Fintech Patterns Skill

When to Use

• Customer is in fintech/financial services
• Compliance concerns come up
• Questions about regulatory requirements
• Long conversation challenges (common in financial chat)
• Need case studies from similar customers

Common Fintech Patterns

Pattern 1: Compliance Concern + Pause

Signal: Customer pauses, then mentions compliance Example: "Um, one thing though — we're in fintech, so there's compliance stuff..." Response: Lead with SOC2/audit success stories, show how other fintechs solved it

Pattern 2: Token Cost + Scale Fear

Signal: Growing user base, worried about costs Example: "Our costs are exploding as we scale..." Response: Show ROI of Context Editing, give specific numbers

Pattern 3: "Claude Forgets"

Signal: Users complaining about lost context Example: "By message 15, Claude forgets what we discussed in message 3" Response: Context Editing with persistent facts pattern

Typical Fintech Requirements

1. Compliance: SOC2, GDPR, financial regulations
2. Audit trails: Logging all AI decisions
3. Data residency: Where data is processed
4. Long conversations: Users ask many follow-ups
5. Accuracy: Can't give wrong financial advice

Success Stories

Acme Wealth

• Problem: 40-50 turn conversations losing context
• Solution: Context Editing with persistent facts
• Result: Passed SOC2 audit, 65% token reduction

FinBot (reference customer)

• Problem: Token costs scaling with user growth
• Solution: Rolling summarization strategy
• Result: 70% cost reduction, better UX

Response Guidelines

1. Acknowledge the industry: "Fintech has unique challenges..."
2. Lead with compliance: Always address regulatory concerns first
3. Use case studies: Reference similar customers
4. Be specific: Give numbers, not generalities