Mortgage Application in the United States increased by 0.20 percent in the week ending November 21 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.

The U.S. mortgage market has declined notably since 2020 and 2021, mostly due to the effect of higher borrowing costs on refinance mortgages. The value of refinancing mortgage originations amounted to 112 billion U.S. dollars in the first quarter of 2025, down from a peak of 851 billion U.S. dollars in the fourth quarter of 2020. The value of mortgage loans for the purchase of a property recorded milder fluctuations, with a value of 272 billion U.S. dollars in the first quarter of 2025. According to the forecast, mortgage lending is expected to slightly increase until the end of 2026. The cost of mortgage borrowing in the U.S. Mortgage interest rates in the U.S. rose dramatically in 2022, peaking in the final quarter of 2024. In 2020, a homebuyer could lock in a 30-year fixed interest rate of under three percent, whereas in 2024, the average rate for the same mortgage type exceeded 6.6 percent. This has led to a decline in homebuyer sentiment and an increasing share of the population pessimistic about buying a home in the current market. The effect of a slower housing market on property prices and rents According to the S&P/Case Shiller U.S. National Home Price Index, housing prices experienced a slight correction in early 2023, as property transactions declined. Nevertheless, the index continued to grow in the following months. On the other hand, residential rents have increased steadily since 2000.

Mortgage Originations in the United States increased to 512.15 Billion USD in the third quarter of 2025 from 458.28 Billion USD in the second quarter of 2025. This dataset includes a chart with historical data for the United States Mortgage Originations.

United States WAS: Market Volume Index data was reported at 209.000 15Mar1996=1000 in 23 Nov 2018. This records a decrease from the previous number of 292.200 15Mar1996=1000 for 16 Nov 2018. United States WAS: Market Volume Index data is updated weekly, averaging 432.150 15Mar1996=1000 from Jan 1990 (Median) to 23 Nov 2018, with 1508 observations. The data reached an all-time high of 1,739.400 15Mar1996=1000 in 13 Jun 2003 and a record low of 40.800 15Mar1996=1000 in 28 Dec 1990. United States WAS: Market Volume Index data remains active status in CEIC and is reported by Mortgage Bankers Association. The data is categorized under Global Database’s United States – Table US.KB008: Mortgage Loan Applications: Weekly Applications Survey.

Out of the ** million mortgage applications in the United States in 2021, roughly ** million resulted in mortgage originations. That included applications for home purchase, home improvement, refinancing, cash out refinancing, and other purposes. White applicants accounted for approximately ** million loan originations worth almost *** trillion U.S. dollars, while for Black and African American applicants, this figure stood at roughly ******* originations and *** billion U.S. dollars, respectively. The the number of mortgages originated to Asian applicants was slightly higher at *******.

United States WAS: Market Volume Index: Government: Purchase data was reported at 164.000 15Mar1996=1000 in 20 Jul 2018. This records a decrease from the previous number of 168.000 15Mar1996=1000 for 13 Jul 2018. United States WAS: Market Volume Index: Government: Purchase data is updated weekly, averaging 132.650 15Mar1996=1000 from Jan 1990 (Median) to 20 Jul 2018, with 1490 observations. The data reached an all-time high of 411.400 15Mar1996=1000 in 30 Apr 2010 and a record low of 25.600 15Mar1996=1000 in 28 Dec 1990. United States WAS: Market Volume Index: Government: Purchase data remains active status in CEIC and is reported by Mortgage Bankers Association. The data is categorized under Global Database’s USA – Table US.KA016: Weekly Applications Survey: Mortgage Loan Applications.

Distribution of purchase mortgages by lender rank for U.S. home buyers in 2024, showing loan volume across different lender size categories from top 10 to 1001+ ranked lenders

View quarterly updates and historical trends for US Mortgage Originations. from United States. Source: Mortgage Bankers Association. Track economic data w…

United States WAS: Market Volume Index: Conventional data was reported at 487.900 15Mar1996=1000 in 20 Jul 2018. This records an increase from the previous number of 484.100 15Mar1996=1000 for 13 Jul 2018. United States WAS: Market Volume Index: Conventional data is updated weekly, averaging 542.650 15Mar1996=1000 from Jan 1990 (Median) to 20 Jul 2018, with 1490 observations. The data reached an all-time high of 2,551.300 15Mar1996=1000 in 13 Jun 2003 and a record low of 49.200 15Mar1996=1000 in 28 Dec 1990. United States WAS: Market Volume Index: Conventional data remains active status in CEIC and is reported by Mortgage Bankers Association. The data is categorized under Global Database’s USA – Table US.KA016: Weekly Applications Survey: Mortgage Loan Applications.

According to Cognitive Market Research, the global Mortgage Loans Software market size will be USD XX million in 2025. It will expand at a compound annual growth rate (CAGR) of XX% from 2025 to 2031.

North America held the major market share for more than XX% of the global revenue with a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031.
Europe accounted for a market share of over XX% of the global revenue with a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031.
Asia Pacific held a market share of around XX% of the global revenue with a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031.
Latin America had a market share of more than XX% of the global revenue with a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031.
Middle East and Africa had a market share of around XX% of the global revenue and was estimated at a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031.

The cloud-based deployment category is the fastest-growing segment of the Mortgage Loans Software industry. Drivers

The rise of fintech lenders drives market growth

The mortgage industry has undergone a significant transformation with the emergence of FinTech lenders, who have introduced fully digital platforms to streamline the loan application and approval processes. These platforms allow borrowers to complete applications online, upload necessary documents, and receive decisions swiftly, often within minutes. This efficiency is primarily achieved through centralized underwriting systems and automation, reducing reliance on traditional, branch-based operations.

Studies indicate that FinTech lenders process mortgage applications approximately 20% faster than traditional lenders without compromising loan quality or increasing default risks [source]. This acceleration enhances borrower satisfaction and allows for more elastic responses to market demand fluctuations, thereby alleviating capacity constraints inherent in conventional mortgage lending. Furthermore, in areas with higher FinTech lending activity, borrowers are more likely to refinance, especially when it is in their financial interest to do so. This suggests that technological innovation has improved the efficiency of financial intermediation in the U.S. mortgage market.

The integration of technology in mortgage lending has also facilitated better access to credit, as FinTech platforms can efficiently handle increased application volumes and adjust supply more elastically in response to exogenous mortgage demand shocks. This adaptability is particularly beneficial during periods of fluctuating market conditions, ensuring that borrower needs are met promptly.

In conclusion, the rise of FinTech lenders has revolutionized the mortgage landscape by leveraging technology to enhance efficiency, responsiveness, and borrower satisfaction, marking a pivotal shift in how mortgage lending operates in the digital age.

https://www.fdic.gov/media/168606

https://files.consumerfinance.gov/f/documents/cfpb_jorring-integrated-intermediation-and-fintech-market-power.pdf

Increasing demand for automation and advanced analytics is driving market growth of Mortgage Loans Software

The mortgage industry is rapidly adopting automation and advanced analytics to optimize lending operations and enhance decision-making. AI-driven automation enables lenders to streamline critical functions such as credit evaluation, fraud detection, and compliance monitoring, significantly reducing manual workload and processing times. By automating document verification, loan underwriting, and risk assessment, financial institutions can process mortgage applications with greater speed and accuracy, improving overall efficiency

https://www.alldigitech.com/wp-content/uploads/2024/11/Alldigi_The-Future-of-AI-in-the-Mortgage-Industry-Whitepaper.pdf

Machine learning algorithms further enhance accuracy in risk assessments and borrower profiling, leading to more precise loan approvals. By analyzing vast datasets, AI models can predict creditworthiness more effectively than traditional scoring methods, allowing lenders to offer better terms to low-risk borrowers while mitigating potential defaults. Additionally, automated fraud detection tools can flag suspicious activities in real time, preventing identity theft an...

Fixed 30-year mortgage rates in the United States averaged 6.40 percent in the week ending November 21 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 total monthly number of mortgage approvals for the purpose of a house sale in the UK plummeted in 2020 during the COVID-19 pandemic, followed by a spike in the second half of the year. In 2021, interest rates started to rise, resulting in a decline in the volume of mortgage approvals. In October 2025, mortgage approvals for home purchases totaled ******, while remortgage approvals stood at around ******. Being approved for a mortgage is one of the first steps in purchasing a home, which makes it an early indicator of the development of transaction volumes. However, a mortgage approval does not necessarily mean that a sale is going to take place, as home buyers need to undergo several other steps to complete the sale: conveyancing, or the process of transferring the legal title of the property from the seller to the buyer, a property survey, contract exchange, and closing.

United States WAS: Market Volume Index: FRM data was reported at 379.400 15Mar1996=1000 in 20 Jul 2018. This records a decrease from the previous number of 380.300 15Mar1996=1000 for 13 Jul 2018. United States WAS: Market Volume Index: FRM data is updated weekly, averaging 414.850 15Mar1996=1000 from Jan 1990 (Median) to 20 Jul 2018, with 1490 observations. The data reached an all-time high of 1,562.500 15Mar1996=1000 in 14 Mar 2003 and a record low of 40.800 15Mar1996=1000 in 28 Dec 1990. United States WAS: Market Volume Index: FRM data remains active status in CEIC and is reported by Mortgage Bankers Association. The data is categorized under Global Database’s USA – Table US.KA016: Weekly Applications Survey: Mortgage Loan Applications.

Lender market share concentration for U.S. home buyers in 2024, showing market share of the top 50 mortgage lenders ranked by loan volume, with remaining lenders accounting for the rest of the market

Average Mortgage Size in the United States increased to 381.40 Thousand USD in October from 379.11 Thousand USD in September of 2025. This dataset includes a chart with historical data for the United States Average Mortgage Size.

Mortgage market statistics from 100+ million applications covering rates, fees, loan types, and lender rankings by Homebuyer.com.

This table contains 80 series, with data starting from 1982 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Mortgages (4 items: Total, mortgage loans outstanding; Mortgages in Canada outstanding; Mortgage loans outside Canada outstanding; Allowance for credit losses); Increases and decreases (15 items: Total, increases and decreases; Gross increase; Cash disbursement of principal; Purchases of mortgages from; ...); Type of mortgage (7 items: Total, mortgages; Total, residential mortgages; Residential mortgages, insured; Residential mortgages, uninsured; ...).

Mortgage Underwriting AI Market Outlook

According to our latest research, the global mortgage underwriting AI market size reached USD 1.42 billion in 2024, reflecting the rapid adoption of artificial intelligence within the financial sector. The market is projected to grow at a robust CAGR of 18.6% from 2025 to 2033, reaching a forecasted value of USD 7.26 billion by 2033. This remarkable growth is primarily driven by the increasing demand for automation, accuracy, and efficiency in mortgage underwriting processes, as financial institutions strive to streamline operations, minimize risks, and enhance customer experiences in a competitive lending environment.

The primary growth factor fueling the expansion of the mortgage underwriting AI market is the urgent need for operational efficiency and cost reduction across the mortgage industry. Traditional underwriting processes are often labor-intensive, time-consuming, and prone to human error, resulting in delayed loan approvals and increased operational costs. By integrating AI-driven solutions, lenders can automate data collection, document verification, and risk analysis, significantly reducing turnaround times and manual workloads. The ability of AI to process vast volumes of data with high accuracy not only expedites decision-making but also enhances the overall reliability of underwriting outcomes, making it an indispensable tool for modern financial institutions. Furthermore, the scalability and adaptability of AI platforms enable mortgage providers to handle fluctuating application volumes without compromising on quality or compliance, further cementing AIÂ’s pivotal role in the sector.

Another significant driver is the evolving regulatory landscape and the heightened focus on compliance within the mortgage industry. Regulatory bodies worldwide are imposing stricter guidelines to ensure transparency, fair lending practices, and risk mitigation. Mortgage underwriting AI solutions are increasingly being leveraged to automate compliance checks, monitor regulatory changes, and generate audit trails, thereby reducing the risk of non-compliance and associated penalties. The integration of advanced analytics and machine learning algorithms enables lenders to identify anomalies, flag suspicious activities, and ensure adherence to both internal policies and external regulations. This proactive approach to compliance not only safeguards institutions from legal repercussions but also fosters trust among borrowers and regulatory authorities, further accelerating the adoption of AI-powered underwriting solutions.

The surge in digital transformation initiatives across the financial services sector also plays a crucial role in propelling the mortgage underwriting AI market forward. As consumer preferences shift towards digital-first experiences, lenders are compelled to modernize their operations and deliver seamless, personalized services. AI-powered underwriting platforms facilitate the digitization of the mortgage process, enabling real-time application processing, instant credit assessments, and tailored loan recommendations. The integration of AI with other emerging technologies, such as blockchain and robotic process automation (RPA), further enhances the efficiency, security, and transparency of mortgage transactions. This convergence of digital technologies not only improves customer satisfaction but also positions lenders to capitalize on new market opportunities and differentiate themselves in an increasingly crowded marketplace.

Regionally, North America continues to dominate the mortgage underwriting AI market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The regionÂ’s leadership can be attributed to the presence of advanced financial infrastructure, early adoption of AI technologies, and a robust ecosystem of fintech innovators. However, the Asia Pacific region is expected to witness the fastest growth during the forecast period, driven by rapid urbanization, expanding middle-class populations, and increasing investments in digital banking solutions. Meanwhile, Europe remains a key market, supported by stringent regulatory frameworks and a strong focus on innovation in financial services. Latin America and the Middle East & Africa are also emerging as promising markets, albeit at a relatively nascent stage, as financial institutions in these regions begin to embrace AI-driven transformation.

In the realm of mortgage underwriting, the integrati

Mortgage Document Classification AI Market Outlook

According to our latest research, the global mortgage document classification AI market size reached USD 1.42 billion in 2024, demonstrating robust momentum driven by the accelerated adoption of automation in mortgage processing. The market is projected to expand at a CAGR of 23.8% from 2025 to 2033, reaching an estimated USD 11.14 billion by 2033. This remarkable growth trajectory is fueled by the increasing demand for intelligent document processing solutions that can streamline loan origination, improve compliance, and reduce operational costs for financial institutions worldwide.

One of the primary growth factors for the mortgage document classification AI market is the surging volume and complexity of mortgage-related documents. As regulatory frameworks become more stringent and the mortgage industry faces mounting pressure to expedite loan processing, financial institutions are turning to advanced AI-powered classification tools. These solutions leverage machine learning and natural language processing to automatically categorize, extract, and validate critical information from a diverse array of documents such as loan applications, income statements, and compliance disclosures. By reducing manual intervention, these AI systems not only accelerate document processing but also minimize the risk of human error, thereby enhancing operational efficiency and customer satisfaction. The increasing digitalization of mortgage processes, coupled with the proliferation of electronic documentation, further amplifies the need for sophisticated classification algorithms that can adapt to evolving document formats and regulatory requirements.

Another significant driver propelling the growth of the mortgage document classification AI market is the imperative for robust risk management and compliance. Financial institutions are under constant scrutiny to adhere to anti-money laundering (AML), know-your-customer (KYC), and other regulatory mandates. AI-powered document classification systems play a pivotal role in automating compliance checks, flagging inconsistencies, and ensuring that all necessary documentation is accurately categorized and archived. By integrating these AI solutions into their workflows, banks and mortgage lenders can achieve higher levels of transparency, auditability, and regulatory adherence. This not only mitigates the risk of costly compliance violations but also streamlines internal audits and reporting processes, thereby freeing up valuable resources for core business activities. The growing emphasis on governance, risk, and compliance (GRC) across the financial sector is expected to further accelerate the adoption of AI-driven document classification technologies in the coming years.

The rapid advancements in AI and machine learning technologies are also catalyzing innovation within the mortgage document classification AI market. Improved algorithms, enhanced data processing capabilities, and the integration of cloud-based platforms are enabling real-time document classification at scale. These technological breakthroughs are making it feasible for even mid-sized and smaller financial institutions to harness the benefits of AI-driven automation without incurring prohibitive infrastructure costs. Furthermore, the emergence of explainable AI (XAI) frameworks is helping to address concerns regarding transparency and accountability in automated decision-making, thereby fostering greater trust among regulators and end-users alike. As AI continues to evolve, the market is likely to witness the introduction of more sophisticated solutions capable of handling multilingual documents, unstructured data, and complex workflows, thereby unlocking new opportunities for growth and value creation across the mortgage ecosystem.

From a regional perspective, North America currently dominates the mortgage document classification AI market, accounting for the largest share owing to the presence of leading technology providers, a mature mortgage industry, and early adoption of digital transformation initiatives. The region’s robust regulatory environment and high volume of mortgage transactions have created fertile ground for the deployment of advanced AI solutions. Meanwhile, Europe is witnessing significant growth driven by stringent data privacy regulations and the increasing need for compliance automation. The Asia Pacific region is poised for the fastest growth over the forecast period, fueled by rapid urbanization, expanding financial se

Distribution of mortgage loan terms in 2024, showing percentage of borrowers choosing each term length.