Support AI for Financial Services
Cut response time by 73% while maintaining compliance
OBJECTIVES
PROJECT TYPE
AI Assistant
A mid-size financial services firm needed to scale customer support without scaling headcount.
15 MIN · NO PREP REQUIRED
VISUAL OVERVIEW
System architecture.
OVERVIEW
A mid-size financial services firm needed to scale customer support without scaling headcount. Their challenge: maintain strict compliance requirements while dramatically improving response times. We built a custom AI assistant that handles 68% of inquiries automatically while ensuring every response meets regulatory standards.
THE PROBLEM
The company's support team was drowning. With a 40% year-over-year growth in customer base, support tickets grew faster than they could hire. Average response time crept from 2 hours to 4 hours, then 6. Customer satisfaction scores dropped.
The obvious solution—hire more agents—faced budget constraints and a tight labor market. They also faced compliance challenges: every customer communication in financial services requires careful documentation and adherence to regulations.
They needed a force multiplier, not just more hands.
CONSTRAINTS
- All responses must be auditable and traceable
- No customer PII can leave their infrastructure
- Must integrate with Salesforce Service Cloud
- Responses must cite specific policies/documentation
- Escalation paths must preserve full context
- Implementation timeline: 6 weeks maximum
DELIVERABLES
What we shipped.
Custom AI assistant trained on 5,000+ support documents
Salesforce integration for seamless ticket management
Compliance review workflow for flagged responses
Admin dashboard for response monitoring and analytics
Escalation system with full conversation context
Training program for support team transition
KEY DECISIONS
How we solved it.
Cloud AI vs. on-premise deployment?
Hybrid approach with on-premise processing for PII
Cloud AI services provided the best language capabilities, but compliance required keeping customer data on-premise. We built a hybrid system that processes queries locally, sends anonymized content to the AI, and reconstructs responses with original context.
Full automation vs. human-in-the-loop?
Confidence-based routing
High-confidence responses (85%+) go directly to customers. Medium confidence (60-85%) queue for quick human review. Low confidence (<60%) route to agents with AI-suggested responses. This balanced automation with quality control.
Retrain AI continuously or periodic updates?
Weekly batch retraining with manual trigger option
Continuous learning risked drift and compliance issues. Weekly retraining with human review of new training data maintained quality while incorporating improvements. Manual triggers allow rapid updates when policies change.
OUTCOMES
Results delivered.
73% faster
Response Time
Average first response dropped from 4.2 hours to 1.1 hours
68%
Automation Rate
Percentage of tickets resolved without human intervention
100%
Compliance Score
Zero compliance violations in first 6 months of operation
54% lower
Cost per Ticket
Reduced from $12.40 to $5.70 per ticket handled
+18 points
CSAT Score
Customer satisfaction improved from 72 to 90
TIMELINE
Project phases.
Discovery & Architecture
Audit existing support workflows, document compliance requirements, design system architecture
Data Preparation
Process and structure 5,000+ support documents, create training dataset, establish evaluation criteria
AI Development
Fine-tune language model, build inference pipeline, develop confidence scoring system
Integration
Connect to Salesforce, build admin dashboard, implement escalation workflows
Testing & Launch
Compliance review, parallel testing with live tickets, team training, production deployment
Ready to build?
Book a call to discuss your project. 15 minutes, no prep required.