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.

The 10-year treasury constant maturity rate in the U.S. is forecast to increase by *** percentage points by 2027, while the 30-year fixed mortgage rate is expected to fall by *** percentage points. From *** percent in 2024, the average 30-year mortgage rate is projected to reach *** percent in 2027.

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

Mortgage Loan Service Market Outlook

The global mortgage loan service market size was valued at approximately $10.5 trillion in 2023 and is projected to reach around $18.2 trillion by 2032, growing at a CAGR of 6.1% during the forecast period. The growth of this market is driven by the increasing urbanization, rising disposable incomes, and favorable government policies aimed at promoting homeownership across various regions. Additionally, the proliferation of digital banking and fintech solutions has made mortgage services more accessible, further contributing to the market's expansion.

One of the primary growth factors for the mortgage loan service market is the significant rise in housing demand globally. As urban populations swell and economic conditions improve, more individuals and families are seeking to purchase homes, driving the need for mortgage loans. This trend is particularly evident in emerging markets, where urbanization is occurring at an unprecedented rate. Governments are also playing a crucial role by implementing policies and grants to make housing more affordable, thereby boosting mortgage adoption.

Technological advancements are another significant factor propelling the mortgage loan service market. The integration of AI, big data analytics, and blockchain technology has revolutionized the way mortgage services are delivered. These technologies streamline application processes, enhance risk assessment, and improve customer service, making it easier and faster for consumers to secure loans. Fintech companies, in particular, are leveraging these technologies to offer more competitive rates and personalized loan products, thereby attracting a broader customer base.

Furthermore, the increasing participation of non-banking financial institutions (NBFIs) and credit unions has diversified the mortgage loan service market. These entities often provide more flexible and innovative loan products compared to traditional banks, meeting the needs of a more varied clientele. NBFIs and credit unions also tend to have more lenient approval processes, making them an attractive option for individuals with non-traditional income sources or lower credit scores. This diversification is contributing significantly to the market's growth.

Mortgage Loans Software is playing an increasingly pivotal role in the evolution of the mortgage loan service market. As the industry embraces digital transformation, software solutions are being developed to streamline the entire mortgage process, from application to approval. These software platforms facilitate better data management, enhance customer experience, and improve operational efficiency for service providers. By automating routine tasks and providing real-time analytics, Mortgage Loans Software helps lenders make more informed decisions, reduce processing times, and minimize errors. This technological advancement is not only beneficial for lenders but also empowers borrowers by offering them greater transparency and control over their mortgage journey.

Regionally, North America continues to dominate the mortgage loan service market due to its well-established financial infrastructure and high homeownership rates. However, the Asia Pacific region is expected to register the fastest growth during the forecast period, driven by rapid urbanization, rising incomes, and government initiatives aimed at affordable housing. Countries like China and India are particularly noteworthy due to their large and growing middle-class populations.

Type Analysis

The mortgage loan service market is segmented by type into fixed-rate mortgages, adjustable-rate mortgages, interest-only mortgages, reverse mortgages, and others. Fixed-rate mortgages are the most popular type, offering borrowers the stability of a constant interest rate over the life of the loan. This makes them particularly attractive in times of low-interest rates, as borrowers can lock in favorable terms for the long term. The predictability of monthly payments also makes fixed-rate mortgages a preferred choice for many homeowners.

Adjustable-rate mortgages (ARMs) offer lower initial interest rates compared to fixed-rate mortgages, making them an attractive option for borrowers who anticipate an increase in their income or plan to sell their property before the rate adjusts. However, the fluctuating interest rates can pose a risk, especially in volatile economic conditions. Despite this, the flexibility

Interactive historical chart showing the 30 year fixed rate mortgage average in the United States since 1971.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

What are 30 year mortgage rates?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Graph and download economic data for 15-Year Fixed Rate Mortgage Average in the United States (MORTGAGE15US) from 1991-08-30 to 2025-07-03 about 15-year, fixed, mortgage, interest rate, interest, rate, and USA.

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.

Bulgaria was at the top of this ranking of ** European countries sorted by the growth rate of their volume of loans to households in 2023. Loans to households in the European Union and the European Economic Area are expected to grow on average by over ***** percent in 2024. Meanwhile, the loans and advances market in Germany is expected to increase by *** percent in 2024. Overall, the total value of the household loans market in the EU as a whole is expected to keep growing during that timeline.

Brand performance data collected from AI search platforms for the query "mortgage rate forecast 2025".

Mortgage interest rates worldwide varied greatly in 2024, from less than **** percent in many European countries, to as high as ** percent in Turkey. The average mortgage rate in a country depends on the central bank's base lending rate and macroeconomic indicators such as inflation and forecast economic growth. Since 2022, inflationary pressures have led to rapid increase in mortgage interest rates. Which are the leading mortgage markets? An easy way to estimate the importance of the mortgage sector in each country is by comparing household debt depth, or the ratio of the debt held by households compared to the county's GDP. In 2023, Switzerland, Australia, and Canada had some of the highest household debt to GDP ratios worldwide. While this indicator shows the size of the sector relative to the country’s economy, the value of mortgages outstanding allows to compare the market size in different countries. In Europe, for instance, the United Kingdom, Germany, and France were the largest mortgage markets by outstanding mortgage lending. Mortgage lending trends in the U.S. In the United States, new mortgage lending soared in 2021. This was largely due to the growth of new refinance loans that allow homeowners to renegotiate their mortgage terms and replace their existing loan with a more favorable one. Following the rise in interest rates, the mortgage market cooled, and refinance loans declined.

Residential Mortgage Loan Market Outlook

The global residential mortgage loan market size was valued at approximately USD 15 trillion in 2023 and is projected to reach around USD 25 trillion by 2032, growing at a compound annual growth rate (CAGR) of 6.1% over the forecast period. The primary growth drivers for this market include increasing urbanization, rising disposable incomes, and favorable government policies aimed at promoting home ownership.

One of the most significant factors contributing to the growth of the residential mortgage loan market is urbanization. As more people move to urban areas in search of better opportunities and living conditions, the demand for residential properties has surged. This urban migration has led to a corresponding increase in the demand for mortgage loans, as individuals seek financial assistance to purchase homes. Additionally, the trend of nuclear families is gaining traction, further boosting the demand for residential properties and, consequently, mortgage loans.

Rising disposable incomes and improved economic conditions have also played a crucial role in the expansion of the residential mortgage loan market. As people earn more, they are more likely to invest in real estate, viewing homeownership as a long-term investment and a means of financial security. Furthermore, low-interest rates on mortgage loans, driven by monetary policies of various countries, have made borrowing more affordable, encouraging more people to take out mortgage loans.

Government policies and initiatives aimed at promoting homeownership have significantly fueled the growth of the residential mortgage loan market. Many countries offer tax incentives, subsidies, and lower interest rates for first-time homebuyers and low-income groups. Such policies are designed to make homeownership more accessible and affordable, driving the demand for mortgage loans. Additionally, governments are increasingly collaborating with financial institutions to provide affordable housing solutions, further stimulating market growth.

On a regional level, North America and Europe have traditionally dominated the residential mortgage loan market due to their mature real estate markets and high homeownership rates. However, emerging economies in the Asia Pacific and Latin America regions are witnessing rapid growth in this sector. Factors such as increasing population, urbanization, and rising middle-class incomes are driving the demand for residential mortgage loans in these regions. Moreover, favorable government policies and a growing number of financial institutions offering mortgage products are further contributing to market expansion.

Type Analysis

The residential mortgage loan market is segmented by type into fixed-rate mortgages, adjustable-rate mortgages, interest-only mortgages, and others. Fixed-rate mortgages are the most popular type, owing to their stability and predictability. Borrowers prefer fixed-rate mortgages because they offer a consistent monthly payment plan, making it easier for them to budget and plan their finances. This stability is particularly appealing during times of economic uncertainty or fluctuating interest rates.

Adjustable-rate mortgages (ARMs), on the other hand, offer lower initial interest rates compared to fixed-rate mortgages. However, the rate can fluctuate based on market conditions, which can either be an advantage or a risk for borrowers. ARMs are often chosen by those who plan to sell or refinance their homes before the adjustable period begins. This type of mortgage is popular among borrowers who are willing to take a risk for the potential benefit of lower initial costs.

Interest-only mortgages allow borrowers to pay only the interest on the loan for a specified period, usually between five to ten years. After this period, the borrower must start paying both the principal and the interest, resulting in higher monthly payments. Interest-only mortgages are typically utilized by investors or those expecting a significant increase in income in the future. This type allows for lower initial payments, providing greater cash flow flexibility in the short term.

The 'Others' category includes various specialized mortgage products tailored to meet specific borrower needs. These can include reverse mortgages, which allow seniors to convert part of their home equity into cash, and jumbo loans, which cater to borrowers looking to finance luxury homes that exceed conforming loan limits. The diversity in mortgage types ensures that there are suitab

Canada Conventional Mortgage: 5 Years: Weekly data was reported at 6.490 % pa in 07 May 2025. This stayed constant from the previous number of 6.490 % pa for 30 Apr 2025. Canada Conventional Mortgage: 5 Years: Weekly data is updated weekly, averaging 5.700 % pa from Jan 2000 (Median) to 07 May 2025, with 1323 observations. The data reached an all-time high of 8.750 % pa in 31 May 2000 and a record low of 4.640 % pa in 12 Jul 2017. Canada Conventional Mortgage: 5 Years: Weekly data remains active status in CEIC and is reported by Bank of Canada. The data is categorized under Global Database’s Canada – Table CA.M005: Conventional Mortgage Rate. [COVID-19-IMPACT]

Forecast: Household Expenditure on Mortgage Interest and Charges in the US 2022 - 2026 Discover more data with ReportLinker!

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Mortgage Rates: Hot Economic Conjecture Puts the Squeeze on Homebuyers

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

The benchmark interest rate in Sweden was last recorded at 2 percent. This dataset provides the latest reported value for - Sweden Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Due to interest rates decreasing in recent years, mortgages in the United Kingdom have become overall more affordable: In 2007, when mortgages were the least affordable, a home buyer spent on average 23.6 percent of their income on mortgage interest and 7.2 percent on capital repayment. In 2019, the year with the most affordable mortgages, mortgage interest accounted for 5.9 percent and capital repayment was 11.5 percent of their income. As interest rates increase in response to the rising inflation, mortgage affordability is expected to worsen. Though below the levels observed before 2007, the total mortgage repayment between 2022 and 2026 is expected to exceed 23 percent of income.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Mortgage Rates Soar, Making Homeownership Out of Reach for Many

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

The global mortgage loan service market is experiencing robust growth, driven by factors such as increasing urbanization, rising disposable incomes, and favorable government policies promoting homeownership. The market, valued at approximately $2 trillion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 6% from 2025 to 2033. This expansion is fueled by a burgeoning demand for both residential and commercial mortgages, particularly in emerging economies with rapidly expanding middle classes. The residential segment currently dominates the market share, accounting for approximately 70%, with individual borrowers representing the largest application segment. However, the commercial estate and enterprise segments are witnessing significant growth, driven by increased corporate investments and infrastructural development. Key players like Rocket Mortgage, United Shore Financial Services, and Quicken Loans are leveraging technological advancements such as online platforms and AI-powered loan processing to enhance efficiency and customer experience, shaping the competitive landscape. The growth trajectory is expected to be influenced by fluctuating interest rates, macroeconomic conditions, and evolving regulatory frameworks. Nevertheless, the long-term outlook remains positive, underpinned by the fundamental drivers mentioned above. Technological advancements, particularly in fintech, are reshaping the mortgage loan service landscape. The rise of digital platforms, streamlined application processes, and enhanced data analytics are significantly improving accessibility and speed of loan approvals. This efficiency boost is leading to increased competition, encouraging lenders to offer more competitive interest rates and flexible repayment options to attract borrowers. Furthermore, the increasing adoption of alternative credit scoring models is broadening access to mortgage loans for previously underserved populations. Regional variations in market growth are expected, with North America and Asia-Pacific representing the largest markets. However, emerging economies in regions like South America and Africa hold significant potential for future growth, given the increasing demand for housing and infrastructural development within these markets. Geographic expansion and strategic partnerships remain key strategies for players aiming for market dominance within this evolving sector.

The US mortgage lending market, a cornerstone of the American economy, is experiencing robust growth, projected to maintain a Compound Annual Growth Rate (CAGR) exceeding 5% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, a consistently increasing population and household formations drive demand for housing, consequently boosting mortgage loan originations. Secondly, historically low interest rates in recent years have stimulated borrowing, making homeownership more accessible. Furthermore, government initiatives aimed at supporting homeownership, along with increasing disposable incomes in certain segments of the population, contribute to the market's positive trajectory. The market is segmented by loan type (fixed-rate mortgages and home equity lines of credit), service providers (commercial banks, financial institutions, credit unions, and other lenders), and application mode (online and offline). Competition is intense among major players like Bank of America, Chase Bank, and US Bank, with smaller institutions and credit unions vying for market share. While the overall trend is positive, potential headwinds include fluctuations in interest rates, economic downturns impacting consumer confidence, and stringent regulatory environments which can impact lending practices. The geographical distribution of the US mortgage lending market reflects regional economic variations. While the United States dominates North America's market share, growth potential exists across various international markets. European and Asian markets, though characterized by distinct regulatory landscapes and consumer behaviors, present opportunities for expansion. The market's future trajectory will depend on several interconnected factors, including macroeconomic conditions, demographic shifts, and technological advancements influencing the mortgage lending process. The continued adoption of digital technologies is expected to streamline lending processes and expand access, impacting the future of the market significantly. Strategic partnerships and acquisitions are also anticipated, further consolidating the market landscape and driving innovation. Recent developments include: August 2023: Spring EQ, a provider of home equity financing solutions, has entered into a definitive agreement to be acquired by an affiliate of Cerberus Capital Management, L.P., a global leader in alternative investing. The main aim of the partnership is to support Spring EQ's mission to deliver offerings and expand its leadership in the home equity financing market., June 2023: VIU by HUB, a digital insurance brokerage platform subsidiary of Hub International Limited, has entered into a new partnership with Unison, a home equity-sharing company. The collaboration will allow homeowners to compare insurance coverage quotes from various carriers and receive expert advice throughout the process.. Key drivers for this market are: Home Renovation Trends are Driving the Market. Potential restraints include: Home Renovation Trends are Driving the Market. Notable trends are: Home Equity Lending Market is Being Stimulated By Rising Home Prices.