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Data Description:
Complaint Number: Unique identifier for each customer complaint.
Product: The financial product associated with the complaint, categorized into five classes: credit
reporting, debt collection, mortgages and loans, credit cards, and retail banking.
Narrative: The textual narrative of the customer's dispute or complaint submitted to the Consumer
Financial Protection Bureau (CFPB).
Background:
The Consumer Financial Protection Bureau (CFPB) acts as a mediator between financial institutions and
consumers, facilitating dispute resolution when complaints arise. To improve efficiency and accuracy in
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Data Description:
Background:
The Consumer Financial Protection Bureau (CFPB) acts as a mediator between financial institutions and consumers, facilitating dispute resolution when complaints arise. To improve efficiency and accuracy in handling customer complaints, there is a need for natural language processing (NLP) models to automatically classify and route complaints to the appropriate teams based on their content and associated financial products. This project aims to develop an NLP model for bank customer complaint analysis, leveraging historical data from the CFPB website.
Objective:
The objective of this internship project is to develop an NLP model for bank customer complaint analysis to classify complaints into predefined categories based on their textual narratives. By automating the classification process, the project aims to improve efficiency in dispute resolution and enhance customer satisfaction by ensuring timely and accurate handling of complaints.