Simulating Compliance Scenarios using Synthetic Data Generation
DOI:
https://doi.org/10.15680/IJCTECE.2022.0501004Keywords:
Synthetic data, compliance scenarios, real-time data, data privacy, fraud detection, regulatory testingAbstract
Synthetic data generation for simulating compliance scenarios will offer organizations an opportunity to revolutionize the testing and validation of their compliance systems. Many modern regulations, particularly in finance, healthcare, and data security, have become distinctly convoluted and require robust systems developed to predict where potential compliance breaches could occur. This paper takes a look at synthetic data and its role in simulating compliance scenarios and how real-time data applications and synthetic data generation technologies can be used, thus enabling organizations to create accurate and scalable compliance tests. Key challenges for studies on synthetic data include data accuracy, overfitting, and computational intensity, providing solutions that should enhance the credibility of compliance simulations while providing room for scalability.
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