Credit Card Agreement Dataset

Author: Noah Gomez
Created: 1 July 2023
Published: 20 December 2023
Updated: 30 May 2024

Status: Active

Active - Continually Updated


Dataset Metadata

Product Concerned: Secured Credit Card
File Type: Created in Microsoft Excel, Hosted Privately
Availability Status: Public
Mother Catelog: Public Datasets
Mother Catelog Description: A collection of datasets acquired, processed, refined, and analyzed by Thick Credit.

Date Updated

30 May 2024


Description

This table hosts commercial data of over 3,800 cardholder agreements in the market. It is a public dataset available via the Consumer Financial Protection Bureau's website used to identify, rank, and tailor the best offers to consumers throughout ThickCredit's product and content. Notably, it informs our assessment of secured credit cards.

Sample (Image)

Similar Datasets

This dataset is similar to but not the same as:

  • the credit builder card dataset,
  • the credit builder loan dataset,
  • the secured credit card dataset,
  • the savings-secured loan dataset,
  • National Credit Union Association's Call Report Dataset, and
  • the rent reporting services dataset.

Data Fields in Table

  • Name. The name of the lender that issues the card.
  • Purchases. The APR calculated on purchase transactions.
  • Balance Transfer. The APR calculated on balance transfers.
  • Cash Advance. The APR calculated on cash advances.
  • Annual Fee. The fee imposed annually, if any, to own the card, expressed as a percent or absolute amount.
  • Balance Transfer %. The fee imposed, if any, for balance transfers, expressed as a percent of the transaction value.
  • Balance Transfer $. The fee imposed, if any, for balance transfers, expressed as a fixed amount.
  • Cash Advance %. The fee imposed, if any, for cash advances, expressed as a percent of the transaction value.
  • Cash Advance $. The fee imposed, if any, for cash advances, expressed as a fixed amount.
  • Foreign Transactions. The fee imposed for foreign transactions, if any, expressed as a percent or absolute amount.
  • Late Payment. The fee imposed for late payments, if any, expressed as a percent or absolute amount.
  • Returned Payment. The fee imposed for returned payments, if any, expressed as a percent or absolute amount.

Data Quality & Validation

Relevance

Data is chosen and collected with consumer borrowers in mind. Data fields are limited to metrics that inform decision-making and risk-mitigation, as well as contact information. Most of the raw data must be analyzed by Thick Credit to drive insights, except for simple fields such as name and purchases.

Collection

All data is continually collected from the Consumer Financial Protection Bureau by human agents. The process involves manually extracting data from PDFs.

Accuracy

Accuracy is reinforced by dual-authentication and continual updating of evolutionary figures, such as interest rates that may evolve with the prime rate.

Completeness

In some instances, cardholder agreements do not include standard metrics, or require an application to determine interest. In these cases, the agreements are excluded by default or sourced by call with the card issuer if critical to analysis.

Recency

The data is updated continually to include new data and new offers entering the market.

Cleaning

Cleaning includes the conversion of PDFs or other non-tabular files into spreadsheets for analysis.

Privacy

The dataset is hosted natively offline and on hard drives inaccessible via internet channels.

Validation

Outliers do not impact raw data, only analysis. We use a conservative framework that eliminates outliers with a material impact on analytical metrics helpful to consumers. There are no aggregation weaknesses in the dataset as of publishing. We adjust all calculations to present the most accurate reality to consumers.

About the Author

Noah Gomez (founder of Thick Credit) is a transatlantic professional and entrepreneur with 3+ years experience in consumer finance education. He also has 5+ years of experience in corporate finance, including debt financing, M&A, listing preparation, US GAAP and IFRS.

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