More science, less art in property assessments
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With analytics and machine learning, Wake County, N.C., is removing much of the human subjectivity from the process.
By using analytics and machine learning to assess real property values, Wake County, N.C., is removing much of the human subjectivity from the process, resulting in more accurate numbers and cost savings.
Wake County Tax Assessment Model
Wake County, N.C., Revenue Department
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Machine learning software from SAS crunches data on the county’s 400,000 properties. That data includes more than 140 variables such as square footage, exterior finish, neighborhood and number of bathrooms. The software uses a sophisticated algorithm to turn around estimations in minutes.
“It’s important to note that the method we are utilizing to assess properties hasn’t changed,” said Marcus Kinrade, the county’s revenue director. All counties must still comply with the state’s General Statutes and use a uniform schedule of values, standards and rules.
“That being said,” he added, “there is a lot of subjective analysis performed by our appraisers when applying the schedule of values, particularly in a market where property values are increasing rapidly. The SAS machine learning models only consider the data, and there is no emotion or human judgment involved. So as a tool providing a check and balance to the work our appraisers are doing, it’s invaluable.”
The department has also used the software to review the boundaries of valuation control areas, or groups of similar properties. “The real benefit is we have a completely objective tool to either validate or possibly invalidate the historical appraisal techniques our office performs,” Kinrade said.
The software is saving the county money because appraisers can work from the office rather than in the field, and the department has had to hire fewer contractors because its employees are more productive.
“As we go forward, we hope to save money in processing appeals that result from potential subjective inequities in assessments by identifying and eliminating possible bias before it occurs,” Kinrade said. ”Working thousands of appeals is a tremendous expense,” and reducing it would yield a monetary benefit to taxpayers and increase public trust in the department’s work.