Propensity to DefaultAnalytics. Predictions. Returns.
Propensity to Default—Probability of a Home Going into Foreclosure
Real estate investors, lenders, and insurers are always looking to stay ahead of the competition. Having access to predictive analytics that identifies a homeowner’s propensity to default profoundly influences business decisions, and ultimately, returns.
In any given year, only a small percentage of homeowners default on their mortgage, so pinpointing the properties that will start the foreclosure process is complex. However, ATTOM uses algorithms and predictive modeling to create residential default propensity scores so that investors, lenders, and others can determine the implied risk of an investment or find homeowners motivated to sell their property before going into default.
How the Propensity to Default Model Works
The ATTOM model uses a variety of data and AI-powered algorithms to determine propensity scores for individual properties where mortgages exist. Each property is given a normalized probability score ranging from 0-100. The higher the score, the more likely the property will default within the next 12 months. Properties are also classified into propensity groups to show a relative likelihood of each specific property going into to default over 12 months, as a comparison to all other properties in the dataset. This allows customers to zero in on the properties within each group that have the highest propensity to default within the next 12-month timeframe.
What ATTOM Delivers
Our model delivers a propensity to default score for every property with an active mortgage in the United States in bulk or cloud. These products include:
- Property Information
(ATTOM ID, address, location)
- Propensity Scores
How Can You Use ATTOM’s Propensity to Default Data?
Reduce risk by pinpointing properties at a higher risk of default. Find listing opportunities and homeowners who might be motivated to sell early and avoid foreclosure.
What is Propensity to Default?
The propensity to default is the likelihood that a homeowner will fall behind on their mortgage payments. A propensity model predicts the probability of default based on factors such as home values, loan structure, and homeowner behavior.