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.

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.

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....

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.

The benchmark interest rate in China was last recorded at 3 percent. This dataset provides the latest reported value for - China Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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.

Lower Limit of First Home Mortgage Rate: above LPR: Beijing data was reported at -0.450 % Point in 17 May 2025. This stayed constant from the previous number of -0.450 % Point for 16 May 2025. Lower Limit of First Home Mortgage Rate: above LPR: Beijing data is updated daily, averaging 0.550 % Point from Oct 2019 (Median) to 17 May 2025, with 2049 observations. The data reached an all-time high of 0.550 % Point in 25 Jun 2024 and a record low of -0.450 % Point in 17 May 2025. Lower Limit of First Home Mortgage Rate: above LPR: Beijing data remains active status in CEIC and is reported by The People's Bank of China. The data is categorized under China Premium Database’s Money Market, Interest Rate, Yield and Exchange Rate – Table CN.MA: Lower Limit of First Home Mortgage Rate: Prefecture Level City. After adjustment on December 15, 2023: the lower limits of the first and second sets of interest rate policies in the six districts of the city are respectively no less than the market quoted interest rate for loans of the corresponding period plus 10 basis points, and no less than the market quoted interest rate for loans of the corresponding period plus 60 basis points; The lower limits of the first and second sets of interest rate policies in the six non-urban districts are not lower than the market quoted interest rate for loans of the corresponding period, and not lower than the market quoted interest rate for loans of the corresponding period plus 55 basis points.

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

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

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]

This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...).

Weekly updated dataset of Santander mortgage offerings, including interest rates, APRC, fees, and LTV for each product.

United States Mortgage Fixed Rate: Mth Avg: 15 Year: Point data was reported at 0.400 % pa in Oct 2018. This records a decrease from the previous number of 0.500 % pa for Sep 2018. United States Mortgage Fixed Rate: Mth Avg: 15 Year: Point data is updated monthly, averaging 0.700 % pa from Sep 1991 (Median) to Oct 2018, with 326 observations. The data reached an all-time high of 1.900 % pa in Mar 1992 and a record low of 0.400 % pa in Oct 2018. United States Mortgage Fixed Rate: Mth Avg: 15 Year: Point data remains active status in CEIC and is reported by Federal Home Loan Mortgage Corporation, Freddie Mac. The data is categorized under Global Database’s United States – Table US.M012: Mortgage Interest Rate.

United States Mortgage Adjustable Rate: Wk Ending: 5 Year data was reported at 4.070 % pa in 06 Dec 2018. This records a decrease from the previous number of 4.120 % pa for 29 Nov 2018. United States Mortgage Adjustable Rate: Wk Ending: 5 Year data is updated weekly, averaging 3.530 % pa from Jan 2005 (Median) to 06 Dec 2018, with 727 observations. The data reached an all-time high of 6.390 % pa in 06 Jul 2006 and a record low of 2.560 % pa in 02 May 2013. United States Mortgage Adjustable Rate: Wk Ending: 5 Year data remains active status in CEIC and is reported by Federal Home Loan Mortgage Corporation, Freddie Mac. The data is categorized under Global Database’s United States – Table US.M012: Mortgage Interest Rate.

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

The benchmark interest rate in Norway was last recorded at 4.25 percent. This dataset provides the latest reported value for - Norway Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

House price index is based on average new house price value at loan approval stage and therefore has not been adjusted for changes in the mix of houses and apartments sold. Interest rates is based on building societies mortgage loans, published by Central Statistics Office up to 2007.
From 2008 interest rates is average rate of all 'mortgage lenders' reporting to the Central Bank.
From 2014 it is based on the floating rate for new customers as published by the Central Bank (Retail interest rates - Table B2.1). The reason for the drop between 2013 and 2014 is due to the difference in methodology - the 2014 data is the weighted average rate on new loan agreements. Further information can be found here:
http://www.centralbank.ie/polstats/stats/cmab/Documents/Retail_Interest_Rate_Statistics_Explanatory_Notes.pdf
Earnings is based on the average weekly earnings of adult workers in manufacturing industries, published by the Central Statistics Office. This series has been updated since 1996 using a new methodology and therefore it is not directly comparable with those for earlier years. House Construction Cost Index is based on the 1st day of the third month of each quarter.
Consumer Price index is based on the Consumer Price Index, published by the Central Statistics Office.
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

Weekly updated dataset of mortgage rates and offerings from TSB including details such as term length, initial interest rate, APRC, fees, and LTV.

United States WAS: Effective Rate: FRM 30-Year: 1-Wk Change data was reported at 0.000 Point in 20 Jul 2018. This records a decrease from the previous number of 0.020 Point for 13 Jul 2018. United States WAS: Effective Rate: FRM 30-Year: 1-Wk Change data is updated weekly, averaging -0.010 Point from Jan 1990 (Median) to 20 Jul 2018, with 1489 observations. The data reached an all-time high of 0.610 Point in 09 Oct 1998 and a record low of -0.530 Point in 28 Nov 2008. United States WAS: Effective Rate: FRM 30-Year: 1-Wk Change data remains active status in CEIC and is reported by Mortgage Bankers Association. The data is categorized under Global Database’s USA – Table US.M013: Weekly Applications Survey: Mortgage Interest Rate.