Fed-DPSDG-WGAN: Differentially Private Synthetic Data Generation for Loan Default Prediction via Federated Wasserstein GAN

Lenders typically conduct thorough credit checks to mitigate credit default risk before lending money. Proactively predicting loan defaulters has become increasingly important. However, creating robust deep-learning algorithms that classify loan defaulters requires abundant data, potentially comprom...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Padmaja Ramachandra, Santhi Vaithiyanathan
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Subjects:	Federated learning WGAN CTGAN differentially private data oversampling trivial auto-encoder
Online Access:	https://ieeexplore.ieee.org/document/10930895/