Why is synthetic data so valuable?
"By 2030 synthetic data will completely overshadow real data in AI models"
- Gartner
What is synthetic data?
Synthetic data is an AI generated version of real data. Synthetic data looks and feels the same as the real original data.
How is synthetic data generated?
AI is used to learn the statistical qualities of original real data and is then trained to generate synthetic data twins. Synthetic data generation can greatly speed up the time to access the valuable data insights. Our product Synthetizor® allows financial institutions to self generate synthetic data from their own original data.
“The fact is you won’t be able to build high-quality, high-value AI models without synthetic data.”
— Gartner
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Data Privacy of Synthetic Data
High quality synthetic data creates flexible and easy to access data which is free from data privacy constraints. Unlike anonymised data, synthetic data cannot be traced back to sensitive original real data.
A key advantage of synthetic data is that it does not contain the sensitive information found in the original real data and is compliant with privacy regulations and laws, such as GDPR. Synthetic data is therefore very appropriate for sharing and testing.
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Analytical Quality of Synthetic Data
High quality synthetic data is statistically representative of original real data. This means that is retains the analytical quality of the original real data.
Our product Synthetizor® produces a performance report of each synthetic data set generated to measure it’s statistic representativeness and quality.
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AI & Testing with Synthetic Data
Synthetic data provides an opportunity to augment real data. This includes effective data labelling, cleansing and reducing underlying data bias.
Augmentation makes synthetic data superior to real data for AI training. Our product Synthetizor® allows financial institutions to label synthetic data sets with financial crime simulations for AI training and testing financial crime control system (such as transaction monitoring systems).
“By 2024, 60% of the data used for the development of AI and analytics projects will be synthetically generated.”
— Gartner
Generate Synthetic Data with FinCrime Dynamics
FinCrime Dynamics specialises in the production of structured tabular transaction synthetic data for financial institutions. Our product Synthetizor® provides a simple self-serve interface to generate synthetic data bespoke to financial institutions and their control systems. Synthetizor® is tailored to fighting financial crime and builds on the power of synthetic data with labelled financial crime simulations to further measure the performance of and calibrate financial crime controls.