Multi-Factor Authentication for Secured Financial Transactions Through Spatio-TGCN Model

In the information economy, online financial transactions must be secure. Digital platforms for everyday transactions put financial services customers at danger of fraud and unauthorized access. This research integrated machine learning and multi-factor authentication to secure online financial transactions. System steps include data preparation, feature extraction, and model training. Data preparation includes data normalization, label encoding, white space removal, and socket information removal. Feature extraction strengthens variable association to improve model predictive ability. The suggested model uses spatio- TGCN for training. We found that the proposed model outperforms GCN and CNN. Comparing to other models, the framework's 91.40% accuracy rate suggests it could safeguard online financial transactions. This method may make internet financial transactions safer.