The loan-to-value ratios in Kansas, Louisiana and Kentucky amounted to ** percent in 2019, which means that on average the value of mortgages constituted ** percent of the value of the residential property in those states. The LTV ratio is calculated by dividing the mortgage amount by the purchase price of the home. The trend seems to be that southern and midwestern states have higher ratios than those in the Northeast or West of the country, which is in line with regional home prices. Areas with higher home prices tend to have lower LTV ratios.

What is the LTV ratio used for? Lenders use this ratio to determine how risky a loan is, because a higher ratio means that the loan is riskier to the lender. Generally, a good LTV ratio for a home loan is ** percent or lower, which means that the loan is worth ** percent of less of the value of the home. Loans are granted if the ratio is higher than that, but only if the loan applicant takes out mortgage guaranty insurance, also known as private mortgage insurance, to cover the lender.

Graph and download economic data for Large Bank Consumer Mortgage Originations: Original Loan-to-Value (LTV): 50th Percentile (RCMFLOLTVPCT50) from Q3 2012 to Q1 2025 about FR Y-14M, origination, large, percentile, mortgage, loans, consumer, banks, depository institutions, and USA.

This statistic presents the average loan to value ratio in the United States from 2011 to 2016. In 2016, the average U.S. LTV ratio amounted to **** percent which means that on average the value of mortgages constituted **** percent of the value of the residential property.

The median combined loan to value (CLTV) ratio in the United States varied greatly among different mortgage types between 2019 and 2023. The CLTV ratio represents the cumulative value of debt on a property relative to its value. A high ratio means a buyer contributes a smaller down payment as the mortgage provider hands out a relatively large loan. A lower CLTV means a smaller loan and less risk for mortgage providers but requires larger contributions from consumers. In the third quarter of 2023, HELOC loans had a CLTV of *****.

Graph and download economic data for Large Bank Consumer Mortgage Originations: Average Interest Rate at Origination by LTV: 30-Year Fixed Rate Mortgage: <=65 Loan-to-Value (RCMFLRIGIRAPCTF30LTVLTE65) from Q3 2012 to Q1 2025 about FR Y-14M, origination, 30-year, large, fixed, mortgage, average, loans, consumer, interest rate, banks, interest, depository institutions, rate, and USA.

In 2023, the customer lifetime value (LTV) of the food and beverage vertical worldwide stood at just over *** U.S. dollars. The health and wellness industry came in second place.

The statistic shows the typical value generated from a software customer over the lifetime of their contract, by delivery type, according to a 2012 survey of conducted by the Boston Consulting Group. As of 2012, the average value generated from a Software as a Service customer was ** thousand U.S. dollars per year, compared with ** thousand U.S. dollars per year from an on-premises software customer.

The Public Use Database (PUDB) is released annually to meet FHFA’s requirement under 12 U.S.C. 4543 and 4546(d) to publicly disclose data about the Enterprises’ single-family and multifamily mortgage acquisitions. The datasets supply mortgage lenders, planners, researchers, policymakers, and housing advocates with information concerning the flow of mortgage credit in America’s neighborhoods. Beginning with data for mortgages acquired in 2018, FHFA has ordered that the PUDB be expanded to include additional data that is the same as the data definitions used by the regulations implementing the Home Mortgage Disclosure Act, as required by 12 U.S.C. 4543(a)(2) and 4546(d)(1).The PUDB single-family datasets include loan-level records that include data elements on the income, race, and sex of each borrower as well as the census tract location of the property, loan-to-value (LTV) ratio, age of mortgage note, and affordability of the mortgage. New for 2018 are the inclusion of the borrower’s debt-to-income (DTI) ratio and detailed LTV ratio data at the census tract level. The PUDB multifamily property-level datasets include information on the unpaid principal balance and type of seller/servicer from which the Enterprise acquired the mortgage. New for 2018 is the inclusion of property size data at the census tract level. The multifamily unit-class files also include information on the number and affordability of the units in the property. Both the single-family and multifamily datasets include indicators of whether the purchases are from “underserved” census tracts, as defined in terms of median income and minority percentage of population.Prior to 2010 the single-family PUDB consisted of three files: Census Tract, National A, and National B files. With the 2010 PUDB a fourth file, National C, was added to provide information on high-cost mortgages acquired by the Enterprises. The single-family Census Tract file includes information on the location of the property based on the 2010 Census for acquisition years 2012 through 2021, and the 2020 Census beginning with the 2022 acquisition year. The National files contain other information but lack detailed geographic information in order to protect Enterprise proprietary data. The multifamily datasets also consist of a Census Tract file, and a National file without detailed geographic information.Several dashboards are available to analyze the data:Enterprise Multifamily Public Use Database DashboardThe Enterprise Multifamily Public Use Database (PUDB) Dashboard provides users an interactive way to generate and visualize Enterprise PUDB data of multifamily mortgage acquisitions by Fannie Mae and Freddie Mac. It shows characteristics about multifamily loans, properties and units at the national level, and characteristics about multifamily loans and properties at the state level. It includes key statistics, time series charts, and state maps of multifamily housing characteristics such as median loan amount, number of properties, average number of units per property, and unit affordability. The underlying aggregate statistics presented in the dashboard come from three multifamily data files in the Enterprise PUDB, updated annually since 2008, including two property-level datasets and a data file on the size and affordability of individual units.Enterprise Multifamily Public Use DashboardPress Release - FHFA Releases Data Visualization Dashboard for Enterprises’ Multifamily Mortgage AcquisitionsMortgage Loan and Natural Disaster DashboardFHFA published an interactive Mortgage Loan and Natural Disaster Dashboard that combines FHFA’s PUDB reports on single-family and multifamily acquisitions for the regulated entities, FEMA’s National Risk Index (NRI), and FHFA’s Duty to Serve 2023 High-Needs rural areas. Desired geographies can be exported to .pdf and Excel from the Public Use Database and National Risk Index Dashboard.Mortgage Loan and Natural Disaster DashboardMortgage Loan and Natural Disaster Dashboard FAQs

E-commerce apps in Japan achieved on average a lifetime value of almost ***** U.S. dollars on day * in the first quarter of 2024. The value of a user would continue to grow within the first month, reaching almost ** dollars at the end of their starting month.

In a 2019 analysis, Riverside, California was the most at risk of a housing downturn in a recession out of the ** largest metro areas in the United States. The Californian metro area received an overall score of **** percent, which was compiled after factors such as home price volatility and average home loan-to-value ratio were examined.