Financial Crime Testing & Machine Learning Training

We enable financial institutions to create tailored synthetic data with the latest financial crime simulations to build high performance machine learning crime detection

Why FinCrime Dynamics?

 
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Unlock the Potential of Machine Learning Using Synthetic Data

Machine learning (ML) requires large quantities of high quality data to unlock its true potential. Access to such data is hindering the use of ML in the fight against financial crime. The rapid generation of synthetic data with high analytical value is now making effective ML possible for financial crime prevention.

 
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Measure and Improve Your Financial Crime Compliance Controls

FinCrime Dynamics allows financial institutions to create their own synthetic data sets enriched with customised financial crime simulations by using our product Synthetizor®. This enriched data can then be freely used to test, measure and improve compliance controls (such as transaction monitoring systems) without the privacy constraints of real client data.

 

Access and Create Financial Crime Vaccines

Financial Crime Vaccines provide a safer way for financial institutions to understand and improve the performance of their financial crime controls. Read our blog on Why “Financial Crime Vaccines” Are The RegTech Breakthrough of 2022. Join the community of industry stakeholders supporting the effort to build, trial & rollout financial crime vaccines here.

Who do we serve?

  • Banks

  • Payment Providers

  • Building Societies

  • Crypto Exchanges

  • FX Exchanges

Innovate with us

  • Secure Data Privacy

    Synthetic data helps mitigate the data privacy concerns when using real private data. Synthetic data retains the analytical qualities of real data but cannot be traced back to the original source, unlike anonymised data.

  • Superior Data Quality

    Synthetic data retains the analytical traits of source data. Data quality can be improved by cleansing and reducing bias. Customised labelling of your data for more effective testing.

  • Scalable Data Generation

    Synthetic data allows for large amounts of data to be quickly generated from small source data sets. This circumnavigates the need to continually gain access to and cleanse real data sets.

  • Simulate Financial Crime

    Test your financial crime controls in a safe way using simulations of financial crime behaviours. Measure your performance against simulations of known financial crime techniques as well as self-customised scenarios. Label your data with financial crime simulations for effective control testing.

  • Score Your Compliance Controls

    Measure and improve your controls against financial crime. Benchmark your financial crime control performance against other financial institutions.

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