REINZ automated estimate | frequently asked questions

The REINZ AVM is a computer-generated valuation of a property’s estimated current market value.

REINZ calculates an AVM for more than 92% of all New Zealand properties. Broken down by category coverage this increases to approximately 99% for houses, units and apartments, with residential sections and lifestyle blocks receiving approximately 98% coverage.

REINZ utilises a variety of different data sources when generating an AVM for a property. The combination of data is processed through several specialised machine learning computer models, these models generate a number of valuations for a particular property. Those valuations are individually evaluated for expected accuracy, with the most likely valuation selected as the valuation range mid-point, and the variation in valuations used to determine the valuation range. Predicting property values is an extremely complex process, as such the REINZ AVM uses REINZ proprietary sophisticated deep machine learning to incorporate over 200 individual datapoints to derive a prediction. Some of these datapoints include: Land area, Site Coverage, number of Bedrooms, number of bathrooms, building condition, floor area, latest CV etc.

REINZ models additionally account for the following factors

  • Geographical areas following different trajectories in terms of desirability
  • The attractiveness of a given housing feature e.g number of bedrooms may vary over time and by geographic location, and is influenced by various external factors (demographic trends, similar properties available on the market at a given time etc)
  • Recorded information on a property is often incomplete, requiring REINZ models to extrapolate data holes.

It is important to note that most build, rebuild or upgrade information (such as renovations) is not available in public records or is not easily quantifiable, therefore this information along with unique features, external factors like changes in the economy, the environment or infrastructure plans are difficult to include in the calculations.

How accurate is the REINZ AVM?

We have not physically inspected the property, its condition, and unique features and we rely on our data sources. Where our data sources are incomplete or inaccurate, the value may be impacted. 

To improve accuracy REINZ AVMs are recalculated every month, using historical and new data received from council, census, house price indices and most importantly property sales submitted by its members, over 1000 real estate agencies across New Zealand. Every month members submit thousands of sales to REINZ, including unconditional sales not publicly released. As the number of property sales in an area greatly affects how much we know about prevailing market values of homes in that area, this timely and exclusive data is pertinent to improving the accuracy of REINZ AVM predictions.

Accuracy also depends on the availability of this combined data in any given area. Physical house attributes obtained from both public and member-provided data such as bedrooms, bathrooms, house size, etc are also very important factors in determining accurate house price estimates, the more data available for our complex models to ingest the better.


What is the difference between an AVM and Comparative Market Appraisal?

REINZ AVM (‘automated valuation model’) is a computer-generated value which should only be used as a general guide and does not replace an agents obligations to provide a Current Market Appraisal (required under the Real Estate Agents Act (Professional Conduct and Client Care) Rules 2012) nor is it to be considered a professional valuation. A Current Market Appraisal takes into account unique features of the property, and can be different from the AVM value displayed. The AVM is based on market data and does not consider unique features of the property. We have not physically inspected the property, its condition, and unique features and we rely on our data sources. Where our data sources are incomplete or inaccurate, the value may be impacted.

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