Author: Noah Gomez
Created: 1 July 2023
Published: 28 December 2023
Updated: 30 May 2024
Active - Continually Updated
Product Concerned: Consumer Financial Products
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.
30 May 2024
This data table hosts commercial data of over 80 consumer expectation metrics from approximately 1,300 households since 2013. This is a public dataset available to the public and used to identify, rank, and tailor the best offers to consumers in ThickCredit's product and content.
This dataset is similar to but not the same as:
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.
All data is continually collected from the Federal Reserve of New York by human agents. The process can involve manually extracting data from PDFs and other nontransferable files.
Accuracy is reinforced by dual-authentication and continual updating of evolutionary figures, such as interest rates that may evolve over time.
The data is collected from an Excel file in aggregate form and does not completion. However, the field names are not available directly in the data file and must be completed using the survey in PDF form for computation and analysis.
The data is updated continually to include new data as it’s made available from the New Yor branch of the Federal Reserve System.
In some cases, cleaning includes the conversion of PDFs or other non-tabular files into spreadsheets for analysis, notably for field names that are codified in the data sheet.
The dataset is hosted natively offline and on hard drives inaccessible via internet channels.
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.
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.
Thick Credit is not a credit repair organization, a credit conseling agency, or a debtor education providor. It does not act on your behalf to communicate with credit reporting agencies or provide pre-bankruptcy credit counseling and pre-discharge debtor education for bankruptcy.
©2024 Thick Credit, All right reserved.