Financial Risk Early Warning Model for Imbalanced Data using SGD-GSVM
Abstract
This work offers a new method for early warning of financial risk by combining SGD optimisation with Gaussian SVM and employing adaptive oversampling for data balancing. The findings show that SGD-GSVM is the best model because it strikes a balance between high accuracy and computational economy. Financial organisations can create real-time risk management plans with the help of the suggested technique. For additional performance improvements, hybrid deep learning approaches might be investigated in future studies.
DOI:
https://doi.org/10.31449/inf.v49i37.9897Downloads
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