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:
Featured Use Cases
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.
Workflow:
Run Syntheticr through your system
Generate alerts
Send outputs to Syntheticr
Receive a comprehensive performance scorecard
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.
Workflow:
Vendor runs Syntheticr in a controlled test
The outputs are scored by Syntheticr
Receive a Comparative Performance report.
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.
Workflow:
Use generic or custom synthetic datasets
Test/Train models
Score outputs via API
Rapidly iterate
Additional Use Cases
System Optimisation
Optimise alert volumes and accuracy before releasing updates, then retrain models after release without risking production performance. Syntheticr creates 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 or quality before you invest. Syntheticr lets you test multiple data configurations and measure how each one affects detection performance, 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 for rapid innovation. Syntheticr has already proven its value in regulatory TechSprints and hackathon environments.
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.
Technology Demos
Safely simulate realistic transaction and alert volumes to test how your AML system behaves under scale without using production data.
Volumetric Testing
Use Syntheticr to demonstrate detection workflows, network visualisation, and model behaviour with credible synthetic scenarios. Ideal for internal stakeholders or customer demos.
Not sure where to begin?
Start with a free Performance Baseline and we’ll guide you to the highest-impact use cases.