Putting Price Tags on Houses
Zürcher Kantonalbank knows its market, down to the square meter
Owing to the concentration of wealth in and around the Swiss Canton of Zürich, the housing market there is a dynamic one for renters and buyers, lessors and sellers alike. Until the 1990s, almost no reliable statistical data was available for any given property, and value estimations were either done by traditional real estate appraisers or by gut feelings about what the market value might be at a particular time. Listings of properties for sale or rent were available almost exclusively in newspapers.
Zürcher Kantonalbank (ZKB) recognized that the Swiss real estate market was no longer simply a bricks-and-mortar one. The bank saw growth potential and room for cost-saving strategies if statistical information could be made readily available both to its mortgage staff and to property seekers.
Real estate opportunities depend on the peculiarities of each market, and the Canton of Zurich is no exception. For example, it is mostly a rental market, compared to North America, where more people own their homes. So, when ZKB created its online real estate subsidiary, www.homegate.ch, in March 2001, the bank wanted to offer more than just Web pages listing the various properties available for purchasing and leasing. ZKB wanted to offer a value-added service to customers, the real estate management companies that rent or sell properties, in the form of analytics-based evaluations of the listed properties, quality adjusted with hedonic price indices.
"Pricing depends on many things other than the obvious location factor. Market fluctuations, timing, features of the property, its history and other related costs are all factors that are analyzed and aggregated for calculating the most accurate index," explains Marco Salvi, economist for Zürcher Kantonalbank. "Our market at the moment is one of strong demand, which means that in order to compete, we must be able to move quickly in order to match that demand. Thanks to in-depth analyses of the characteristics of the listed properties, we are able to benchmark each property and to pass those insights on to the landlords."
Using this service, rental and property management companies can maximize their exposure to high quality applicants and find optimal pricing strategies. "Landlords can use current data to decide whether they want to hold out longer for a tenant who might be willing to pay a higher rate or whether renting the flat quickly presents a better advantage for them," says Salvi.
Streamlining Both the Data and Business Costs
"Strategically, when ZKB senior management assigns specific growth goals," continues Salvi, "we are able to expand accordingly by knowing the true value of each property and then making those properties available to everyone on the staff via the intranet. We are able to know the market as it fluctuates and provide value-added services to our customers on both sides of the mortgage contract."
By using SAS, ZKB has reduced the cost of each appraisal by 97 percent, from CHF900 to CHF30. Taking into account that in 2002 approximately 40 percent of all Swiss mortgages were applications evaluated with hedonic models, it's easy to see the impressive shift in the cost/profit ratio of providing this service. ZKB can also control risks and losses. "The appraisal process is an important step in the monitoring of the mortgage credit risk. As such, we have almost zero percent default rate," Salvi says.
ZKB has made large-scale use of new, rich data sources and automated valuation models (AVMs) to estimate the market value of properties by statistical methods, including hedonic modeling, used by academic economists since the 1960s. In a nutshell, an AVM collects transactional data on houses and records their characteristics (size, age, location, quality, etc.). It then uses regression techniques to extract the market valuation of each of the various characteristics in relation to each other.
Applying Best Practices Vertically, Horizontally
With the success of combining online services with SAS analytics, Salvi and his team have been able to establish and demonstrate best practices that can be applied across departments to strengthen ZKB's overall market position.
About Zürcher Kantonalbank
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Economist for Zürcher Kantonalbank
To rapidly find the optimal price for real estate
SAS helps ZKB achieve a 97 percent reduction in evaluation costs, near zero percent default rate.
“Pulling together data and accessing it are some of SAS' major strengths. (Other vendors) could not scale with us as our needs grew, and SAS can do that.”
economist, Zürcher Kantonalbank