Technology

Industry Solution

SOLUTION

Your buyers expect evidence, not just demos…

…and you need to prove performance fast, without waiting for access to sensitive client data.

Syntheticr supports a range of use cases for AML and financial crime technology providers, including transaction monitoring vendors, regtech platforms, data providers, and infrastructure firms building compliance capabilities into payments products by providing a risk-free way to:

Demonstrate measurable detection performance with ground-truth scoring
Run credible proofs-of-concept without client data dependencies
Benchmark new features, models, and rule sets before release

This makes sales cycles shorter, product decisions clearer, and performance claims defensible.

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 platform 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