Big Data Strengthens Property Market Self-Governing
For the sake of argument, let’s assume that no one would knowingly overpay for the purchase of a home or investment property.
Let’s further assume that no bank would jeopardize its business and incur the wrath of the Monetary Authority of Singapore (MAS) by lending money to credit-suspect borrowers who are buying overvalued property.
Finally, let’s assume that the Singapore government wants to strike the right balance between housing affordability, capital appreciation for retirement savings, and global investment for the sake of the economy.
If we take these assumptions as valid, then why in the world did the property market reach a point at which cooling measures have cost us $ 21 billion in lost market value…and counting?
Four words: lack of pricing transparency.
When participants have insufficient information to make pricing decisions, markets fail.
Imagine if there had been a transparent, market value for each home in Singapore in 2006. How would this pricing mechanism have changed things?
First, the government would have been able to monitor the pricing mechanism of different market segments, at the granular level, against other key indicators, like income, inflation and GDP.
This would have given decision-makers more timely information on which to set policy.
For example, by tracking a big dataset of changing home valuations, policy analysts could have detected the upward pressure on prices in real-time. This would have given policymakers more information in which to decide whether or not to take preemptive actions like increasing land supply and authorising more development of Housing Board and private projects.
As a result, this timely increase in supply would have helped position the market to absorb the subsequent increase in demand that was caused by low interest rates and cheap mortgages.
Second, if we assume that consumers don’t knowingly overpay, a transparent market value on each home would have given them an unbiased guide based on data in which to negotiate a deal between a willing buyer and a willing seller.
Third, a transparent pricing mechanism would have allowed banks to establish (meaning mark-to-market) the real-time value of their entire mortgage portfolio in a matter of minutes. With this capability, credit analysts and MAS could have tracked the portfolios daily and made risk assessments in real-time. This, in turn, would have allowed the banks and regulators to identify non-performing loans and take actions quickly, on an individual case basis, rather than using a blunt instrument that imposed one-size-fits-all borrowing limits on all Singaporeans.
Fourth, a market valuation on each home would have prevented cases of misrepresentation that hurt the real estate industry’s reputation and led to a new regulatory body being formed at taxpayer expenses. Transparent pricing would have made it difficult to dupe naïve buyers and sellers. Furthermore, if misrepresentation had occurred, there would have been sufficient documentation for the legal system to handle it.
In summary, transparent pricing means government has more comprehensive and timely information in which to conduct urban planning and set policy.
Agents have a pricing benchmark to guide their clients, document their needs, and negotiate the right home at the right price.
Finally, the property industry can regulate itself because the pricing is now transparent. This means there is less of a need for government to intervene in the property market.
The good news is that, today, technology and big data make a transparent pricing mechanism possible.
SRX Property's X-Value is a case in point. Developed with government agencies, academics, and valuers, it sources from the nation’s most comprehensive property database and instantaneously calculates a single value for every home in Singapore using best practices methodologies including comparable market analysis.
As a computer-driven price mechanism, X-Value, factors in all the comparables and adjusts for important variables like location, size, floor, and age.
It also factors in macro trends from its proprietary price indices; and important on-the-ground information from thousands of market participants interacting with SRX Property apps and pricing data on a daily basis.
It’s impossible for a human, even if it had access to all SRX Property’s raw property and geospatial data, to do what a computerized price mechanism does in seconds in terms of accuracy, data completeness, relevancy, and objectivity.
Already, people are requesting over 60,000 X-Values per month. Last year, 93.8% of HDB homes were transacted within 10% of the X-Value.
Researchers and analysts can use X-Value to track market movements and estimate gains and losses. For example, SRX Property arrived at $21 billion by using the X-Value to calculate the value of all transacted flats (recorded) at the market’s price peak and then compared it with their values at 31 December 2014.
At their peak, the measurable market value was at about $455 billion while it was $434 billion at the end of 2014. The difference is $21 billion and counting because prices continue to drop.
Consumers can freely use it to check on a valuation price of properties they are interested in.
Government agencies and research institutions can use X-Value and associated data and analytics to forecast the market and solve problems before they get too big.
The purpose of big data and technology is to improve productivity, efficiency, and decision-making.
A property market with a universally-accepted and transparent pricing mechanism would make the market more transparent, keeping it on an even keel that reduces the need for cooling measures.
Will your home be sold at a profit today? Check your home's X-value now!