Governance

Deploying Compliance-Secure Conversational AI in Retail Banking

Designing and launching a generative customer service platform meeting EU AI Act High-Risk systems criteria and strict data privacy regulations.

The Challenge

The client aimed to leverage LLM-based customer service agents to handle account inquiries and support queues. Under the new EU AI Act guidelines, financial AI tools interacting with customer portfolios are classified as High-Risk systems. This requires absolute transparency, explainable responses, drift monitoring, and strict GDPR data governance before deploying to production.

Architecture and Operational Alignment

AI Governance Compliance Structure

AI Act Data Quality Model Safety Explainability Bias Audit GDPR Filtering Drift Monitor Guardrails RAG Linage Decision Logs

The Solution

We established an AI governance model with automated prompt testing, compliance check-gates, and real-time response quality monitoring. An active filtering pipeline checks user requests and model replies for bias, toxic language, or PII leakage, blocking responses immediately if they violate security policies. LLM outputs are linked to audit logs to ensure full explainability during regulatory reviews.

LLM Token Usage Distribution by Service Area

Account Queries
58% (58% Volume)
Transaction Audits
24% (24% Volume)
General Help Desk
10% (10% Volume)
Compliance Reviews
6% (6% Volume)
Model Evaluations
2% (2% Volume)

Performance Metrics (KPIs)

Key Performance Indicator (KPI) Target Actual Result Status
Customer Satisfaction (CSAT) > 15% increase +22% CSAT Target Exceeded
Automated Query Resolution > 60% resolution 68% resolved Target Exceeded
Response Output Latency < 1.5 seconds 1.1 seconds Highly Responsive
Compliance Audit Rate 100% logging 100% logged Perfect Compliance

Customer Query Resolution Channels

Self-Service Chatbot Agent Handover Interactive Voice (IVR) Q1 202630%50%20%Q2 202650%35%15%Q3 202668%22%10%
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