Datasets:
consumer-finance-complaints

Tasks:

Text Classification

Sub-tasks: topic-classification

Languages: English

Multilinguality: monolingual

Size Categories: 1M<n<10M

Language Creators: crowdsourced

Annotations Creators: crowdsourced

Source Datasets: original

License:

Dataset card Files Files and versions Community

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Split (1)

train

The dataset viewer is not available for this split.

Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    ValueError
Message:      Invalid string class label Credit reporting or other personal consumer reports
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 322, in compute
                  compute_first_rows_from_parquet_response(
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 88, in compute_first_rows_from_parquet_response
                  rows_index = indexer.get_rows_index(
                File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 444, in get_rows_index
                  return RowsIndex(
                File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 347, in __init__
                  self.parquet_index = self._init_parquet_index(
                File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 364, in _init_parquet_index
                  response = get_previous_step_or_raise(
                File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 566, in get_previous_step_or_raise
                  raise CachedArtifactError(
              libcommon.simple_cache.CachedArtifactError: The previous step failed.
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 126, in get_rows_or_raise
                  return get_rows(
                File "/src/services/worker/src/worker/utils.py", line 64, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 103, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1392, in __iter__
                  example = _apply_feature_types_on_example(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1080, in _apply_feature_types_on_example
                  encoded_example = features.encode_example(example)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1888, in encode_example
                  return encode_nested_example(self, example)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1243, in encode_nested_example
                  {k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1243, in <dictcomp>
                  {k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1299, in encode_nested_example
                  return schema.encode_example(obj) if obj is not None else None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1089, in encode_example
                  example_data = self.str2int(example_data)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1026, in str2int
                  output = [self._strval2int(value) for value in values]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1026, in <listcomp>
                  output = [self._strval2int(value) for value in values]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1047, in _strval2int
                  raise ValueError(f"Invalid string class label {value}")
              ValueError: Invalid string class label Credit reporting or other personal consumer reports

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Dataset Card for Consumer Finance Complaints

Dataset Summary

This database is a collection of complaints about consumer financial products and services that we sent to companies for response.

The Consumer Complaint Database is a collection of complaints about consumer financial products and services that we sent to companies for response. Complaints are published after the company responds, confirming a commercial relationship with the consumer, or after 15 days, whichever comes first. Complaints referred to other regulators, such as complaints about depository institutions with less than $10 billion in assets, are not published in the Consumer Complaint Database. The database generally updates daily.

Complaints can give us insights into problems people are experiencing in the marketplace and help us regulate consumer financial products and services under existing federal consumer financial laws, enforce those laws judiciously, and educate and empower consumers to make informed financial decisions. We also report on complaint trends annually in Consumer Response’s Annual Report to Congress.

Supported Tasks and Leaderboards

Text Classification Tasks

Task	Label Name	Description	SOTA
Text Classification	Product	Predict the related product of a complaint	N/A

Task	Label Name	Description	SOTA
Text Classification	Sub-Product	Predict the related sub product of a complaint	N/A

Task	Label Name	Description	SOTA
Text Classification	Tags	Predict whether a complaint has been made by someone elderly or a service person	N/A

Languages

English

Dataset Structure

Data Instances

This dataset is a point in time extract of the database, the database increases in size every day

An example of 'train' looks as follows.

{
 "Complaint ID": "4511031",
 "Product": "Credit reporting, credit repair services, or other personal consumer reports",
 "Sub Issue": "Credit inquiries on your report that you don't recognize",
 "Consumer Disputed": "N/A",
 "Sub Product": "Credit reporting",
 "State": "TX",
 "Tags": "Older American, Servicemember",
 "Company Public Response": "",
 "Zip Code": "75202",
 "Issue": "Improper use of your report",
 "Submitted via": "Web",
 "Company Response To Consumer": "Closed with explanation",
 "Complaint Text": "I am XXXX XXXX and I am submitting this complaint myself and there is no third party involved. Despite the multiple previous written requests, the unverified inquiries listed below still remain on my credit report in violation of Federal Law. The Equifax Credit Bureau failed to comply with Fair Credit Reporting Act, XXXX XXXX sections XXXX within the time set forth by law and continued reporting of erroneous information which now, given all my attempts to address it directly with the creditor, as willful negligence and non-compliance with federal statutes. PLEASE REMOVE THE FOLLOWING INQUIRIES COMPLETELY FROM MY CREDIT REPORT : XXXX CARD-Date of inquiry XX/XX/XXXX XXXX CARD-Date of inquiry XX/XX/XXXX",
 "Date Received": "07-02-2021",
 "Company": "EQUIFAX, INC.",
 "Consumer Consent Provided": "Consent not provided",
 "Timely Response": "Yes",
 "Date Sent To Company": "2021-07-02"
}

Data Fields

Field	name	Description	Data Type
Date received	The date the CFPB received the complaint	date & time
Product	The type of product the consumer identified in the complaint	plain text	This field is a categorical variable.
Sub-product	The type of sub-product the consumer identified in the complaint	plain text	This field is a categorical variable. Not all Products have Sub-products.
Issue	The issue the consumer identified in the complaint	plain text	This field is a categorical variable. Possible values are dependent on Product.
Sub-issue	The sub-issue the consumer identified in the complaint	plain text	This field is a categorical variable. Possible values are dependent on product and issue. Not all Issues have corresponding Sub-issues.
Consumer complaint narrative	Consumer complaint narrative is the consumer-submitted description of "what happened" from the complaint. Consumers must opt-in to share their narrative. We will not publish the narrative unless the consumer consents, and consumers can opt-out at any time. The CFPB takes reasonable steps to scrub personal information from each complaint that could be used to identify the consumer.	plain text	Consumers' descriptions of what happened are included if consumers consent to publishing the description and after we take steps to remove personal information.
Company public response	The company's optional, public-facing response to a consumer's complaint. Companies can choose to select a response from a pre-set list of options that will be posted on the public database. For example, "Company believes complaint is the result of an isolated error."	plain text	Companies' public-facing responses to complaints are included if companies choose to publish one. Companies may select a public response from a set list of options as soon as they respond to the complaint, but no later than 180 days after the complaint was sent to the company for response.
Company	The complaint is about this company	plain text	This field is a categorical variable.
State	The state of the mailing address provided by the consumer	plain text	This field is a categorical variable.
ZIP code	The mailing ZIP code provided by the consumer	plain text	Mailing ZIP code provided by the consumer. This field may: i) include the first five digits of a ZIP code; ii) include the first three digits of a ZIP code (if the consumer consented to publication of their complaint narrative); or iii) be blank (if ZIP codes have been submitted with non-numeric values, if there are less than 20,000 people in a given ZIP code, or if the complaint has an address outside of the United States). For example, complaints where the submitter reports the age of the consumer as 62 years or older are tagged, ‘Older American.’ Complaints submitted by or on behalf of a servicemember or the spouse or dependent of a servicemember are tagged, ‘Servicemember.’ Servicemember includes anyone who is active duty, National Guard, or Reservist, as well as anyone who previously served and is a Veteran or retiree.
Tags	Data that supports easier searching and sorting of complaints submitted by or on behalf of consumers.	plain text
Consumer consent provided?	Identifies whether the consumer opted in to publish their complaint narrative. We do not publish the narrative unless the consumer consents and consumers can opt-out at any time.	plain text	This field shows whether a consumer provided consent to publish their complaint narrative
Submitted via	How the complaint was submitted to the CFPB	plain text	This field is a categorical variable.
Date sent to company	The date the CFPB sent the complaint to the company	date & time
Company response to consumer	This is how the company responded. For example, "Closed with explanation."	plain text	This field is a categorical variable.
Timely response?	Whether the company gave a timely response	plain text	yes/no
Consumer disputed?	Whether the consumer disputed the company’s response	plain text	YES/ NO/ N/A: The Bureau discontinued the consumer dispute option on April 24, 2017.
Complaint ID	The unique identification number for a complaint	number

Data Splits

This dataset only contains a TRAIN set - this can be further split into TRAIN, TEST and VALIDATE subsets with the datasets library

Dataset Creation

Curation Rationale

Open sourcing customer complaints

Source Data

https://cfpb.github.io/api/ccdb/

Initial Data Collection and Normalization

This database is maintained by the Consumer Financial Protection Bureau

Who are the source language producers?

English

Annotations

Annotation process

User submitted to the CFPB

Who are the annotators?

N/A

Personal and Sensitive Information

All PII data has been anonymised

Considerations for Using the Data

Social Impact of Dataset

N/A

Discussion of Biases

This database is not a statistical sample of consumers’ experiences in the marketplace. Complaints are not necessarily representative of all consumers’ experiences and complaints do not constitute “information” for purposes of the Information Quality Act .

Complaint volume should be considered in the context of company size and/or market share. For example, companies with more customers may have more complaints than companies with fewer customers. We encourage you to pair complaint data with public and private data sets for additional context.

The Bureau publishes the consumer’s narrative description of his or her experience if the consumer opts to share it publicly and after the Bureau takes steps to remove personal information. We don’t verify all the allegations in complaint narratives. Unproven allegations in consumer narratives should be regarded as opinion, not fact. We do not adopt the views expressed and make no representation that consumers’ allegations are accurate, clear, complete, or unbiased in substance or presentation. Users should consider what conclusions may be fairly drawn from complaints alone.