30 Year Mortgage Rate in the United States remained unchanged at 6.58 percent in August 21 from 6.58 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 6.68 percent in the week ending August 15 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.

Dataset contains the percent of denied mortgages based on the purpose of the application and disaggregated by race. Each cell represents the denial rate within that column's race/ethnicity category's total applications. Data pulled from the Consumer Financial Protection Bureau, collected by the Home Mortgage Disclosure Act, which requires many financial institutions to maintain, report, and publicly disclose information about mortgages.

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

The benchmark interest rate in the United States was last recorded at 4.50 percent. This dataset provides the latest reported value for - United States Fed Funds Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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.

Analysis of ‘Property Prices Index By City 2009 to 2021’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/jolenech/property-prices-index-by-city-2009-to-2021 on 13 February 2022.

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

Context

I wanted to see how affordable housing is across countries and wanted to compare the price of housing. But I could not find a properly documented and easily downloaded dataset hence I created one with the help of web-scraping with Python and Pandas.

Content

I spent a lot of time searching for a source for the information I wanted in order to compare affordability. I stumbled upon a great website which was exactly what I was looking for Numbeo The website has a lot of details like affordability index, prime to income ratio, price to rent ratios in and out of city centre and more!

Now I had the data, I needed to download it. Since I couldn't get the raw form of the data, I did web scraping in order to get details in the table for 2009 to 2021 using a for loop to go through all links and create csv files for every year.

What's in the dataset?

Details of columns Note: There are a few null values in the 2009 dataset (mortgage and Affordability Index columns.

Check out the code I used on Github.

Acknowledgements

I couldn't have gotten the data without Numbeo!

Inspiration

I was working on a project trying to see if Price of Housing in Singapore can be justified and wanted more data that's global instead of just from Singapore. Let me know if you have any questions!

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

15 Year Mortgage Rate in the United States decreased to 5.71 percent in August 14 from 5.75 percent in the previous week. This dataset includes a chart with historical data for the United States 15 Year Mortgage Rate.

Minority-Interest-Expense Time Series for Blend Labs Inc. Blend Labs, Inc. provides a cloud-based software platform for financial services firms in the United States. It operates in two segments, Blend Platform and Title. The company offers a suite of products that powers digital-first consumer journeys for mortgages, home equity loans and lines of credit, vehicle loans, personal loans, credit cards, and deposit accounts; and a suite of add-on products that offers to enhance consumers' journeys to homeownership, such as close, income verification for mortgage and home equity, homeowners' insurance, and title. It also provides Blend Builder to configure or build custom workflows from a pre-built set of components; verification components to automate confirmation tasks that are needed to underwrite a loan or approve the opening of a new deposit account; decisioning components to reduce the need for human intervention by automatically applying business rules throughout an application workflow configured by a financial services firm; and workflow intelligence components to manage data collection and automate tasks throughout the loan origination process. In addition, the company offers title search procedures for title insurance policies, escrow, and other closing and settlement services; and other trustee services, as well as professional and consulting services. It serves banks, credit unions, fintechs, and other non-bank mortgage lenders. The company was incorporated in 2012 and is headquartered in Novato, California.

Ebit-Interest-Coverage Time Series for Flushing Financial Corporation. Flushing Financial Corporation operates as the bank holding company for Flushing Bank that provides banking products and services primarily to consumers, businesses, and governmental units. It offers various deposit products, including checking and savings accounts, money market accounts, non-interest bearing demand accounts, NOW accounts, and certificates of deposit. The company provides mortgage loans secured by multi-family residential, commercial real estate, one-to-four family mixed-use property, one-to-four family residential property, and commercial business loans; construction loans; small business administration loans and other small business loans; mortgage loan surrogates, such as mortgage-backed securities; and consumer loans, including overdraft lines of credit, as well as the United States government securities, corporate fixed-income securities, and other marketable securities. It operates full-service banking offices in Queens, Nassau, Suffolk, Kings, and New York counties, New York; and an internet branch under the iGObanking and BankPurely brands. The company was founded in 1929 and is based in Uniondale, New York.

Austria Lending Rate: NB: Households: Mortgage: Rate Fixation: Between 5 and 10 Years data was reported at 3.320 % pa in Mar 2025. This records an increase from the previous number of 3.250 % pa for Feb 2025. Austria Lending Rate: NB: Households: Mortgage: Rate Fixation: Between 5 and 10 Years data is updated monthly, averaging 3.540 % pa from Jan 2003 (Median) to Mar 2025, with 267 observations. The data reached an all-time high of 5.740 % pa in Jun 2004 and a record low of 1.320 % pa in Jul 2021. Austria Lending Rate: NB: Households: Mortgage: Rate Fixation: Between 5 and 10 Years data remains active status in CEIC and is reported by Oesterreichische Nationalbank. The data is categorized under Global Database’s Austria – Table AT.M004: Lending Rates.

The benchmark interest rate in Mexico was last recorded at 7.75 percent. This dataset provides - Mexico Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This data set provides recent market information on corporate loan transactions (339 records based on 187 agreements) sourced from filings by US SEC Registrants in all non-financial industries for the First Quarter 2021 (Q1 2021). Of the 339 records there are 8 loan transactions with credit rating equal to or higher than A-, 55 records in the BBB letter category, 47 records in the BB letter category, 46 records in the B letter category, 11 records that are rated at less than B-, and 172 records that are not rated. These 339 corporate loan transactions span the 11 GICS Sectors as follows: Energy 12; Materials 38; Industrials 50; Consumer Discretionary 86; Consumer Staples 20; Healthcare 31; Financials (mainly REITS, excludes FIs) 50; Information Technology 14; Communication Services 8; Utilities 20; and Real Estate 10. The following categories of data are described as follows: 1) Filing Information (with 7 data fields) includes the Filing Company Name, Filing Date, Filing Form and Type of Agreement (credit agreement, amended and restated credit agreement, or an amendment to a credit agreement), and Filing Company’s Central Index Key (CIK), SIC Code and GICS Sector Name; 2) Borrower and Other Loan Participant Details (6 data fields) includes the Primary Borrower’s Name, the Primary Borrower’s country of incorporation, the name(s) of additional borrowers, the name(s) of guarantors, the relationship of the guarantor(s) to the primary borrower, the name(s) of the lead arranger(s)/lender(s); 3) Credit Rating Information (17 data fields) includes publicly available S&P credit ratings and Moody’s credit ratings, if available, as at the date of the credit agreement for Primary Borrower, Parent, Issue and the respective dates of the ratings; 4) Loan Characteristics (16 data fields) includes whether the loan is a revolver or term loan, senior secured or senior unsecured, or other asset class. Also includes data on the loan amount, currency, pricing notes, collateral type, and types of financial covenants; and 5) Loan Pricing Details (11 data fields) includes the type of reference interest rate (e.g., LIBOR), the lending margin (or the fixed rate), commitment fee, annual (facility) fee, and other types of fees, as well as notes and other information related to the pricing. This data/information would assist any company’s finance & treasury department in negotiating pricing with banks/lenders or a multinational corporation’s international tax department to price its intercompany loans for transfer pricing purposes. CUFTanalytics has a database of over 14,000 records from corporate loan transactions from January 2009 to present day.

Abstract copyright UK Data Service and data collection copyright owner.The Family Resources Survey (FRS) has been running continuously since 1992 to meet the information needs of the Department for Work and Pensions (DWP). It is almost wholly funded by DWP. The FRS collects information from a large, and representative sample of private households in the United Kingdom (prior to 2002, it covered Great Britain only). The interview year runs from April to March.The focus of the survey is on income, and how much comes from the many possible sources (such as employee earnings, self-employed earnings or profits from businesses, and dividends; individual pensions; state benefits, including Universal Credit and the State Pension; and other sources such as savings and investments). Specific items of expenditure, such as rent or mortgage, Council Tax and water bills, are also covered.Many other topics are covered and the dataset has a very wide range of personal characteristics, at the adult or child, family and then household levels. These include education, caring, childcare and disability. The dataset also captures material deprivation, household food security and (new for 2021/22) household food bank usage. The FRS is a national statistic whose results are published on the gov.uk website. It is also possible to create your own tables from FRS data, using DWP’s Stat Xplore tool. Further information can be found on the gov.uk Family Resources Survey webpage. Safe Room Access FRS data In addition to the standard End User Licence (EUL) version, Safe Room access datasets, containing unrounded data and additional variables, are also available for FRS from 2005/06 onwards - see SN 7196, where the extra contents are listed. The Safe Room version also includes secure access versions of the Households Below Average Income (HBAI) and Pensioners' Incomes (PI) datasets. The Safe Room access data are currently only available to UK HE/FE applicants and for access at the UK Data Archive's Safe Room at the University of Essex, Colchester. Prospective users of the Safe Room access version of the FRS/HBAI/PI will need to fulfil additional requirements beyond those associated with the EUL datasets. Full details of the application requirements are available from Guidance on applying for the Family Resources Survey: Secure Access.FRS, HBAI and PIThe FRS underpins the related Households Below Average Income (HBAI) dataset, which focuses on poverty in the UK, and the related Pensioners' Incomes (PI) dataset. The EUL versions of HBAI and PI are held under SNs 5828 and 8503 respectively. The secure access versions are held within the Safe Room FRS study under SN 7196 (see above). The FRS aims to: support the monitoring of the social security programme; support the costing and modelling of changes to national insurance contributions and social security benefits; provide better information for the forecasting of benefit expenditure. From April 2002, the FRS was extended to include Northern Ireland. Detailed information regarding anonymisation within the FRS can be found in User Guide 2 of the dataset documentation. For the second edition (October 2014) the data have been re-grossed following revision of the FRS grossing methodology to take account of the 2011 Census mid-year population estimates. New variable GROSS4 has been added to the dataset. Main Topics: Household characteristics (composition, tenure type); tenure and housing costs including Council Tax, mortgages, insurance, water and sewage rates; welfare/school milk and meals; educational grants and loans; children in education; informal care (given and received); childcare; occupation and employment; health restrictions on work; children's health; National Health Service treatment; wage details; self-employed earnings; personal and occupational pension schemes; income and benefit receipt; income from pensions and trusts, royalties and allowances, maintenance and other sources; income tax payments and refunds; National Insurance contributions; earnings from odd jobs; children's earnings; interest and dividends; investments; National Savings products; assets; vehicle ownership. Standard Measures Standard Occupational Classification Multi-stage stratified random sample Face-to-face interview Computer Assisted Personal Interviewing 2005 2006 ABSENTEEISM ACADEMIC ACHIEVEMENT ADMINISTRATIVE AREAS AGE APARTMENTS APPLICATION FOR EMP... APPOINTMENT TO JOB ATTITUDES BANK ACCOUNTS BEDROOMS BONDS BONUS PAYMENTS BUILDING SOCIETY AC... BUSES BUSINESS RECORDS CARE OF DEPENDANTS CARE OF THE DISABLED CARE OF THE ELDERLY CARS CHARITABLE ORGANIZA... CHILD BENEFITS CHILD CARE CHILD DAY CARE CHILD MINDERS CHILD MINDING CHILD SUPPORT PAYMENTS CHILD WORKERS CHILDREN CHRONIC ILLNESS COHABITATION COLOUR TELEVISION R... COMMERCIAL BUILDINGS CONCESSIONARY TELEV... CONSUMPTION CONTACT LENSES COUNCIL TAX CREDIT UNIONS Consumption and con... DAY NURSERIES DEBILITATIVE ILLNESS DEBTS DENTISTS DISABILITIES DISABILITY DISCRIMI... DISABLED CHILDREN DISABLED PERSONS DOMESTIC RESPONSIBI... ECONOMIC ACTIVITY ECONOMIC VALUE EDUCATION EDUCATIONAL BACKGROUND EDUCATIONAL FEES EDUCATIONAL GRANTS EDUCATIONAL INSTITU... EDUCATIONAL VOUCHERS ELDERLY EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ENDOWMENT ASSURANCE ETHNIC GROUPS EXPENDITURE EYESIGHT TESTS FAMILIES FAMILY MEMBERS FINANCIAL DIFFICULTIES FINANCIAL INSTITUTIONS FINANCIAL RESOURCES FINANCIAL SUPPORT FOOD FREE SCHOOL MEALS FRIENDS FRINGE BENEFITS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... FURTHER EDUCATION Family life and mar... GENDER GIFTS GRANDPARENTS GRANTS HEADS OF HOUSEHOLD HEALTH HEALTH SERVICES HEARING IMPAIRED PE... HEARING IMPAIRMENTS HIGHER EDUCATION HOLIDAY LEAVE HOME BASED WORK HOME OWNERSHIP HOME SHARING HOURS OF WORK HOUSEHOLD BUDGETS HOUSEHOLD HEAD S OC... HOUSEHOLDS HOUSING HOUSING FACILITIES HOUSING FINANCE HOUSING TENURE INCOME INCOME TAX INDUSTRIES INSURANCE INSURANCE PREMIUMS INTEREST FINANCE INVESTMENT INVESTMENT RETURN Income JOB DESCRIPTION JOB HUNTING JOB SEEKER S ALLOWANCE LANDLORDS LEAVE LOANS LODGERS MANAGERS MARITAL STATUS MARRIED WOMEN MARRIED WOMEN WORKERS MATERNITY LEAVE MATERNITY PAY MEDICAL PRESCRIPTIONS MORTGAGE PROTECTION... MORTGAGES MOTORCYCLES NEIGHBOURS Northern Ireland OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OCCUPATIONS ONE PARENT FAMILIES OVERTIME PARENTS PART TIME COURSES PART TIME EMPLOYMENT PARTNERSHIPS BUSINESS PASSENGERS PATERNITY LEAVE PENSION CONTRIBUTIONS PENSIONS PHYSICALLY DISABLED... PHYSICIANS POVERTY PRIVATE EDUCATION PRIVATE PERSONAL PE... PRIVATE SCHOOLS PROFITS QUALIFICATIONS RATES REBATES REDUNDANCY REDUNDANCY PAY RENTED ACCOMMODATION RENTS RESIDENTIAL MOBILITY RETIREMENT ROOM SHARING ROOMS ROYALTIES SAVINGS SAVINGS ACCOUNTS AN... SCHOLARSHIPS SCHOOL MILK PROVISION SCHOOLCHILDREN SCHOOLS SEASONAL EMPLOYMENT SECONDARY EDUCATION SECONDARY SCHOOLS SELF EMPLOYED SEWAGE DISPOSAL AND... SHARES SHIFT WORK SICK LEAVE SICK PAY SICK PERSONS SOCIAL CLASS SOCIAL HOUSING SOCIAL SECURITY SOCIAL SECURITY BEN... SOCIAL SECURITY CON... SOCIAL SERVICES SOCIAL SUPPORT SOCIO ECONOMIC STATUS SPECIAL EDUCATION SPECTACLES SPOUSES STATE EDUCATION STATE HEALTH SERVICES STATE RETIREMENT PE... STUDENT HOUSING STUDENT LOANS STUDENTS STUDY SUBSIDIARY EMPLOYMENT SUPERVISORS SUPERVISORY STATUS Social stratificati... TAXATION TELEVISION LICENCES TELEVISION RECEIVERS TEMPORARY EMPLOYMENT TENANCY AGREEMENTS TENANTS HOME PURCHA... TERMINATION OF SERVICE TIED HOUSING TIME TOP MANAGEMENT TRAINING UNEARNED INCOME UNEMPLOYED UNEMPLOYMENT BENEFITS UNFURNISHED ACCOMMO... UNWAGED WORKERS VEHICLES VISION IMPAIRMENTS VISUALLY IMPAIRED P... VOCATIONAL EDUCATIO... VOLUNTARY WORK WAGES WIDOWED WORKING MOTHERS WORKING WOMEN property and invest...

Abstract copyright UK Data Service and data collection copyright owner.The Opinions and Lifestyle Survey (formerly known as the ONS Opinions Survey or Omnibus) is an omnibus survey that began in 1990, collecting data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules. The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain. From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers. In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, Covid-19 Module, 2020-2022: Secure Access. From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable. The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage.Secure Access Opinions and Lifestyle Survey dataOther Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093). See Opinions and Lifestyle Survey: Secure Access for details. Main Topics:Each month's questionnaire consists of two elements: core questions, covering demographic information, are asked each month together with non-core questions that vary from month to month. The non-core questions for this month were: Financial capability (Module 336): this module was asked on behalf of the Financial Services Authority. The purpose of the module was to gain a general view of how respondents who have a mortgage or rent their property would cope with a change to their circumstances, such as an increase to their mortgage or rent payment or a rise in interest rates. It also asks all respondents about type and amount of debt and how the individual or family who have a mortgage or rent their property would cope with 'shock' changes to income. Disability monitoring (Module 363): the Special Licence version of this module is held under SN 6470. Road pricing (Module MAE): this module was asked on behalf of the Department for Transport and asks for opinions on road pricing. Older workers (Module MAW): this module was asked on behalf of the Centre for Research into the Older Workforce (CROW) and examines work based training opportunities for older workers. Multi-stage stratified random sample Face-to-face interview

The benchmark interest rate in Japan was last recorded at 0.50 percent. This dataset provides - Japan Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate in the United Kingdom was last recorded at 4 percent. This dataset provides - United Kingdom Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Bank Lending Rate in the United States remained unchanged at 7.50 percent in July. This dataset provides - United States Average Monthly Prime Lending Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Austria Lending Rate: NB: Households: Mortgage: Rate Fixation: Between 1 and 5 Years data was reported at 3.490 % pa in Mar 2025. This records a decrease from the previous number of 3.650 % pa for Feb 2025. Austria Lending Rate: NB: Households: Mortgage: Rate Fixation: Between 1 and 5 Years data is updated monthly, averaging 2.590 % pa from Jan 2003 (Median) to Mar 2025, with 267 observations. The data reached an all-time high of 4.840 % pa in Nov 2008 and a record low of 1.210 % pa in Jan 2021. Austria Lending Rate: NB: Households: Mortgage: Rate Fixation: Between 1 and 5 Years data remains active status in CEIC and is reported by Oesterreichische Nationalbank. The data is categorized under Global Database’s Austria – Table AT.M004: Lending Rates.