PAYMENT FRAUD DETECTION

Catch payment fraud
before the chargeback

Stop losing 2-5% of revenue to friendly fraud, account takeovers, and synthetic identities. Flag suspicious transactions in under 50ms—before they hit your payment processor.

Reduce chargebacks by 73% on average
Deploy in 4 hours with REST API
No upfront ML training required

Used by payment platforms processing $2B+ annually

Live Transaction Feed
Real-time
$2,450.00FLAGGED
Card Purchase2s ago
Velocity check: 8 txns in 3minRisk: 92%
$89.99APPROVED
Subscription5s ago
Normal patternRisk: 8%
$15,200.00REVIEW
Wire Transfer12s ago
New device + high amountRisk: 78%
156
Flagged today
2.4K
Processed
47ms
Avg latency
$847M
Fraud prevented (2025)
73%
Avg. chargeback reduction
47ms
P95 detection latency
0.3%
False positive rate

Protecting transactions for

PayFlow
NeoBank
LendTech
FinanceHub

THE COST OF DOING NOTHING

Payment fraud is bleeding your business dry

$32B

Lost to payment fraud in 2024 (US fintech alone)

$3.75

Cost per $1 of fraud (fees + operations + reputation)

45 days

Avg. time to detect sophisticated fraud patterns manually

HOW IT WORKS

Detection in three layers

Every transaction goes through velocity checks, behavioral analysis, and ML risk scoring

1

Velocity & Rules Engine

Flag obvious patterns: 10 transactions in 2 minutes, card-not-present from high-risk country, email domain mismatch.

2

Behavioral Anomaly Detection

Compare to user history: first international purchase, 4x normal order value, new shipping address, device fingerprint change.

3

ML Risk Score

Gradient-boosted model trained on 50M+ labeled transactions outputs 0-100 risk score with feature explanations (SHAP values).

FRAUD TYPES WE CATCH

Built for payment platforms & neobanks

Account Takeover (ATO)

Detects credential stuffing, session hijacking, SIM swaps

Login from new device
Geo-impossible travel
Behavioral anomaly

Friendly Fraud / Chargeback Abuse

Flags customers with history of disputed legitimate purchases

Multiple past chargebacks
High-value goods
Digital delivery

Synthetic Identity Fraud

Catches fabricated identities before they accumulate credit

No credit history
Recent SSN issuance
PO Box address

Card Testing & BIN Attacks

Stops automated scripts testing stolen card numbers

Rapid small transactions
Sequential card numbers
High decline rate

DEVELOPER-FIRST

Deploy in hours, not months

Single REST API. Webhook callbacks. No model training required.

POST /api/v1/transactions
Authorization: Bearer sk_live_...
Content-Type: application/json

{
  "amount": 129.99,
  "type": "PURCHASE",
  "userId": "usr_abc123",
  "ipAddress": "192.168.1.1",
  "deviceId": "dev_xyz789"
}

// Response (47ms)
{
  "id": "txn_def456",
  "status": "FLAGGED",
  "riskScore": 0.87,
  "riskFactors": [
    "Velocity: 5 transactions in 8 minutes",
    "New device fingerprint",
    "Amount 3.2x user average"
  ]
}
4 hours
Average integration time
REST + Webhooks
Standard protocols
SDKs
Node.js, Python, Java, Go

WHY FRAUDIES

Built different

FeatureFraudiesLegacy VendorsIn-house Build
Time to deploy4 hours6-8 weeks4-6 months
API response time<50ms200-500msVaries
False positive rate0.3%3-8%10%+
Model training requiredNoYes (60 days)Yes (ongoing)
Monthly cost (at scale)$2,500$15K-50K$80K+ eng cost
Explainable decisionsYes (SHAP)LimitedIf built

TRUSTED BY FINTECH LEADERS

Real results from real companies

"Fraudies caught a synthetic identity ring that would have cost us $380K. The ML explanations helped us understand the fraud pattern and update our KYC process."

SC
Sarah Chen
VP Risk, PayFlow (Series B)
91% chargeback reduction

"We integrated in 6 hours. First week prevented $47K in friendly fraud. The webhook integration was cleaner than Stripe's documentation."

MJ
Marcus Johnson
CTO, NeoBank (Seed)
6 hour integration

"False positive rate dropped from 12% to 0.4%. Our ops team went from reviewing 2,000 alerts/day to 80. Massive efficiency gain."

PS
Priya Sharma
Head of Fraud Ops, LendTech (Series C)
0.4% false positives

Pay for itself in week one

If you're processing $1M+/month, you're likely losing $20-50K to fraud. Our $2,500/month plan typically prevents $150K+ in fraud losses.

WITHOUT FRAUDIES
-$38,000
Monthly fraud losses
WITH FRAUDIES
-$10,250
$2,500 subscription + $7,750 fraud
Calculate your ROI

Stop losing money to fraud

14-day free trial. No credit card required. Cancel anytime.

Common questions

How long does integration take?

Most teams integrate in 4-6 hours. We provide REST API endpoints, webhook handlers, and SDKs for Node.js, Python, Java, and Go. No ML training period required—our models work out of the box.

What's your false positive rate?

Our average false positive rate is 0.3%, compared to 3-8% for legacy vendors. We achieve this through multi-layer detection (rules + behavioral + ML) and continuous model refinement based on your feedback.

Do you support real-time webhooks?

Yes. Configure webhooks to receive instant notifications when transactions are flagged. Typical webhook delivery is under 100ms. We also support batch API calls for historical analysis.

What fraud types do you detect?

We catch account takeover (ATO), friendly fraud/chargeback abuse, synthetic identity fraud, card testing, velocity attacks, and emerging patterns. Our ML models are trained on 50M+ labeled transactions.

How do you handle compliance?

We're SOC 2 Type II certified, PCI DSS compliant, and GDPR ready. Full audit trails are maintained for all decisions. We provide compliance exports for regulatory reporting.

What if I need custom rules?

You can configure custom velocity rules, blocklists, and thresholds via dashboard or API. Our ML models adapt to your specific transaction patterns within the first 30 days.