Fixed 30-year mortgage rates in the United States averaged 6.69 percent in the week ending August 22 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.

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

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

The value of the loan portfolio of banks to households was expected to grow the most in Hungary and Bulgaria in 2025 and 2026. Meanwhile, bank loans to households in Germany, Italy, and France were forecast to have low growth rates, staying under *** percent in 2025. Overall, the total value of the household loans market in the EU as a whole is expected to keep growing in the next few years.

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 **** percent of their income on mortgage interest and *** percent on capital repayment. In 2019, the year with the most affordable mortgages, mortgage interest accounted for *** percent and capital repayment was **** 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 ** percent of income.

The Global Home Loan Market Report is Segmented by Loan Purpose (Purchase, Home Improvement/Renovation, Others), Provider (Banks, Housing Finance Companies, Others), Interest Rates (Fixed Interest Rates, Floating Interest Rates), Loan Tenure (Less Than or Equal To 10 Years, 11 – 20 Years, and More), and Geography (North America, South America, and More). The Market Forecasts are Provided in Terms of Value (USD).

US Mortgage/Loan Brokers Market Analysis The US mortgage/loan brokers market is substantial, valued at USD XX million in 2025 with a projected CAGR of 5.00% during 2025-2033. This growth is attributed to factors such as rising demand for home ownership, increasing home values, and low interest rates. The market is segmented by component (products, services), enterprise (large, small, medium-sized), application (home loans, commercial loans, etc.), end-user (business, individuals), and region. Prominent players include Quicken Loans, Wells Fargo, and Caliber Home Loans. Market Drivers and Trends The growth of the US mortgage/loan brokers market is driven by several factors, including the increasing demand for residential and commercial construction, government incentives for home ownership, and the availability of various loan options. Additionally, technological advancements, such as online loan applications and mobile banking, are simplifying the loan application process. However, rising interest rates and stricter lending regulations pose potential challenges to the market's growth. Nonetheless, the growing need for mortgages and the increasing complexity of loan processes are expected to drive the market's expansion in the coming years. Recent developments include: November 2022: A digital home equity line of credit was introduced by loanDepot, one of the country's biggest non-bank retail mortgage lenders, against the backdrop of inflation and rising consumer debt., October 2022: Pennymac Financial Services launched POWER+, its next generation broker technology platform. Brokers will now have more speed and control over the mortgage process to deliver an exceptional experience to their customers and referral partners.. Notable trends are: Adoption of the New Technologies Driving the Market.

Type of Mortgage Loan:Conventional Mortgage Loans: Backed by private investors and typically require a down payment of 20% or more.Jumbo Loans: Loans that exceed the conforming loan limits set by Fannie Mae and Freddie Mac.Government-insured Mortgage Loans: Backed by the Federal Housing Administration (FHA), Department of Veterans Affairs (VA), or U.S. Department of Agriculture (USDA).Others: Includes non-QM loans, reverse mortgages, and shared equity programs.Mortgage Loan Terms:30-year Mortgage: The most common term, offering low monthly payments but higher overall interest costs.20-year Mortgage: Offers a shorter repayment period and lower long-term interest costs.15-year Mortgage: The shortest term, providing lower interest rates and faster equity accumulation.Others: Includes adjustable-rate mortgages (ARMs) and balloons loans.Interest Rate:Fixed-rate Mortgage Loan: Offers a stable interest rate over the life of the loan.Adjustable-rate Mortgage Loan (ARM): Offers an initial interest rate that may vary after a certain period, potentially leading to higher or lower monthly payments.Provider:Primary Mortgage Lender: Originates and services mortgages directly to borrowers.Secondary Mortgage Lender: Purchases mortgages from originators and packages them into securities for sale to investors. Key drivers for this market are: Digital platforms and AI-driven credit assessments have simplified the application process, improving accessibility and borrower experience. Potential restraints include: Fluctuations in interest rates significantly impact borrowing costs, affecting loan demand and affordability. Notable trends are: The adoption of online portals and mobile apps is transforming the mortgage process with faster approvals and greater transparency.

The North America mortgage/loan brokers market is poised for steady growth, with a market size of XX million and a CAGR of 5.00% during the forecast period of 2025-2033. The market is driven by rising homeownership rates, increasing mortgage interest rates, and growing demand for refinancing. Additionally, the emergence of fintech companies offering innovative mortgage products and services is further propelling market growth. Key market trends include the increasing use of technology to improve the mortgage process, the growing popularity of jumbo loans, and the rising demand for reverse mortgages. However, the market is also subject to certain restraints, such as regulatory changes and economic downturns. Major players in the market include Penny Mac, Home Point, Caliber Home Loans, and Fairway Independent Corporation. The United States is the largest market for mortgage/loan brokers in North America, followed by Canada. Recent developments include: In November 2022, To expand the use of eNotes across 250 locations in 49 states, Primary Residential Mortgage Inc. (PRMI) employed the eVault and digital closing platform from Snapdocs., In August 2022, Due to the slowdown in home sales caused by rising interest rates, the two biggest mortgage lenders in the US are increasing pressure on their smaller rivals by providing discounts and other incentives. The two biggest mortgage originators in the US, Rocket Mortgage and United Wholesale Mortgage, respectively, are pursuing aggressive strategies at a time when many lenders are leaving the market or going out of business.. Notable trends are: Increase in Digitization in Lending and Blockchain Technology is driving the market.

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 is a second mortgage?

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

Market Analysis for Digital Mortgage Software The global digital mortgage software market is expanding rapidly, driven by a surge in digitalization and technological advancements within the mortgage industry. In 2025, the market size was valued at 7885.3 million USD, with a CAGR of XX% projected over the forecast period from 2025 to 2033. The market growth is primarily attributed to the increasing demand for efficient and streamlined mortgage processes, digitization efforts in the banking and financial sector, and growing adoption of cloud-based solutions. The digital mortgage software market is segmented based on deployment type (cloud-based, on-premises), application (retail lending, residential mortgage, trade finance, others), and region. Major players in the market include Roostify, Ellie Mae, Blend, StreamLoan, Maxwell, SimpleNexus, Salesforce, Cloudvirga, and Blue Sage Solutions. North America dominates the market, followed by Europe and Asia-Pacific. Key market trends include the increasing adoption of artificial intelligence (AI) and machine learning (ML) for loan origination, automated underwriting, and risk assessment, as well as the growing popularity of mobile-friendly mortgage solutions.

The global mortgage lender market is expected to exhibit robust growth over the forecast period, driven by several factors. Increasing urbanization, a growing middle class, and favorable government policies are fueling the demand for residential and commercial real estate, stimulating the need for mortgage financing. Additionally, low mortgage rates and rising disposable income levels are making homeownership more accessible, further propelling market growth. The market for mortgage lenders is highly competitive, with large financial institutions, regional banks, and non-bank lenders vying for market share. Key players in the industry include Wells Fargo Bank, JPMorgan Chase Bank, Bank of America, and Quicken Loans. These companies offer various mortgage products and services, including fixed-rate mortgages, adjustable-rate mortgages, jumbo loans, and government-backed loans, to cater to the diverse needs of borrowers. The market is segmented by application (new house, second-hand house), type (residential, commercial/estate), and region (North America, South America, Europe, Asia Pacific, Middle East & Africa). North America and Europe are expected to remain the largest regional markets, while Asia Pacific is projected to experience significant growth due to its large population and rapidly expanding economies. The mortgage lending industry is subject to regulatory changes and economic fluctuations, which can impact market dynamics. However, the industry is resilient and well-positioned for continued growth in the coming years.

More than ************* mortgage loans are projected to be affected by the increasing mortgage interest rates in Canada by 2025. About *********** of these mortgages are projected to be up for renewal in 2024. These loans were taken out at a time when interest rates were much lower, meaning that homeowners will be affected by a notable increase in their monthly payments.

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.

This dataset provides values for 15 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.

The global digital mortgage software market is projected to reach $3,190.9 million by 2033, growing at a CAGR of 16.8% from 2025 to 2033. The market growth is attributed to the increasing adoption of digital mortgage solutions by lenders to automate and streamline the mortgage process, reduce paperwork, and improve customer experience. Key drivers include rising homeownership rates, increasing demand for affordable housing, and the growing popularity of online mortgage applications. Prominent market trends include the integration of artificial intelligence (AI) and machine learning (ML) to automate tasks, enhance underwriting accuracy, and improve decision-making. The market is segmented by application into retail lending, residential mortgage, trade finance, and others. Cloud-based solutions are gaining traction due to their flexibility, scalability, and cost-effectiveness. Key market players include Roostify, Ellie Mae, Blend, Streamloan, Maxwell, SimpleNexus, Salesforce, Cloudvirga, Blue Sage Solutions, RapidValue, WebMax, Preclose, Kofax, RealKey, and Newgen Software. North America holds the largest market share, followed by Europe and Asia Pacific. The increasing adoption of digital mortgage software in emerging economies is expected to drive growth in these regions. The digital mortgage software market is experiencing rapid growth as lenders seek to digitize their mortgage processes to improve efficiency, streamline the borrower experience, and meet evolving regulatory requirements. With a market value of over $1 billion in 2022, the industry is projected to reach $2.5 billion by 2030, growing at a CAGR of over 10%.

Global Mortgage Loan Service market size 2025 was XX Million. Mortgage Loan Service Industry compound annual growth rate (CAGR) will be XX% from 2025 till 2033.

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

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.