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There is a large information gap between professionals and non-professional in the real estate industry, largely due to the difficulty predicting market prices.
This is unlike the stock market, where the price of any particular share is the same no matter where you trade it from. In real estate, however, there are significant differences in price depending on various factors such as location, size and age of building. These factors can cause the price of identical properties to diverge significantly.
Thus, there is a movement in favour of using technology to predict market prices (an activity previously seen as involving the application of tacit knowledge built up over a long career).
Typical of such use of technology is estimation of real estate prices using big data and AI.
Big data and AI
“Big data” is an expression referring, literally, to large volumes of data. Improvements in data-processing technology allow big data to be utilized in business, and it is now used in problem-solving, in the raising of operational value-add, and in operational support.
For example, a certain maker of PCs analyses all client contact with its call centres to automatically ascertain what kind of problems are currently occurring with its products. It can also forecast what kind of problems are likely to occur in the future.
The use of a large volume of diverse information allows events to be modelled and the impact of proposed initiatives to be analysed. Big data is already in use in a wide range of areas including market analysis, driverless cars and infrastructure installation. Big data could be seen as equivalent to the “wisdom” of a person who has accumulated scientific skills such as statistics and data processing.
The application of artificial intelligence (AI) has allowed further progress with utilization of big data. The acronym AI is often used to refer to robots equipped with human-like consciousness and judgement.
In asset management centred on financial products, management by AI (in which transactions are carried out automatically according to pre-set criteria) is now common. This has even given rise to the word FinTech, which combines the words financial and technology. Services that similarly use big data and AI to analyse prices have recently come to the fore in the real estate industry.
Real estate evaluation using big data and AI
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In real estate pricing, although there are market prices, the sales price is ultimately decided between the buyer and the seller, making accurate prediction difficult.
Even when looking at actual transactions, it is not possible to estimate an accurate market price that reflects factors such as region, size, and the age of any buildings from a small sample. To be sure that all necessary factors have been reflected a vast amount of data has to be considered. This is where big data and AI comes in.
Since around 2015, services have become available that provide, for example, reference prices arrived at by AI analysis of past transaction data (big data) and real estate investment simulations based on those reference prices. Various refinements to these services are available, such as reference price maps, calculation of investment yields that take account of degradation over time and vacancy rates, and real-time assessment of sales price and rents.
Real estate services that utilise advanced technology in this way have become known as “real estate tech”.
Technology now an essential real estate investment tool
To estimate real estate prices from big data, large volumes of data and high-performance computers are needed. More and more real estate tech services estimating real estate prices are becoming available. We would encourage people already engaging in real estate investment, and those new to it, to utilise these services.
