Product

Rules Engine

Author, test and deploy custom compliance rules without engineering changes. Version every rule, and simulate it against real transaction history before it ever affects a live decision.

The problem

Compliance logic buried in developer code goes stale

In most fintechs, compliance logic lives in developer code. Changing a threshold means a ticket, a sprint, and a deploy — so rules go stale, and compliance teams can't respond to new typologies or regulatory shifts at the speed those changes demand. Worse, no one can prove which version of a rule was in force when a given decision was made.

Without a rules engine

  • Compliance raises a threshold change → files a Jira ticket

  • Engineering picks it up in the next sprint (days to weeks)

  • Change goes through review and deploy pipeline

  • New typology is already established before the rule fires

  • No record of which threshold was in force on any given date

With Fintegrity's Rules Engine

  • Compliance opens the policy builder directly

  • Rule drafted and simulated against 30 days of history

  • False-positive rate checked before going live

  • Rule activated with an effective date in hours

  • Every decision references the exact rule version in force

How it works

Draft. Simulate. Activate. Version.

Fintegrity gives compliance teams a no-code policy builder. Rules are defined in a versioned schema with conditions, an action (flag / review / block), and effective dates. Engineering sets up the integration once; after that, the compliance team owns the rules.

Versioning

Effective dates and full version history

Rules are never silently overwritten — old versions are retained and queryable, and every decision references the exact rule version that produced it.

When a regulator asks "what rule was in force on this date?", the answer is on record.

Simulation

Test before it touches a customer

Before a rule goes live, run it against your last 30 days of transactions to see how often it would have fired, on which transactions, and an estimated false-positive rate — so you tune before alerts pile up.

Speed

Hours, not weeks

Because rule changes do not require code, compliance moves at the speed of the threat, not the release calendar. Engineering sets up the integration once; after that, the compliance team owns the rules.

Alert quality

Simulation kills alert fatigue before it starts

Alert fatigue is the silent killer of compliance programs — too many low-signal alerts, and the real ones get buried. Simulation lets you start narrow and tune deliberately, keeping signal high and your team focused on what matters.

Because the simulation runs against real historical transactions (not synthetic data), the results reflect your actual customer population — not an approximation. A rule that would have fired 4,000 times in 30 days on real data needs tuning before it goes live.

Example simulation result
RuleAmount > ₦2M in any 24h window
PeriodLast 30 days
Would-fire count2,841 times
Sample hits12 shown
Est. false-positive rate94%
RecommendationRaise threshold or add counterparty filter

Simulation result before activation. Compliance team tunes threshold to ₦5M — estimated false-positive rate drops to 18%. Rule goes live the same afternoon.

See how Fintegrity evaluates transactions in real time

We'll show you the policy builder, run a live simulation against transaction history, and demonstrate a rule going from draft to active without a single engineering change.