Automated Banking Complaint Classification using Stochastic Gradient Descent

The work focuses on the automated classification of banking complaints, addressing a critical challenge faced by financial institutions globally, the efficient and accurate categorization of customer complaints. The proposed system leverages advanced machine learning techniques to classify complaints into predefined categories, streamlining the complaint management process and enhancing customer service efficiency. The end system obtained 85.79% accuracy, which surpassed conventional approaches, and performed well in large-scale complaint data processing. This work aims to significantly reduce the time and effort required for managing banking complaints.