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High-Fidelity Synthetic
Fraud Data

Designed for real fraud models. Delivered without lock-in.

WHAT WE DO

Enterprise-Grade Synthetic Fraud Data

IKARAS International builds synthetic fraud
datasets for teams that:

Synthetic data without behavioral realism
leads to false confidence. IKARAS solves
this by modeling fraud as a dynamic system,
not static rows.
Built for banks, fintechs, payment platforms,
marketplaces, SaaS, and analytics teams
that need speed, control, and production-
ready outcomes.
1
Cannot use real customer data
2
Need faster model iteration
3
Require auditability and reproducibility
4
Want realistic fraud behavior, not toy datasets

Our datasets support early prototyping, production-level testing, robustness analysis, and long-term
model improvement, using the same core data generation approach.

WHY IKARAS

What Makes Our Data Different

Most synthetic data focuses on appearance. Rows look statistically plausible, but the behavior underneath is shallow.

We focus on behavior.

Fraud is not a random label.
It involves:
Identities
Timing
Intent
Escalation
Adaptation

The IKARAS FraudSim pipeline models fraud as evolving behavior over time, delivering depth and realism that table-based generators and generic synthesis tools cannot achieve.

How It Works

We don’t need your sensitive transaction history.

We only need the structure and objectives that define your fraud environment.

From there, we generate high-fidelity synthetic fraud data that behaves like your world- safe, labeled, and production-ready.

1. Share Your Schema

Provide your data structure and
key fields.

No raw data. No approvals. No
compliance delays.

2. Define Your Risk Goals

Set fraud rates, scenarios, attack
types, and testing objectives.

We tailor the simulation to your
exposure.

3. We Model Real Fraud
Behavior

Persistent identities. Escalation.
Drift. Coordination.

Fraud is simulated as behavior, not
just a label.

4. Generate & Validate

You receive a fully labeled,
validated dataset, ready for

training, testing, and stress-
testing.

What You Get
More Than a Dataset. A Complete
Fraud Simulation Package.

Every delivery includes:

  • Full transaction dataset
  • Fraud-only subset
  • Validation summary
  • Scenario breakdown
  • Drift & behavioral integrity checks
  • Configuration snapshot (fully reproducible)
  • Run manifest & documentation
  • Executive-ready PDF + HTML report

Audit-ready. Deterministic. Safe to
share internally.

Train for the fraud that hasn’t happened yet.

One Platform.
Fifteen Real-World Fraud Scenarios.

We model 15 distinct fraud scenarios, giving you broader and deeper coverage than almost any synthetic data provider in the market. Every scenario is fully customizable. Adjust the weight, fraud rate, dominance, and overlap to match your exact risk exposure and testing goals.

Account & Identity Compromise

Account Takeover (ATO)
Unauthorized access with device changes, abnormal velocity, and high-risk actions.

Synthetic Identity
Partially fabricated identities that appear legitimate, then diverge over time.

Device/IP Mismatch
Sudden deviation in device fingerprint, IP reputation, or location patterns.

Geo-Impossible Activity
Transactions occurring in physically implausible locations within short timeframes.

Payment & Transaction Fraud

Card Testing
Low-value, high-velocity transactions to validate stolen card details.

Botnet Testing
Automated distributed micro-transactions across multiple accounts.

High-Value Cashout
Rapid escalation to maximize withdrawals or transfers before detection.

Velocity Anomaly
Sudden spikes in transaction frequency or volume.

Chargeback Fraud
Post-transaction disputes reversing completed payments.

Abuse & Exploitation

Friendly Fraud
Legitimate users disputing valid transactions.

Promo Abuse
Exploiting referral bonuses, discounts, or incentives.

Refund Abuse
Manipulating refund policies after receiving goods or services.

Return Fraud
Abusing return systems through counterfeit or repeated cycles.

Coordinated & Networked Fraud

Merchant Collusion
Coordinated fraud between merchants and users.

Triangulation
Three-party schemes using stolen credentials to fulfill third-party purchases.

Pricing

Pay for the Dataset. Not a Platform.

IKARAS pricing is based on scope, complexity, and volume.
No subscriptions. No lock-in. No hidden fees.

What Determines Cost

  • Dataset size
  • Number of fraud scenarios
  • Scenario weightage and overlap
  • Drift and validation depth

Fully configurable to your needs.

What You Get

  • Labeled transaction dataset
  • Configurable fraud mix
  • Validation summary
  • Reproducible configuration files

Delivered in days. Audit-ready.
Integration-ready.

Frequently Asked Questions

Most tools focus on row-level similarity. IKARAS models fraud as evolving behavior with identity persistence, escalation, coordination, and drift. You test detection systems, not just classifiers.
Yes. Scenario dominance, overlap, and drift are configurable, allowing you to stress-test models against future attack patterns, not just historical data.
Yes. Fraud behaviors can overlap within the same lifecycle. Labels represent dominant behavioral regimes, not isolated events.
Yes. Fraud rate, scenario weightage, overlap intensity, and temporal dominance are fully configurable before generation.
Yes. Identities persist across transactions, preserving behavioral continuity and coordination patterns.
Each dataset includes fraud rate checks, scenario distribution validation, identity consistency verification, temporal integrity testing, and internal ML sanity checks.
Yes. Every delivery includes configuration snapshots and run manifests for deterministic regeneration and auditability.
Most datasets are delivered within days. No legal approvals or masking workflows are required.
Yes. All datasets are fully synthetic and designed to support governance, audit, and compliance review.