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ToolsStrelcenia, E. and Prakoonwit, S., 2023. Synthetic data generation in finance: requirements, challenges and applicability. In: IEEE International Conference on Digital Management, Information Science and Technology, 17-18 March 2023, Shenyang, Chin.
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Abstract
Financial datasets possess susceptible, private and identifiable details about clients. The usage and distribution of such data for research outside a financial institution are strictly constrained due to privacy laws. One option to deal with this restriction is creating artificial data. The generation of fake data protects the confidentiality of customers' information. Data privacy is a prime concern in public opinion. This research study reviews various requirements and challenges for data generative techniques and handling synthetic data in finance.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Class imbalance; financial data; synthetic data |
| Group: | Faculty of Science & Technology |
| ID Code: | 38334 |
| Deposited By: | Symplectic RT2 |
| Deposited On: | 04 Apr 2023 13:27 |
| Last Modified: | 04 Apr 2023 13:27 |
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