Fixed 30-year mortgage rates in the United States averaged 6.79 percent in the week ending June 27 of 2025. This dataset provides the latest reported value for - United States MBA 30-Yr Mortgage Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

30 Year Mortgage Rate in the United States decreased to 6.67 percent in July 3 from 6.77 percent in the previous week. This dataset includes a chart with historical data for the United States 30 Year Mortgage Rate.

Retail Interest Rates - Mortgage Rates. Published by Central Bank of Ireland. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Table B.3.1 presents quarterly mortgage rate data specific to the Irish market. These data include all euro and non-euro denominated mortgage lending in the Republic of Ireland only. New business refers to new mortgage lending drawdowns during the quarter, broken down by type of interest rate product (i.e. fixed, tracker and SVR). The data also provide further breakdown of mortgages for principal dwelling house (PDH) and buy-to-let (BTL) properties. Renegotiations of existing loans are not included....

In May 29, 2019, FHFA published its final Monthly Interest Rate Survey (MIRS), due to dwindling participation by financial institutions. MIRS had provided information on a monthly basis on interest rates, loan terms, and house prices by property type (all, new, previously occupied); by loan type (fixed- or adjustable-rate), and by lender type (savings associations, mortgage companies, commercial banks and savings banks); as well as information on 15-year and 30-year, fixed-rate loans. Additionally, MIRS provided quarterly information on conventional loans by major metropolitan area and by Federal Home Loan Bank district, and was used to compile FHFA’s monthly adjustable-rate mortgage index entitled the “National Average Contract Mortgage Rate for the Purchase of Previously Occupied Homes by Combined Lenders,” also known as the ARM Index.

Mortgage Application in the United States increased by 2.70 percent in the week ending June 27 of 2025 over the previous week. This dataset provides - United States MBA Mortgage Applications - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Weekly updated dataset of Nationwide Building Society mortgage products, including interest rates, LTVs, APRC and product fees.

This dataset provides values for 30 YEAR MORTGAGE RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This dataset is about book series. It has 1 row and is filtered where the books is What calls to ARMS? : International evidence on interest rates and the choice of adjustable-rate mortgages. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

This dataset provides insights into the global housing market, covering various economic factors from 2015 to 2024. It includes details about property prices, rental yields, interest rates, and household income across multiple countries. This dataset is ideal for real estate analysis, financial forecasting, and market trend visualization.

📑 Column Descriptions

Weekly updated dataset of Lloyds mortgage products including interest rates, LTVs, APRC and product fees.

Interest rates to be paid on debentures issued with respect to a loan or mortgage insured by the Federal Housing Commissioner under the provisions of the National Housing Act (the Act). The Department will continue to publish semi-annually the debenture interest rate for the next six-month period in the Federal Register. Concurrently with the publication in the Federal Register, the Department will update the list of debenture interest rates.

Graph and download economic data for 30-Year Fixed Rate Conforming Mortgage Index: Loan-to-Value Greater Than 80, FICO Score Between 720 and 739 (OBMMIC30YFLVGT80FB720A739) from 2017-01-03 to 2025-06-20 about score, 30-year, fixed, mortgage, rate, indexes, and USA.

Switzerland Mortgage Rate: Variable data was reported at 2.633 % pa in Sep 2018. This stayed constant from the previous number of 2.633 % pa for Aug 2018. Switzerland Mortgage Rate: Variable data is updated monthly, averaging 4.295 % pa from Jun 1976 (Median) to Sep 2018, with 508 observations. The data reached an all-time high of 7.990 % pa in Jan 1991 and a record low of 2.623 % pa in Nov 2017. Switzerland Mortgage Rate: Variable data remains active status in CEIC and is reported by Swiss National Bank. The data is categorized under Global Database’s Switzerland – Table CH.M005: Mortgage Rates.

Source: From lending institutions and local authorities The loan payments dataset stops in 2007. The figures on fixed interest rate mortgages relate to mortgages which provide that the rate of interest may not be changed, or may only be changed at intervals of not less than one year. The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change.

DESCRIPTION

Create a model that predicts whether or not a loan will be default using the historical data.

Problem Statement:

For companies like Lending Club correctly predicting whether or not a loan will be a default is very important. In this project, using the historical data from 2007 to 2015, you have to build a deep learning model to predict the chance of default for future loans. As you will see later this dataset is highly imbalanced and includes a lot of features that make this problem more challenging.

Domain: Finance

Analysis to be done: Perform data preprocessing and build a deep learning prediction model.

Content:

Dataset columns and definition:

credit.policy: 1 if the customer meets the credit underwriting criteria of LendingClub.com, and 0 otherwise.

purpose: The purpose of the loan (takes values "credit_card", "debt_consolidation", "educational", "major_purchase", "small_business", and "all_other").

int.rate: The interest rate of the loan, as a proportion (a rate of 11% would be stored as 0.11). Borrowers judged by LendingClub.com to be more risky are assigned higher interest rates.

installment: The monthly installments owed by the borrower if the loan is funded.

log.annual.inc: The natural log of the self-reported annual income of the borrower.

dti: The debt-to-income ratio of the borrower (amount of debt divided by annual income).

fico: The FICO credit score of the borrower.

days.with.cr.line: The number of days the borrower has had a credit line.

revol.bal: The borrower's revolving balance (amount unpaid at the end of the credit card billing cycle).

revol.util: The borrower's revolving line utilization rate (the amount of the credit line used relative to total credit available).

inq.last.6mths: The borrower's number of inquiries by creditors in the last 6 months.

delinq.2yrs: The number of times the borrower had been 30+ days past due on a payment in the past 2 years.

pub.rec: The borrower's number of derogatory public records (bankruptcy filings, tax liens, or judgments).

Steps to perform:

Perform exploratory data analysis and feature engineering and then apply feature engineering. Follow up with a deep learning model to predict whether or not the loan will be default using the historical data.

Tasks:

1. Feature Transformation

Transform categorical values into numerical values (discrete)

1. Exploratory data analysis of different factors of the dataset.

2. Additional Feature Engineering

You will check the correlation between features and will drop those features which have a strong correlation

This will help reduce the number of features and will leave you with the most relevant features

1. Modeling

After applying EDA and feature engineering, you are now ready to build the predictive models

In this part, you will create a deep learning model using Keras with Tensorflow backend

United States Mortgage Debt Outstanding: Effective Interest Rate data was reported at 3.799 % in Mar 2020. This records a decrease from the previous number of 3.872 % for Dec 2019. United States Mortgage Debt Outstanding: Effective Interest Rate data is updated quarterly, averaging 7.677 % from Mar 1977 (Median) to Mar 2020, with 173 observations. The data reached an all-time high of 11.449 % in Mar 1985 and a record low of 3.750 % in Dec 2017. United States Mortgage Debt Outstanding: Effective Interest Rate data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s United States – Table US.KB025: Mortgage Interest Paid. [COVID-19-IMPACT]

Dataset of UK mortgage products with 1-year fixed terms, including initial rates, APRC, fees, and LTV percentages.

Source: From lending institutions and local authorities The loan payments dataset stops in 2007. The figures on fixed interest rate mortgages relate to mortgages which provide that the rate of interest may not be changed, or may only be changed at intervals of not less than one year. The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change.

Analysis of ‘Percentage of mortgages constituted according to interest rate. HPT (API identifier: 24456)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/urn-ine-es-tabla-t3-3-24456 on 08 January 2022.

--- Dataset description provided by original source is as follows ---

Table of INEBase Percentage of mortgages constituted according to interest rate. Monthly. National. Mortgages Statistic

--- Original source retains full ownership of the source dataset ---

15 Year Mortgage Rate in the United States decreased to 5.80 percent in July 3 from 5.89 percent in the previous week. This dataset includes a chart with historical data for the United States 15 Year Mortgage Rate.