Let's integrate AI Agents in Event-Sourced Systems
Official Schedule Context
- Date/time: 2026-07-01 · 11:40am-12:00pm
- Track/room: AI in Finance · Track 3
- Speaker(s): Divakar Kumar
- Session type/status: session · confirmed
Official Description
Fraud detection has always been a race against time. In traditional event-sourced systems, every
transaction, login, or transfer is captured as a sequence of immutable events. These events tell a
clear story — but only after the fact. What if events could do more than just record history? What
if they could talk back? In this talk, we’ll explore how agentic event-driven systems transform
fraud detection. Imagine every PaymentInitiated, LoginAttempt, or DeviceChanged event not just being
logged, but immediately consumed by an autonomous Fraud Detection Agent. This agent correlates
events across accounts, reasons over historical event streams, and generates new events like
SuspiciousActivityFlagged or TransactionHeldForReview. Through a real-world inspired use case in
banking and digital payments, we’ll show: - How event sourcing provides the perfect memory layer for
fraud detection agents - Patterns for agents to safely inject new domain events without violating
invariants - How to avoid runaway feedback loops when multiple agents interact (e.g., fraud +
compliance + customer service agents) - Governance, auditing, and explainability challenges when
autonomous agents take part in mission-critical workflows By the end of this session, you’ll see how
event-driven DDD systems evolve when agents stop being passive consumers and start actively shaping
the event stream — turning fraud detection from a reactive process into a proactive, adaptive
defense.
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