Fake Bank Name Detection using LSTM and RNN

With the rise of online fraud, safeguarding banking transactions is crucial. This paper presents a deep learning approach using Long Short-Term Memory (LSTM) and Recurrent Neural Networks (RNNs) to detect fake bank names. The system analyzes textual patterns to differentiate between real and fraudulent bank names. It involves training on a dataset of authentic and fake names, with performance evaluated on accuracy, precision, recall, and F1-score. The aim is to enhance online security and mitigate risks associated with fake bank websites.