Financial Services

Industry Solution

Banks, neobanks, EMIs, payment processors, card issuers, PSPs, and other regulated firms processing customer payments at scale. As transaction volumes grow and criminals adapt, payments firms need to prove their AML controls work — without relying on fragile, privacy-sensitive production data.

Syntheticr gives you a risk-free way to:

Establish a clear baseline of current effectiveness
Validate new models and rules before release
Benchmark vendors or internal upgrades with ground-truth scoring

This makes investment decisions faster, safer, and easier to defend to regulators and boards.

How it works

Syntheticr provides high-fidelity synthetic transaction data generated from a simulation of legitimate activity and embedded money laundering networks. You run it through your stack as if it were production, and Syntheticr provides an objective score of the output.

Ready-to-use

Realistic data covering all major transaction types and aligned to ISO20022 standards
Embedded network typologies and AML methodologies reflecting real-world behaviour
Objective scorecards to quantify accuracy and false positives
A 6-month greenfield period for unbiased model training

Get started

Choose a subscription plan aligned to your needs
Download the synthetic datasets to your environment
Process the datasets through your AML system to generate alerts
Upload the alerts for review
Receive your performance scorecard

What you get

Synthetic datasets including entity profiles, transactions, and risk intelligence
Objective performance scorecards
Comparative reports across time, systems and versions
Optional:
- Low-volume labelled subsets for training
- Custom versions with variable data quality
- Multi-bank datasets

SOLUTION