What is Mortgage Data? Examples, Providers & Datasets to Buy
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- Guide
- FAQ
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- Guide
- FAQ
What is Mortgage Data?
Mortgage data refers to information related to loans secured by real estate property. Mortgage databases help assess the risk associated with granting a mortgage and to determine the terms and conditions of the loan.
What Are Examples of Mortgage Data?
Examples of mortgage data include datasets offering insights into home loan markets and borrower behavior. Key examples include:
- Loan Information: Data on loan amounts, interest rates, and terms.
- Borrower Demographics: Age, income, credit scores, and geographic location of borrowers.
- Property Details: Information on properties, including value, location, and type.
- Payment Histories: Records of on-time payments, defaults, or late payments.
- Market Trends: Data on mortgage origination volumes, refinancing trends, and regional activity.
Best Mortgage Databases, Datasets & API
The best mortgage datasets provide comprehensive insights into borrower profiles, loan performance, and market dynamics. This curated list features the top datasets and APIs, selected for accuracy, quality, and trusted providers where you can buy mortgage data.
Mortgage Data | Homeownership Data | Financial Services | Lender Data
Alesco Home Ownership Mortgage Data - 50+ Million US Homeowners - Available for Licensing!
US National Deed & Mortgage Data | 500M+ Records | Deed & Mortgage Characteristics | 15 Years of Property Transaction Data
Factori US Home Ownership Mortgage Data | Property Data | Real-Estate Data - 340+ Million US Homeowners
Mortgage Data, Property Data, Title Data, Ownership Data | Over 150 MM Records and 200 Attributes
Mortgage Data | USA Coverage | 74% Right Party Contact Rate | BatchData
Mortgage Advertisement data for independent mortgage lenders
Mortgage Rates (Front Line Prices) - Hourly Historical Prices (6am - 10pm EST)
Consumer Marketing Data | Versatile B2C Contact Data | API & Dataset | US Household, Housing, Mortgage Data
US National NMLS Loan Originator Mortgage Data | Nationwide Mortgage Licensing System | NMLS IDs | LO Names & Company Names
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Top Mortgage Data Providers & Companies
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Immobiliare.it Insights
Immobiliare.it Insights is a proptech dedicated to the analysis and processing of Italian and foreign real estate market data. We offer highly detailed real estate analysis with demand, supply and transaction data, energy performance indicators, location intelligence and much more.+1BILDemand data+2MReal Transactions+25MEnergy Datapoints -
Think Data Group
CoverageUSAAt Think Data Group, we’re experts in bringing data opportunities to life on both the buy side and sell side. We have extensive experience working with new data sources and launching products that deliver durable revenue streams.CCPAcompliantScaleExtensivePricingFlexible pricing models -
BatchService
CoverageUSADeepen the insights your platform or application offers by harnessing unparalleled property data and accurate owner contact information from a single API.74%Right Party Contact Rate600+Data Points900%Efficiency Improvement -
PromotedAlesco Data
CoverageUSAVWe've collaborated with Alesco for several months now, and I have nothing but praise for their services. Their team is absolutely outstanding. Our requirements for data were quite stringent, yet they not only met but exceeded our expectations. If you're in need of a reliable provider who delivers exceptional service when it matters most, don't hesitate to choose them.
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Versium
CoverageUSACUsing Versium REACH has allowed us to easily and cost-effectively activate our CRM and ICP data. Versium REACH allows us to activate our data over our preferred media channels giving us the ability to compound frequency with our audiences.
Popular Use Cases for Mortgage Data
Mortgage data is used by lenders and banks. This data serves as an additional record in approving a loan application. Lenders benefit from this data to ensure the transparency and credibility of a borrower to pay. Mortgage data also serves as a strong decision indicator for the lending institution to avoid unreliable borrowers. Another benefit of using this data is to target a better audience based on their previous mortgage loan. Mortgage data is valuable to lending institutions for risk management, as it allows them to conduct KYC procedures so that they don’t grant loans to borrowers who won’t repay them.
Main Attributes of Mortgage Data
Below, we outline the most popular attributes associated with this type of data—features that data buyers are actively seeking to meet their needs.
| Attribute | Type | Description | Action |
|---|---|---|---|
| String | The first name of a contact. | View 24 datasets | |
| String | The last name (surname) of a contact. | View 24 datasets | |
| String | The abbreviation of a state name. | View 22 datasets | |
| String | The full name of a contact (first, middle, and last name). | View 17 datasets | |
| String | The gender of a contact. | View 16 datasets | |
| String | The name of a state. | View 15 datasets |
How is Mortgage Data Collected?
Mortgage data is collected from various credible sources. These sources include social media platforms, online news sites, online publications, lending agencies, the government, and any related public records. In the form of a list or charts, these sources are gathered and analyzed to create mortgage datasets which undergo cleansing and filtering to eliminate duplications and incomplete data. Then, data is organized and compiled for data storage.
What Are the Typical Attributes of Mortgage Data?
Here are some typical attributes of mortgage data:
| Attribute | Description |
|---|---|
| Loan Amount | The principal amount borrowed for a home loan. |
| Interest Rate | The percentage charged on the principal amount annually. |
| Borrower Demographics | Age, income, and credit scores of borrowers. |
| Property Value | The assessed or market value of the property. |
| Payment History | Records of payments made, including on-time payments and defaults. |
| Loan Term | Duration of the loan, typically in years (e.g., 15 or 30 years). |
| Refinancing Activity | Data on the frequency and characteristics of loan refinancing. |
| Geographic Data | Regional information, including state, city, or neighborhood of the mortgaged property. |
How can I assess the quality of Mortgage Data?
To assess the quality of mortgage data, users must ask providers where they got their data and what processes are involved in creating their datasets. Good quality mortgage data must also be accurate and reliable. Furthermore, sources of mortgage data must be credible and must be timely. Since some borrowers are unable to maintain a good credit score, data updating important so that the data reflects their most current credit score. Data providers must also offer excellent customer service, and provide extra mortgage information in case questions about the data are raised. Lastly, users may read online reviews to ensure credibility and ask for a mortgage data sample to counter-check if it is worthy.
Frequently Asked Questions
How is the Quality of Mortgage Data Maintained?
The quality of Mortgage Data is ensured through rigorous validation processes, such as cross-referencing with reliable sources, monitoring accuracy rates, and filtering out inconsistencies. High-quality datasets often report match rates, regular updates, and adherence to industry standards.
How Frequently is Mortgage Data Updated?
The update frequency for Mortgage Data varies by provider and dataset. Some datasets are refreshed daily or weekly, while others update less frequently. When evaluating options, ensure you select a dataset with a frequency that suits your specific use case.
Is Mortgage Data Secure?
The security of Mortgage Data is prioritized through compliance with industry standards, including encryption, anonymization, and secure delivery methods like SFTP and APIs. At Datarade, we enforce strict policies, requiring all our providers to adhere to regulations such as GDPR, CCPA, and other relevant data protection standards.
How is Mortgage Data Delivered?
Mortgage Data can be delivered in formats such as CSV, JSON, XML, or via APIs, enabling seamless integration into your systems. Delivery frequencies range from real-time updates to scheduled intervals (daily, weekly, monthly, or on-demand). Choose datasets that align with your preferred delivery method and system compatibility for Mortgage Data.
How Much Does Mortgage Data Cost?
The cost of Mortgage Data depends on factors like the datasets size, scope, update frequency, and customization level. Pricing models may include one-off purchases, monthly or yearly subscriptions, or usage-based fees. Many providers offer free samples, allowing you to evaluate the suitability of Mortgage Data for your needs.
What Are Similar Data Types to Mortgage Data?
Mortgage Data is similar to other data types, such as Home Ownership Data, Property Data, Real Estate Market Data, Commercial Real Estate Data, and Residential Real Estate Data. These related categories are often used together for applications like Smart City.
