What is an AVM? ( Automated Valuation Model)
AVMs are software-based pricing models used in the real estate market to value properties. AVMs are more efficient and consistent than a human appraiser, but they are also only as accurate as the data behind them. AVMs use advanced analytics, such as machine-learning models, to analyze many different data points for a given property to predict a property’s current or future value.
Here is ATTOM Valuation Process:
ATTOM’s AVM Accuracy :
AVMs are used in real estate business to capture information of potential home-sellers, Zillow Zestimate is the most well-known example for an AVM provider.
Pros:
- It a quick way to give home buyers and sellers a sense of their property value without going too deep in the real estate process.
- It is a proven way to attract valuable leads.
- It provides “tipping point” in making home buyers and sellers decide to take action.
Cons:
- AVMs are only estimates – can be misleading, can not replacing more in-depth like in-home inspections/appraisals or CMA.
- The average Zestimate is off (+/-) by $14,000. This can go up or down depending on the availability of public records in that area.
- They are automated – because they are automated, AVMs don’t take into account the human element of real estate. This may include neighborhood changes that can be intangible to home improvements that aren’t reflected in public records
These pros and cons explain the important of confidence score and forecast standard deviation that represents the precision of the AVM estimate and measures the deviation between the range of values and the point value itself.
According to ATTOM robust statistical models, a forecast standard deviation max of 0.08, (ATTOM begins their model by creating a geostack that’s ordered from the most local areas to the larger surrounding areas. Geostacks are particularly important in calculating hyperlocal valuations because they allow you to draw your sample from within a single neighborhood, even when properties in other neighborhoods are physically closer).
A forecast standard deviation max of 0.08, confidence score using the forecast standard deviation max as follows: Confidence Score = 100 – (0.08 x 100) = 92
A higher forecast standard deviation, the range of probable sales price will be wider and the confidence score will be lower. Conversely, with a lower forecast standard deviation, the range of probable sales price will be narrower, and the confidence score will be higher. What our confidence score communicates is that we are confident we’ve estimated the value of the home within a percentage of the sales price. So, a score of 92 means we are confident that our estimated sale price is within 8% (100 – 92) of the true market value.
Current AVM is for standard single-family residences, not for Mobile Homes, Homes on Farm or Agricultural Land and • Multi-Unit Homes due to two reasons:
- These property types typically have a negative impact on the predictive value of other homes.
- These property types require different data and modeling.
