Use Cases

Get the most from Syntheticr

USE CASES

Choose your goal

Syntheticr supports continuous improvement and optimisation of AML performance - from establishing a baseline, to objectively comparing technologies, and developing new models.

Select a use case below to see the typical workflow, and the outputs you’ll receive:

Performance Baseline

For almost every Syntheticr user, this is the first step. Run Syntheticr through your existing AML system to establish a clear, objective view of current performance. You’ll get an objective, quantified scorecard that demonstrates where improvements will have the greatest impact.

Vendor Assessment

When evaluating new AML technologies, Syntheticr lets you compare options safely and fairly. Vendors run the same synthetic scenarios, and Syntheticr scores the outputs with precise performance metrics. It’s a fast, controlled way to make high-stakes vendor decisions with confidence.

Model Development

Syntheticr provides realistic, risk-free data for building and improving models. Vendors use it as a core development asset, and financial institutions use it to accelerate in-house innovation. Scoring-as-a-service, let teams rapidly iterate and prove progress without production data.

System Optimisation

Optimise alert volumes and accuracy before releasing updates, then retrain models after release. With Syntheticr you can create an automated feedback loop via API to help your system learn safely and continuously.

Data Impact Assessment

Quantify the impact of changes to data scope/quality before you invest. Syntheticr lets you test data configurations and measure how the performance impact, so you can prioritise and right-size data improvement spend.

System Benchmark

Track performance trends over time to prove progress and spot drift early. Every Syntheticr assessment is recorded, and you receive clear benchmarking on quarterly improvements.

Peer Benchmark

Understand how you perform relative to anonymised peers. Syntheticr provides a dedicated and controlled benchmark dataset and scores your outputs against a cohort of your peers.

Hackathons

Give teams safe data with embedded typologies and ground truth feedback loops to rapidly test innovative financial crime technology concepts. Syntheticr has proven its value across multiple regulatory TechSprints and hackathon environments.

Technology Demos

Use Syntheticr to demonstrate detection workflows, network visualisation, and model behaviour with credible synthetic scenarios. Ideal for internal stakeholders or customer demos.

Employee Training

Train analysts and investigators on real-world laundering typologies using realistic synthetic data with known outcomes. Build confidence in alert handling, transaction analysis, and SAR writing.

Volumetric Testing

Safely simulate realistic transaction and alert volumes to test how your AML system behaves under scale without using production data.

Not sure where to begin?

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