The property market, like that of gold and oil, is a rather murky world.
The prices you’ll see on most websites are asking prices. The value of a done deal – the real price – can take land registries weeks to process, by which time a fast-paced market will have moved on.
So those on the inside doing the deals, such as estate agents and developers, have a distinct advantage.
Could technology help blast open this closed market?
Teun van den Dries, chief executive of Dutch software company GeoPhy, believes his data analytics software program could do just that, starting with commercial property, a global market worth about Ä22.5tn (£15.7tn), according to the European Public Real Estate Association.
His program crunches lots of different data sets – public transport, roads, congestion, location, demographics, local economy, building quality and so on – to calculate an estimated value for a property.
And he has data for 41 countries, from Singapore to Spain, Brazil to Belgium.
“If you look at the current property market, almost all transactions are handled by estate agents that will describe property as being well situated, with great accessibility and beautiful views,” he says. “And that could all be true, but it doesn’t mean anything and it doesn’t allow you to compare.”
Location accounts for 70%-75% of the weighting in the algorithm – a mathematical set of rules – and his pricing is accurate within about 5%, he says.
Estate agents are known for their creative euphemisms when it comes to property descriptions, but data could help cut through the sales speak to arrive at a more realistic assessment, he believes.
But, he notes, “a valuation is never right until someone pays. So, it’s the same price point a surveyor will put their signature on.”
The only difference is that it’s derived from data and a set of comparable rules, he says.
However, there are some valuations it can’t help us to understand – parts of London, such as St James’s Park or Mayfair, home of the £90m mansion, simply defy data analysis.
At present, his customers are pension funds and other large institutions that own property portfolios. They want quick access to property valuations, as well as other data, such as the energy efficiency of their buildings.
But he hopes this type of analysis could also help make the residential property and rentals markets more transparent, too.
So when your landlord says prices are rising in your area and hikes up your rent, you’ll be able to see if that’s really the case, says Mr van den Dries.
But not everyone is so sure about the benefits of data analytics in the commercial property market.
For example, a seller may offload a building to make a loss to offset against tax and as such will sell at a lower “rational” price, he says.
And shifts in economies thousands of miles away – China or in the Middle East, perhaps – could suddenly empty money out of a given market, without the data giving any warning.
While many large publicly owned property owners have talked about using data, many “just don’t really know where to start and are only at the start of the journey,” he says. “Commercial property is the last imperfect market.”
“Homes may be better, as they are more homogenous and could be more comparable,” he adds.
Mr van den Dries admits that there is some resistance to this new data-driven approach – a number of property owners have expressed displeasure at having their buildings benchmarked, he says.
But he, and others, remain convinced that better analysis of more data is key to a more efficient – and less mysterious – property market.