that made up ~60% of ticket volume.
Every Tier-2 escalation cost $40–$80 in agent time. Leadership had piloted a generic chatbot that could only deflect FAQs and create more tickets. They needed an AI customer support agent wired into core banking systems — one that actually resolves requests under strict financial compliance, audit logging, and PII controls.
The brief to Wilayah Softworks: ship a production AI agent for banking support, not a demo that answers “what are your hours?”
02 — Research
What we learned
We analyzed 14 months of transcripts across 28,000 tickets to cluster resolvable intents, edge cases requiring human judgment, and the exact core-banking API calls each high-volume category needed. Parallel compliance workshops defined hard boundaries: what the agent may never say, never execute, and must always escalate.
Evaluation criteria included containment rate, false-resolution risk, GDPR/PII handling, and time-to-human handoff. We benchmarked rule-based IVR, off-the-shelf AI chatbots, and a retrieval-augmented agent architecture. Only the RAG + tool-calling approach could ground answers in Solace policy documents while executing authenticated banking actions.
We also designed an offline evaluation harness with golden transcripts so every model or prompt change is regression-tested before production — critical for AI customer service in regulated finance.
03 — Solution
What we built
We built a production AI support agent connected to Solace’s core banking APIs. It autonomously resolves balance inquiries, statement delivery, card freezes, and PIN resets within compliance guardrails:
• PII masking and field-level redaction in logs • Full audit trail for every tool call and customer utterance • Human escalation with full context handoff in under 30 seconds • Retrieval-augmented policy answers so updates propagate in hours, not sprints • Observability with tracing, containment dashboards, and weekly quality reviews
The agent is model-agnostic behind a tool interface — Solace can swap LLM providers without rewriting banking integrations. Guardrails block account-opening advice, credit decisions, and any action outside the approved tool set. This is conversational AI for customer support designed for banks: resolve first, escalate cleanly, never invent policy.
Technology stack
Measurable results
Outcomes validated with the client operations team after launch — not vanity metrics.
- 40% of support tickets resolved autonomously — no human involved
- 9× faster average resolution time (18 hours → under 2 minutes)
- CSAT improved to 4.7/5.0 — above the human-only 4.4 baseline
- Zero compliance violations across a 180-day audit window
- Tier-2 escalation cost reduced by 38% in the first quarter
- Average handle time on remaining human tickets fell 22% via richer context handoff
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