ML · Risk

Global fraud models
don't speak
Indonesian.

A real-time fraud scoring system trained on local fraud patterns QRIS payment chains, e-wallet transfers, card number attacks, and the scam scripts that actually circulate here.

Most fraud tools were built for Western payment systems. They miss the patterns that matter in Indonesia: chained QRIS transfers (where fraudsters move money through Indonesia's national QR payment network in rapid steps), layered e-wallet movements across GoPay, OVO, and DANA, and social engineering scams spread through WhatsApp. We built a scoring system that learns from real Indonesian transaction data and explains every decision in plain language so your compliance team can act on it.

A fraud system that doesn't know your market
isn't protecting it.

Most fraud systems flag transactions based on patterns from other countries. They miss local tactics, block legitimate customers, and bury your compliance team in false alerts while the real fraud slips through unnoticed.

5x

False positive rate

Generic models flag five legitimate transactions for every real fraud case wasting analyst time on false alerts.

0

Local pattern coverage

QRIS payment chains, e-wallet transfers, and local WhatsApp scams are invisible to models built for other markets.

0

Explainability

Black-box scores with no clear explanation behind them leave compliance teams unable to justify decisions to OJK (Indonesia's financial regulator) or to customers.

21%

Customer friction

One in five falsely blocked Indonesian digital banking customers switches providers within 30 days, taking their balance with them.

Five steps.
Four happen in under 100ms.

Your fraud team stays in control setting risk thresholds, approving updates, handling escalations. The scoring runs automatically on every transaction, in real time, without slowing down your customers.

Hover a step to see it in action
Ingest , connecting to banking and payment systems Score , real-time risk scoring in under 100ms Explain , plain-language reasoning for flagged transactions Escalate , routing high-risk cases to analysts Learn , system learning from analyst feedback
01
Ingest
Connected to your banking system or payment platform to receive transactions as they happen.
02
⟳ auto
Score
Each transaction gets a risk score in under 100 milliseconds faster than the payment itself completes.
03
⟳ auto
Explain
Every flagged transaction comes with a plain-language explanation of why it was flagged.
04
⟳ auto
Escalate
High-risk cases sent to the right analyst with all the context they need to act quickly.
05
⟳ auto
Learn
The system learns from analyst feedback. New fraud patterns are picked up in days, not months.

Every score comes with a reason. Your compliance team can defend every decision.

What your team actually sees.

Live dashboard , risk scores, flagged transactions, and plain-language explanations at a glance.

Fraud Detection dashboard showing real-time transaction scoring, alert queue, and explainability panel

Less noise.
More caught fraud.

Pillar
Before
After
Detection
Local fraud patterns missed
Indonesia-trained scoring
False positives
5x false alert ratio
60% reduction
Latency
Delayed batch scoring
Under 100ms, real-time
Compliance
No explanation behind decisions
Full audit trail
  • 60% fewer false positives

    Your analysts spend time on real threats instead of clearing false alerts. Fewer legitimate customers get blocked.

  • Sub-100ms scoring speed

    Risk decisions happen before the transaction completes. Your customers don't notice a thing.

  • 100% explainable decisions

    Every score comes with a clear reason. Your compliance team can explain every blocked transaction to OJK (the regulator) or to the customer.

  • Days to learn new patterns

    When fraud tactics change, the system adapts in days not the months it takes to update a vendor's model.

caught.

Show us your false positives.
We'll show you what local scoring catches.

A 30-day pilot using a sample of your past transactions. We score them with our system, compare results to what you have today, and show you exactly where local patterns make the difference before you commit to anything.

30-day pilot

Historical scoring assessment

We re-score 30 days of your past transactions and show you the false alerts and missed fraud with no impact to your live systems.