For those building AI agents in Fintech, understanding design patterns is key.
Choosing the right one for a given problem set can deliver the best results
1. The Expert Pattern 🎓
The specialist with in-depth knowledge.
Perfect for structured tasks like tax calculations or accounting processes where rules stay constant and data is well-defined.
2. The Validator Pattern ✅
The quality-checker to ensure accuracy.
This pattern shines in scenarios where accuracy is non-negotiable, like validating financial API responses or user-submitted forms for submission and compliance standards.
3. The Task Splitter Pattern 🔄
The organizer dividing tasks into manageable parts for precise execution.
Excels in multi-stage workflows like loan processing, where each step (credit check, income verification, risk assessment) needs individual attention.
4. The Delegator Pattern 🎯
The matchmaker assigning the right agent for the job.
It's the master of routing tasks to specialized agents based on specific criteria. Think of fraud detection systems where different types of transactions require different levels of scrutiny.
5. The Human-AI Collaboration Pattern 🤝
Keeps humans in control for reviewing critical outputs.
Essential for high-stakes operations like final loan approvals, large transactions, or account privilege changes where human judgment and accountability are crucial.
6. The RAG (Retrieval-Augmented Generation) Pattern 📚
Combines AI reasoning with real-world data sources.
Perfect for customer-facing applications like intelligent support from Orin like AI agents.
Robo financial advisors, giving accurate, up-to-date guidance on Fintech products.
As you might be aware these patterns aren't one-size-fits-all.
But you can adapt and combine building blocks to meet your specific project needs.
Which of these #AIAgents patterns would work best for your #Fintech app?
Article by
Peter H
Customer Success
Published on
Jan 20, 2025
