Mortgage Approvals in the United Kingdom increased to 64.17 Thousand in June from 63.29 Thousand in May of 2025. This dataset provides the latest reported value for - United Kingdom Mortgage Approvals - 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 May 2025, mortgage approvals for home purchases totaled ******, while remortgage approvals stood at ******* 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.

Mortgage Approvals in Spain increased to 42274 Units in May from 39176 Units in April of 2025. This dataset provides - Spain Mortgage Approvals- actual values, historical data, forecast, chart, statistics, economic calendar and news.

This data contains an unquantified element of refinancing of existing mortgages (e.g. involving the redemption of an existing mortgage and its replacement with a mortgage from a different lender). The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change.

The number of monthly mortgage approvals for home purchase in the United Kingdom (UK) peaked at nearly 108,000 approvals in November 2020, after falling to record low levels at the beginning of the coronavirus pandemic in the second quarter of the year. The spike was due to the easing of the first lockdown and a rise in the demand for housing. In 2022, the housing market started to cool, resulting in a falling number of mortgage approvals. In September 2024, there were 65,647 mortgage approvals. Remortgaging approvals followed a similar trend.

Following the COVID-19 pandemic in 2020, the number of residential mortgage approvals in the UK plummeted. As the measures eased, the market rebounded, peaking at ******* mortgage approvals in November 2020. In 2022 and 2023, mortgage lending declined again as a response to the rising mortgage interest rates and the cooling of the housing market. In May 2025, the number of mortgage approvals exceeded *******—up from about ****** in the same month a year ago. The increase indicated a rise in mortgage demand and an improvement in consumer sentiment.

Mortgage loan approvals for existing properties, new properties and new residential construction and existing residential properties.

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

This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Estimates (2 items: Dollars; Dwelling units ...), Type of mortgage loan approvals (3 items: Total; Conventional; National Housing Act ...), Type of lender (3 items: Total; Canada Mortgage and Housing Corporation; Approved lenders ...).

Mortgage lending information comes from the Federal Financial Institutions Examination Council's (FFIEC) Home Mortgage Disclosure Act (HMDA) data. Loan originations are the creation of a loan after bank approval. Loan origination rates are calculated from the number of loan applications that were either approved or denied—what is termed as decisioned applications. For all charts, the loan’s purpose can be selected via a dropdown list. Trends are summarized by all loan purposes and by Loans for home purchase, home improvement, or refinancing.

Source: From lending institutions and local authorities This data contains an unquantified element of refinancing of existing mortgages (e.g. involving the redemption of an existing mortgage and its replacement with a mortgage from a different lender). The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change.

This table contains data described by the following dimensions (Not all combinations are available): Geography (13 items: Canada; Prince Edward Island; Newfoundland and Labrador; Nova Scotia ...), Estimates (2 items: Dwelling units; Dollars ...), Type of residential category (2 items: New residential construction; Existing residential properties ...), Type of mortgage loan approvals (3 items: Total; mortgage loan approvals; Conventional; National Housing Act ...), Type of housing (3 items: Total; single-detached and multiples; Single-detached; Multiples ...).

Mortgage Approvals in Oman decreased to 1507 units in June from 1976 units in May of 2025. This dataset provides - Oman Mortgage Approvals- actual values, historical data, forecast, chart, statistics, economic calendar and news.

This data contains an unquantified element of refinancing of existing mortgages (e.g. involving the redemption of an existing mortgage and its replacement with a mortgage from a different lender). The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change.

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 value of mortgage approvals in the UK started to increase in the final quarter of 2023, reaching 22.7 billion British pounds in September 2024. In recent years, the market has undergone significant fluctuations, including a dramatic decline in May 2020 because of the COVID-19 pandemic and two notable drops in 2023, attributable to the aggressive mortgage interest rate hikes and worsening economic conditions.

Analysis of ‘Overall Loan Approvals by year’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/https-data-usmart-io-org-ae1d5c14-c392-4c3f-9705-537427eeb413-dataset-viewdiscovery-datasetguid-25ad382a-6039-4053-8544-b7d074cde78e on 11 January 2022.

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

Source: From lending institutions and local authorities
This data contains an unquantified element of refinancing of existing mortgages (e.g. involving the redemption of an existing mortgage and its replacement with a mortgage from a different lender).
The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change.

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

Overall Loan Approvals by year. Published by Department of Housing, Local Government, and Heritage. Available under the license Creative Commons Attribution Share-Alike 4.0 (CC-BY-SA-4.0).Source: From lending institutions and local authorities
This data contains an unquantified element of refinancing of existing mortgages (e.g. involving the redemption of an existing mortgage and its replacement with a mortgage from a different lender).
The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change.
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Mortgage Application in the United States decreased by 3.80 percent in the week ending July 25 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.

1) Data Introduction • The Home Loan Approval dataset determines eligibility for a home loan based on customer details provided by Dream Housing Finance company.

2) Data Utilization (1) Home Loan Approval data has characteristics that: • The dataset includes various socioeconomic variables such as gender, marital status, education, number of dependents, income, loan amount, and credit history. (2) Home Loan Approval data can be used to: • Financial Industry: It is useful for banks and financial institutions to explore variables that determine whether they are lending or not and to develop credit rating models. • Research: It helps to build a database by securing data to evaluate credit risk.