Synthetic Data Applications in Finance
CoRR(2023)
Abstract
Synthetic data has made tremendous strides in various commercial settings
including finance, healthcare, and virtual reality. We present a broad overview
of prototypical applications of synthetic data in the financial sector and in
particular provide richer details for a few select ones. These cover a wide
variety of data modalities including tabular, time-series, event-series, and
unstructured arising from both markets and retail financial applications. Since
finance is a highly regulated industry, synthetic data is a potential approach
for dealing with issues related to privacy, fairness, and explainability.
Various metrics are utilized in evaluating the quality and effectiveness of our
approaches in these applications. We conclude with open directions in synthetic
data in the context of the financial domain.
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