Author: Noah Gomez
Created: 1 July 2023
Published: 31 December 2024
Updated: 2 January 2024
Active - Continually Updated
Product Concerned: Mortgage
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.
2 January 2024
This data table hosts mortgage rate data for 30-year conforming, jumbo, FHA, VA, and USDA loans, as well as 15-year conforming loans. It is a public dataset manages by Optimal Blue and made available via the St. Louis Federal Reserve as separate metrics. We use it 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 with consumer borrowers in mind. Data fields are limited to metrics that inform decision-making and risk-mitigation, as well as contact information. Mortgage rate data is updated automatically by the data service provider.
All data is continually collected from Optimal Blue by human agents. The process can involve manually extracting data from disparate data sources.
Accuracy is reinforced by dual-authentication and continual updating of evolutionary figures, in this case interest rates that evolve over time.
The data is collected from an Excel file in aggregate form and does not require completion. However, some metrics require adjustment to reflect nuances across multi-dimensional figures, such as x-year rates per FICO score.
The data is updated continually to include new data as it’s made available from Optimal Blue either through its website or via the St. Louis Federal Reserve interface..
Because Optimal Blue’s data is pre-cleaned and provided as-is, cleaning is not necessary for the dataset.
The dataset is hosted natively offline and on hard drives inaccessible via internet channels after download from Optimal Blue.
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.