Adding Value with AI: A True Story
IN MARCH 2018, Kathy Gillis, the CEO of Property Valuation Services Corporation (PVSC), saw an opportunity in the property assessment field to use artificial intelligence (AI). Having little experience in the topic, she and her Vice President of Strategy, Meredith Buchanan, decided to bring their idea to a three-day AI seminar at the Rotman School of Management. The two quickly realized that PVSC was among the first to consider applying AI to the property valuation field globally.
Gillis brought the idea back to PVSC’s Chief Data Scientist, Dr. Ashley Wu, who was keen to pursue an AI approach. Within months, Wu’s team discovered they could use machine learning to predict property values faster, cheaper, and with more accuracy than any other technology. Now, Gillis needed to develop a strategy that would take advantage of this opportunity.
To value properties, assessors collect property data such as lot and building size, number of bedrooms, quality of construction, and recent renovations, often by visiting the site. This data is then combined with real estate market sales information to determine the property’s value. Each year, PVSC reassesses all properties in Nova Scotia, as municipalities use the property values to determine the amount property owners will be taxed. Notices are provided to owners indicating any change in their value. Owners who disagree with the changes may appeal this new value. Although appeals are rare, the process allows PVSC to gain up -to-date information and may result in revisions to the assessment.
At the outset, Gillis envisioned a tool to “raise the bar for accountability” across the industry, which may require “building a new software or a new CAMA [computer-assisted mass appraisal] system.” Wu felt that the latest AI methods might fit
