Audit & signal mapping
Mapped the existing rules engine's false-positive patterns to find which behavioral and network signals the static rules were missing.
FINANCE · CASE STUDY
GCC Digital Bank cut false positives −40%
Real-time, explainable fraud detection built for a GCC digital bank — cutting false positives 40% while giving analysts a clear reason behind every flag.
- Live within one quarter
- Explainable, not black-box
- Real-time transaction scoring
SentryAI Live−40%false positives
Capabilities
Real-time scoring
Explainable flags
Faster analyst action
Pattern adaptation
The explainable risk queue
The queue compliance analysts see the moment they sign in — sorted by risk, every flag explained.
LIVE QUEUE — SORTED BY RISK SCOREAUTO-REFRESH
TXN-88213Card-not-present, $4,120Velocity anomaly · new device · flagged 00:01 agoHIGH RISK< 1 min
TXN-88209Wire transfer, $980Geo mismatch · needs reviewREVIEW4 min
TXN-88198POS purchase, $62Cleared — normal patternCLEAR14 min
TXN-88190ATM withdrawal, $300Cleared — known locationCLEAR26 min
Every flag ships with the reasons behind it — an analyst clears or escalates, the model never blocks silently.
Why they called us
The existing rules-based fraud engine caught obvious cases but flagged a high volume of legitimate transactions as false positives, and every flag it did raise came with no explanation — compliance analysts had to manually reconstruct why a transaction was blocked before they could act on it.
Replace static fraud rules with real-time, explainable detection compliance teams can act on immediately.
Live within one quarterTimeline
AI engineers + risk/compliance advisorTeam
From audit to production
Why one quarter was realistic — the scope was one model and one compliance workflow, not a core-banking rebuild. Here's the breakdown:
Model build & validation
Trained the real-time scoring model and validated every flag against analyst-labeled outcomes before it touched a live transaction.
Compliance workflow integration
Wired explainable flags directly into the existing compliance tooling — no separate dashboard for analysts to check.
Live rollout & tuning
Rolled out alongside the legacy rules engine, then tuned on real analyst clear/escalate decisions during the first weeks live.
What we delivered
The stack behind the real-time explainable-risk layer.
Real-time explainable fraud model
A gradient-boosted scoring model runs on every transaction in under 50ms, paired with a feature-attribution layer that surfaces the exact behavioral and network signals behind each flag — not a black-box number an analyst has to reverse-engineer.
Python
PyTorch
Kafka
FastAPI
PostgreSQL
Redis
Docker
Grafana
Plus core-banking and case-management integration into the existing compliance stack — the connective work most off-the-shelf fraud tools skip.
The challenge
The existing rules-based fraud engine caught obvious cases but flagged a high volume of legitimate transactions as false positives, and every flag it did raise came with no explanation — compliance analysts had to manually reconstruct why a transaction was blocked before they could act on it.
What we built
We deployed a real-time detection model that scores transactions on behavioral and network signals rather than static rules, with every flag paired to the specific reasons behind it so a compliance analyst can act — or clear a false positive — in seconds instead of escalating.
Core capabilities
RTS
Real-time scoring
Transactions are scored on behavioral and network signals as they happen, not in a nightly batch.
EXP
Explainable flags
Every flag ships with the specific reasons behind it — no black-box scores.
FAST
Faster analyst action
Compliance can clear or escalate in seconds instead of manually reconstructing context.
ADAPT
Pattern adaptation
Detection adapts to emerging fraud patterns rather than relying on static rule sets.
Inside SentryAI
The risk queue compliance analysts use every shift, from sign-in to audit trail.
Main feature — a flagged transaction, explained, not just scored
Dashboard — false positives & review time
Login — compliance portal access
Detail — explainable risk score
Audit log — analyst actions
The outcome
False positives fell 40%, driven as much by faster, more confident analyst action on explainable flags as by the model's raw detection rate.
−40%false positives
Livewithin one quarter
3AI systems shipped
What the compliance team is saying
Straight from the team reviewing flags every day.
“Our old rules engine flagged everything and explained nothing so every case meant an analyst reconstructing the story from scratch before they could clear or escalate it. What Bounce shipped scores transactions in real time and hands us the actual reasons behind a flag — velocity or device or geo or whatever tripped it. That's what changed our review time not just a 'smarter' model.”
Fatima NoorRisk & Compliance Manager, Financial ServicesFrequently Asked Questions
No — every score is a prioritization and explanation signal. A compliance analyst clears or escalates each flag; the model never freezes an account on its own.
Each score ships with the specific behavioral and network signals that drove it — velocity anomalies, device mismatches, geo deviation — not just a single opaque number.
Live within one quarter, covering the detection model build and the compliance workflow integration — not a pilot running in parallel with the old rules engine.
Detection adapts to emerging patterns rather than relying on a static rule set that has to be manually rewritten every time fraud tactics change.
No — it removes the manual reconstruction work behind every flag, so analysts spend their time acting on real risk instead of reverse-engineering why a transaction was blocked.
◆ Let's build
Ready to put AI to work in your industry?
Tell us your challenge. We'll come back with a concrete, no-obligation plan and a live demo of what's possible for your team.
- Free AI auditWe map the highest-ROI AI opportunities across your workflows.
- Prototype in weeksA working proof-of-concept on your real data before you commit.
- One accountable teamStrategy, models, data and deployment — end to end.
120+ teams shipped across 6 industries
Book a free demo
Reply within 1 business day · No obligation.