Bank Customer Dataset for Personal Loan Prediction This dataset contains demographic, financial, and behavioral data of 5,000 bank customers collected during a marketing campaign aimed at offering personal loans. The primary objective is to predict whether a customer accepted the personal loan offer (personal_loan), making this a supervised binary classification problem.

The dataset includes 14 features such as age, income, credit card usage, education level, mortgage value, and account ownership information. It can be used for machine learning tasks such as classification modeling, feature selection, customer segmentation, and marketing analytics.

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.

Dataset contains the percent of denied mortgages based on the type of dwelling the applicant is applying for 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.

Dataset from Housing & Development Board. For more information, visit https://data.gov.sg/datasets/d_fbb057402a1d4a953a9b46babbdbf1fc/view

The global mortgage loan service market is experiencing robust growth, driven by factors such as increasing urbanization, rising disposable incomes, and favorable government policies supporting homeownership. The market size in 2025 is estimated at $2 trillion, exhibiting a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033. This positive trajectory is fueled by the expansion of the middle class globally, particularly in emerging economies, leading to a greater demand for housing finance. The market is segmented by loan type (residential and commercial estate) and application (individual and enterprise). The residential segment currently dominates, but the commercial estate segment is witnessing significant growth, propelled by investments in real estate development and infrastructure projects. Technological advancements, such as the rise of fintech and online mortgage platforms, are streamlining the loan application and approval processes, enhancing customer experience and driving market efficiency. However, fluctuating interest rates, stringent regulatory compliance requirements, and economic downturns represent key restraints. The competitive landscape is highly fragmented, with a mix of large established banks (Chase, PNC Bank, Truist) and specialized mortgage lenders (Rocket Mortgage, United Shore Financial Services, LoanDepot) vying for market share. The continued growth of the mortgage loan service market hinges on macroeconomic stability, consistent consumer confidence, and innovative solutions addressing evolving borrower needs. Increased adoption of digital technologies, including AI-powered credit scoring and personalized loan offerings, will further shape the industry. Geographic expansion into underserved markets and the development of sustainable mortgage solutions are also key factors influencing future market dynamics. Regional variations exist, with North America and Europe currently holding the largest market share due to their well-established financial infrastructure and higher homeownership rates. However, rapid growth is anticipated in Asia-Pacific, driven by burgeoning economies and increased urbanization in countries like India and China. Successful players will need to adapt to changing regulatory landscapes, adopt robust risk management strategies, and leverage technological advancements to maintain a competitive edge.

Dataset contains home mortgage applications denied in LA City, LA County, and California, disaggregated by race. 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.

The US mortgage lending market, a significant component of the broader financial landscape, is experiencing robust growth, driven by several key factors. Low interest rates in recent years stimulated demand, particularly for fixed-rate mortgages, fueling a surge in refinancing activity and new home purchases. The increasing homeownership aspirations among millennials and Gen Z, coupled with a persistent housing shortage in many areas, further contribute to market expansion. While home equity lines of credit (HELOCs) represent a smaller segment, their usage is expected to rise as homeowners tap into their equity for renovations or other investments. Competition in the sector is intense, with established commercial banks like Bank of America and Chase, alongside regional players such as PNC Bank and credit unions like PenFed, vying for market share. The shift towards online mortgage applications and processing offers convenience and efficiency, increasing accessibility and potentially driving down costs. However, challenges remain. Rising interest rates, inflation, and potential economic slowdown could temper future growth, impacting both affordability and demand. Moreover, stringent lending regulations and increased scrutiny of borrowers' creditworthiness may restrict lending practices. The market will likely see further consolidation among lenders, particularly smaller institutions. Despite these headwinds, the long-term outlook remains positive, projecting a continuation of moderate growth, particularly in segments catering to first-time homebuyers and those pursuing home improvements through HELOCs. Technological advancements and improved data analytics will play pivotal roles in shaping the competitive landscape and enhancing customer experience. The segmentation within the US mortgage lending market reflects diverse borrower needs and lender strategies. Fixed-rate mortgages remain the dominant product, providing predictable monthly payments. However, the rise of adjustable-rate mortgages and HELOCs provides borrowers with alternative financing options. The distribution channels are also varied, with both online and offline applications prevalent. The geographical distribution is concentrated, with the United States driving a significant portion of the overall market. Canada and Mexico contribute substantially to the North American market, while other regions show more moderate growth. Future market performance will depend critically on macroeconomic conditions, regulatory changes, and innovative financial products that cater to evolving consumer preferences. The increasing reliance on technology for lending, underwriting, and customer service will further reshape this dynamic and competitive market. This comprehensive report offers an in-depth analysis of the US mortgage lending market, covering the period from 2019 to 2033. With a base year of 2025 and an estimated year of 2025, this report provides a detailed forecast (2025-2033) and analysis of the historical period (2019-2024). We delve into key market segments, trends, and growth drivers, providing valuable insights for stakeholders across the industry. This report is essential for investors, lenders, financial institutions, and anyone seeking to understand the dynamics of this multi-billion-dollar market. Keywords: US Mortgage Lending, Mortgage Market Trends, Home Equity Loans, Fixed Rate Mortgages, Mortgage Industry Analysis, Mortgage Rates, Real Estate Finance, Mortgage Lending Market Size, Commercial Banks, Credit Unions, Online Mortgages, Mortgage Regulations, Mortgage Acquisitions 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.

This dataset contains a wealth of information from 52,000 loan applications, offering detailed insights into the factors that influence loan approval decisions. Collected from financial institutions, this data is highly valuable for credit risk analysis, financial modeling, and predictive analytics. The dataset is particularly useful for anyone interested in applying machine learning techniques to real-world financial decision-making scenarios.

Overview: This dataset provides information about various applicants and the loans they applied for, including their demographic details, income, loan terms, and approval status. By analyzing this data, one can gain an understanding of which factors are most critical for determining the likelihood of loan approval. The dataset can also help in evaluating credit risk and building robust credit scoring systems.

Dataset Columns: Applicant_ID: Unique identifier for each loan application. Gender: Gender of the applicant (Male/Female). Age: Age of the applicant. Marital_Status: Marital status of the applicant (Single/Married). Dependents: Number of dependents the applicant has. Education: Education level of the applicant (Graduate/Not Graduate). Employment_Status: Employment status of the applicant (Employed, Self-Employed, Unemployed). Occupation_Type: Type of occupation, which provides insights into the nature of the applicant’s job (Salaried, Business, Others). Residential_Status: Type of residence (Owned, Rented, Mortgage). City/Town: The city or town where the applicant resides. Annual_Income: The total annual income of the applicant, a key factor in loan eligibility. Monthly_Expenses: The monthly expenses of the applicant, indicating their financial obligations. Credit_Score: The applicant's credit score, reflecting their creditworthiness. Existing_Loans: Number of existing loans the applicant is servicing. Total_Existing_Loan_Amount: The total amount of all existing loans the applicant has. Outstanding_Debt: The remaining amount of debt yet to be paid by the applicant. Loan_History: The applicant’s previous loan history (Good/Bad), indicating their repayment reliability. Loan_Amount_Requested: The loan amount the applicant has applied for. Loan_Term: The term of the loan in months. Loan_Purpose: The purpose of the loan (e.g., Home, Car, Education, Personal, Business). Interest_Rate: The interest rate applied to the loan. Loan_Type: The type of loan (Secured/Unsecured). Co-Applicant: Indicates if there is a co-applicant for the loan (Yes/No). Bank_Account_History: Applicant’s banking history, showing past transactions and reliability. Transaction_Frequency: The frequency of financial transactions in the applicant’s bank account (Low/Medium/High). Default_Risk: The risk level of the applicant defaulting on the loan (Low/Medium/High). Loan_Approval_Status: Final decision on the loan application (Approved/Rejected).

The global mortgage verification service market, currently valued at approximately $3.4 billion (2025 estimate based on provided 2025 market size of 3397 million), is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 6.5% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing adoption of digital lending platforms and the growing need for efficient and secure verification processes are significantly contributing to market growth. Furthermore, stringent regulatory compliance requirements and a rising demand for faster loan processing times are compelling lenders to integrate advanced mortgage verification solutions. The market is segmented by application (Retail Lending, Residential Mortgage, Trade Finance, Others) and verification type (Income, Employment, Asset, Credit, Others). Residential mortgage applications currently dominate the market due to the substantial volume of mortgages processed globally. However, growth is anticipated across all segments, with trade finance and other applications showing promising potential as digitalization expands into these sectors. The competitive landscape is characterized by a mix of established players and emerging fintech companies. Key players like Finicity, Truv, and CoreLogic are leveraging their existing infrastructure and expertise to enhance their offerings and cater to the evolving needs of lenders. Meanwhile, innovative fintechs are introducing new technologies, such as AI-powered verification systems, to improve accuracy and efficiency. Geographical distribution shows a concentration of market activity in North America, driven by established financial markets and early adoption of digital technologies. However, growth is also expected in other regions, particularly in Asia Pacific and Europe, as digital financial infrastructure develops and regulatory frameworks mature. This expansion will be influenced by varying economic conditions and regulatory changes across different regions, with emerging markets offering significant untapped potential.

The Puerto Rico Home Mortgage Finance Market Is Segmented By Application (Home Purchase, Refinance, Home Improvement, And Other Applications), By Provider (Banks, Housing Finance Companies, And Real Estate Agents), And By Interest Rate (Fixed Rate Mortgage Loan And Adjustable Rate Mortgage Loan). The Report Offers Market Size And Forecasts For The Puerto Rico Home Mortgage Finance Market In Value (USD) For All The Above Segments.

The Europe Home Mortgage Finance Market is experiencing robust growth, projected to maintain a Compound Annual Growth Rate (CAGR) exceeding 6% from 2025 to 2033. While the exact market size in 2025 is not provided, considering a typical market size for a major European region and applying a conservative estimation based on available data regarding similar markets and growth rates, a reasonable estimate for the 2025 market size would be in the range of €3 trillion. This signifies a substantial and expanding market fueled by several key drivers. Low interest rates in the past, though potentially fluctuating in the coming years, have historically stimulated borrowing, and government incentives for first-time homebuyers continue to play a significant role. Furthermore, increasing urbanization and a growing population, particularly in key European economic hubs, contribute to the demand for mortgages. However, the market faces challenges. Economic uncertainty and potential interest rate hikes could temper growth, as could tightening lending regulations aimed at managing risk within the financial sector. The market is segmented by various loan types (fixed-rate, adjustable-rate, etc.), loan-to-value ratios, and borrower demographics. Key players include established international banks like Bank of America, Barclays, BNP Paribas, and Deutsche Bank, alongside significant regional players and increasingly competitive fintech lenders like Rocket Mortgage and United Shore Financial. The market's future will depend on the interplay of economic conditions, regulatory changes, and the innovative approaches adopted by lenders to serve an evolving customer base. The competitive landscape is highly dynamic, with both established financial institutions and innovative fintech companies vying for market share. This competitive intensity is driving innovation in mortgage products and services, such as digital mortgage applications and personalized lending solutions. Technological advancements, including AI-powered credit scoring and improved fraud detection systems, also contribute to market growth. However, potential future economic downturns and evolving regulatory landscapes present considerable risks. The continued growth will depend on effective risk management, adapting to changing consumer preferences, and the ability to navigate an increasingly complex regulatory environment. The forecast period of 2025-2033 presents both significant opportunities and substantial challenges for players in the Europe Home Mortgage Finance market. Notable trends are: Increased Number of Salaried Individuals is Driving the Market Growth.

This dataset contains detailed synthetic records of loan applications, including applicant demographics, financial profiles, loan details, automated risk assessments, and approval or denial outcomes. It is ideal for developing and evaluating AI models for credit decisioning, risk analysis, and fair lending compliance, with fields supporting bias detection and explainability. The data structure enables robust analytics for both operational and regulatory use cases.

In the fiscal year 2023, applications for the Flat 35 Purchase Program of the Japan Housing Finance Agency (JHF) amounted to around 36.4 thousand, representing a decrease from the previous year. The JHF supports the provision of long-term fixed-rate Flat 35 housing loans, either by securitizing loans granted by private financial institutions under the Purchase Program or by insuring loans securitized by private lenders through its Guarantee Program.

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 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%.

Belgium Mortgage Credits: Applications: ow Other Financial Purpose data was reported at 183.000 EUR mn in Feb 2025. This records a decrease from the previous number of 219.000 EUR mn for Jan 2025. Belgium Mortgage Credits: Applications: ow Other Financial Purpose data is updated monthly, averaging 120.500 EUR mn from Jan 1995 (Median) to Feb 2025, with 362 observations. The data reached an all-time high of 453.000 EUR mn in Mar 1999 and a record low of 22.000 EUR mn in Feb 1995. Belgium Mortgage Credits: Applications: ow Other Financial Purpose data remains active status in CEIC and is reported by National Bank of Belgium. The data is categorized under Global Database’s Belgium – Table BE.KB010: Mortgage Credits.

Belgium Mortgage Credits: Number of Applications: ow Other Financial Purpose data was reported at 1.500 Unit th in Feb 2025. This records a decrease from the previous number of 1.700 Unit th for Jan 2025. Belgium Mortgage Credits: Number of Applications: ow Other Financial Purpose data is updated monthly, averaging 1.500 Unit th from Jan 1995 (Median) to Feb 2025, with 362 observations. The data reached an all-time high of 6.700 Unit th in Mar 1999 and a record low of 0.500 Unit th in Jan 1995. Belgium Mortgage Credits: Number of Applications: ow Other Financial Purpose data remains active status in CEIC and is reported by National Bank of Belgium. The data is categorized under Global Database’s Belgium – Table BE.KB010: Mortgage Credits.

The Home Mortgage Disclosure Act (HMDA), enacted by Congress in 1975, is implemented by the Federal Reserve Board's Regulation C (12 CFR Part 203). HMDA was made permanent in February 1988, and was expanded in August 1989 to require additional data to be reported about applications received and about applicant and borrower characteristics. HMDA makes available to the public information that helps to show whether financial institutions are serving the housing credit needs of their neighborhoods and communities. It also helps government officials make public sector investments and indicates to private investors the neighborhoods where their efforts are needed. In addition, HMDA data help identify possible discriminatory lending patterns and assist regulatory agencies in enforcing compliance with anti-discrimination statutes.

The LAR & TS data are collected by a financial institution as a result of applications for, and originations and purchases of, home-purchase loans (including refinancings) and home-improvement loans for each calendar year. The TS data contain specific information about the reporting institution, including respondent identification number used in the report, their supervisory agency code, respondent's name and address. The primary categories of each LAR record are data about the application and loan, action taken, property location, applicant information, and whether the loan was sold.

Dataset contains the reason for home mortgage applications denials in LA City disaggregated by race. 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.