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Consumer Banking Issues Dataset
Finance & Banking Analytics
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About
This dataset provides a collection of consumer complaints related to bank accounts or services, as well as credit card matters. It serves as a valuable resource for financial and banking analytics, enabling text classification, natural language processing, and data pre-processing tasks. The data originates from a verified provider and offers insights into various issues encountered by consumers with financial institutions.
Columns
- date_received: The date when the complaint was received.
- product: The broader category of the financial product or service involved (e.g., Bank account or service, Other bank product/service, Certificate of deposit).
- sub_product: A more specific category within the product (e.g., Checking account, (CD) Certificate of deposit).
- issue: The specific problem reported by the consumer (e.g., Using a debit or ATM card, Account opening, closing, or management, Deposits and withdrawals, Problems caused by my funds being low).
- sub_issue: A more detailed description of the issue. This column often appears to be blank in the provided samples.
- consumer_complaint_narrative: The narrative provided by the consumer detailing their complaint. This column is not present in the provided sample data, but is listed in the column names.
- company_public_response: The public response from the company regarding the complaint. This column is not present in the provided sample data, but is listed in the column names.
- company: The name of the financial institution against which the complaint was filed (e.g., Wells Fargo & Company, Santander Bank US, Bank of America, JPMorgan Chase & Co., First Tennessee Bank, People's United Bank, TD Bank US Holding Company).
- state: The state where the consumer resides (e.g., CA, NY, GA, TX, NJ, TN, CT, FL).
- zip_code: The postal code of the consumer.
- tags: Special tags associated with the consumer, such as 'Older American' or 'Servicemember'.
- consumer_consent_provided: Indicates if the consumer provided consent for their narrative to be publicly shared. This column often appears to be blank in the provided samples.
- submitted_via: The method by which the complaint was submitted (e.g., Web, Fax, Postal mail, Phone, Referral).
- date_sent_to_company: The date when the complaint was sent to the company.
- company_response_to_consumer: The company's response to the consumer (e.g., Closed with explanation, Closed, Closed with monetary relief).
- timely_response: Indicates if the company provided a timely response (True/False).
- consumer_disputed: Indicates if the consumer disputed the company's response (True/False).
- complaint_id: A unique identifier for the complaint.
Distribution
The data file is typically provided in CSV format. Specific numbers for rows or records are not available from the current sources, but the dataset is structured to capture individual consumer complaints.
Usage
This dataset is ideal for:
- Financial & Banking Analytics: Analysing trends in consumer complaints within the banking sector.
- Natural Language Processing (NLP): Processing the text of complaints for sentiment analysis, topic modelling, and keyword extraction.
- Text Classification: Categorising complaints based on their content, issue, or sub-product.
- Pre-processing: Preparing text data for machine learning models.
- Identifying Consumer Pain Points: Pinpointing common issues with specific banks or financial products.
Coverage
The data samples provided cover complaints received on 29th and 30th July 2013. Geographic coverage includes various states across the United States, such as California, New York, Georgia, Texas, New Jersey, Tennessee, Connecticut, and Florida. The dataset also includes demographic information through 'tags' such as 'Older American' and 'Servicemember', indicating data availability for these specific groups.
License
CC0
Who Can Use It
- Data Analysts: To identify patterns and trends in consumer behaviour and banking issues.
- Financial Institutions: To understand common complaint areas and improve customer service.
- Researchers: For academic studies on consumer finance, banking regulations, and complaint resolution.
- Data Scientists: For building and training NLP models for text analysis, classification, and sentiment analysis on consumer feedback.
- Consumer Protection Agencies: To monitor and investigate banking practices based on consumer grievances.
Dataset Name Suggestions
- Bank and Credit Card Consumer Complaints
- Financial Service Complaint Data
- Consumer Banking Issues Dataset
- US Bank Complaint Records
Attributes
Original Data Source: Bank and Credit Card Complaints
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