Consumer Complaints Classification Using Machine Learning & Deep Learning

Abstract

Complaint handling system used by financial companies are handled by live
agents these days, there’s a need to move from a system handled by live agents
to a system which automatically handles the complaints to increase efficiency &
save cost & time. We are planning to develop an automatic financial complaint
classification system that automatically deals with the customer complaints by
segregating the data & routing it to the right department. We are planning
to develop the system by using Natural Language Processing (NLP), Artificial
Intelligence (AI), Machine Learning (ML) & Deep Learning (DL) concepts and
implement using Python, Jupyter Notebook,.etc. The end product will be a webbased application system where customer can register their complaints without having to worry about sending it to right department. (Bejarano) Developed system will automatically segregate the complaints & route it to the right
department. Through this project we are trying to attain best results for our
complaint classification task by comparing various Machine Learning (ML)
models, Deep Learning (DL) models and Ensemble methods on basis of accuracy and time and applying the one which best suits the requirement. (Zhang,
Zhao, and Lecun) We are using data pre-processing methods like data augmentation, lemmatization etc and on top of that TF-IDF and Word2Vec methods for
ML and DL models respectively.