January 1, 2025

Generative AI in Data Engineering: Use Cases for Synthetic Fraud Scenarios

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Generative AI enhances fraud detection by providing robust synthetic data for training models, improving accuracy.
Empirical results indicate the proposed method reduces false favorable rates in fraud detection models, increasing reliability.
Analysis involves integrating generative adversarial networks into existing ETL architectures for enhanced data pipelines.
This research emphasizes the ethical considerations of creating synthetic data, advocating for its responsible application.

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Generative AI improves synthetic data use cases in fraud detection, suggesting scalable data engineering solutions.

Ravi Kiran Alluri (2025) studied this question.

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