The enormous amount of available real estate data ensures that model-based valuations – predicted house values on the basis of big data and algorithms – are becoming increasingly smart and popular. Real estate professionals take advantage of this, as it saves them time and money. In addition, the accuracy increases. Factors and connections that are hidden deep within the data can easily be extracted and recognized by advanced systems and, therefore, be included in the valuation of an object.
International house valuation model
As a specialist in the field of model-based valuations, we have developed an international Automated Valuation Model. It concerns a mathematical model that calculates the value of one or more real estate objects on the basis of big data and algorithms. And that for more than 40 countries! As a result, real estate professionals can value individual houses or entire real estate portfolios worldwide, reducing the number of transactions and increasing the reliability.
To determine a house value, we use Machine Learning (ML) in combination with a large amount of international real estate, address and location data. The data used for this goes back to 1995 and says something about the object to be valued (such as the price development, the year of construction, surface area, energy label and housing type), the location characteristics, market developments and historical transaction prices of comparable houses in the area.
With the house valuation model, real estate professionals are supported in their daily work. For example, they can determine the profitability of investments, validate valuation reports and/or value collateral without the need for a physical valuation. This saves costs and time, which many real estate professionals now benefit from.
Complexity and reliability
The complexity lies in the representativeness of figures and training of the model. Our accumulated knowledge has played an important role in the development and optimization of the model. As a result, we can identify factors that do not belong to ‘normal’ sales conditions and then filter them out of the model. Think of family transactions, foreclosure sales or other outliers that influence the representativeness of a house value.
The model is continuously provided with accurate and reliable data. We achieve this by monthly ‘retraining’ our model with the latest real estate data. The ISAE3402 Type II certificate is a confirmation of the robustness of this process and the reliability of the resulting house values. In addition, we have our international house value model tested annually by the Erasmus University (Erasmus Q-Intelligence) to guarantee quality at the highest level.
The foundation for the development of our international house valuation model lies in being able to understand, process and combine large amounts of data. Data with one thing in common; Location!
Each country has unique address, housing and location characteristics, which complicates the development of an efficient and effective international valuation model. Nevertheless, we succeeded in developing a model that works “borderless”, meaning there are no limits (read boundaries) to zoom in on properties and patterns per location. The strength of the model lies in its intensive training, in which the data in all 40+ countries is categorized into hexagons. This enables it to understand and convert these various data into actual house values.
The international house valuation model is disruptive to the traditional valuation market, as high costs and long waiting times have become a thing of the past. In a market where quick action is a must, the solution lies in reliable automated house valuations for a fraction of the cost and time.
Would you like to know more about our international home value model? Please contact us.