When things break, you want receipts
Tahin built and scaled risk systems for the past decade at leading fintechs like Stripe, Mercury, and Interac.
Most fintechs say they're building event-driven risk systems. In reality? They're chaining REST APIs and calling it a day. That's not event-driven—that's request/response with better marketing. A true event-driven risk system reacts the moment something happens: a payment attempt, a login, a session switch. It's about wiring your system so that events drive decisions—automatically, asynchronously, and scalably. That means emitting immutable events when state changes, consuming those events in dedicated, purpose-built processors, and designing your services to be decoupled from each other.
Why does this matter? Because in risk, timing is everything. Fraud happens in milliseconds. If your system only checks risk after a user action completes—or worse, once a batch job runs—then you've already lost. With true event-based architecture, you can take action while the event is unfolding. Want to challenge a login based on device risk before session creation? Trigger a step-up auth based on real-time velocity? You can't do that unless your architecture is actually listening, not polling. Yes, infra costs can go up. But that's the price of being reactive at scale—and with the right design, you control cost by isolating consumers, not flooding them.
Event logs aren't just for real-time decisioning. They're your forensic source of truth. When losses happen—and they will—you need to know exactly how. Event-based systems give you that. You can replay the chain, run simulations, audit decisions, and tune your rules off real sequences, not guesses. You can build shadow pipelines to evaluate new models live without deploying them. Try doing that with a monolith and some scheduled scripts.
When things go wrong
Let's talk about when things go wrong—because they always do. Someone bypasses a check. A rule fires too aggressively. You lose money, or worse, a customer. With traditional architectures, incident response means digging through fragmented logs, stale dashboards, and hand-wavy assumptions. But in an event-driven system, you have a full audit trail. You can reconstruct the exact timeline of what happened—down to the millisecond. You can attribute loss to specific attack vectors, identify what decision logic triggered, and diagnose if it was a rule failure or system design flaw.
This isn't just useful—it's essential. Clean post-mortems lead to better models, better policies, and better fraud strategy. Without this level of traceability, your team is just guessing. With it, you're learning. Fast. That's how modern risk teams turn incidents into leverage.
Most "Risk Engines" Are Held Together With Duct Tape
If you grew quickly, it is likely that your existing risk engine is held together with duct tape. This is probably because your engineers were too busy building product features and scaling your infrastructure for the growth you have been experiencing. The didn't have time for "back office" tasks like building a robust risk engine. But now you are growing and you are starting to see the limitations of your existing risk engine.
Here's the problem with the batch-job-and-API band-aid: it creates fragile, opaque systems. Polling every few seconds? You'll miss signals and burn resources. Tightly coupled API flows? They break the moment one service fails or times out. You can't tune these systems easily, and you definitely can't explain your decisioning logic to auditors or regulators. Most importantly, they scale poorly—complexity creeps in fast, and suddenly your "MVP risk engine" becomes an unmaintainable mess. We've seen it. We've been called in to fix it.