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
In a further application of data-analysis techniques to real estate data, ZKB developed an automated appraisal tool. "We use almost 20 years of internal customer data, combined with external historical property data and market statistics. Pulling together data and accessing it are some of the major strengths of SAS. With solutions we have used from other vendors in the past, we found that they could not scale with us as our needs grew, and SAS can do that," says Salvi.

"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."

Measurable ROI
Since 1997, ZKB has used SAS to create statistical evaluation models to determine the most accurate and current property price. "Traditional evaluation methods cost approximately CHF900 (US$668), but using SAS, we have brought our cost down to approximately CHF30 (US$22). We are also very accurate and can permanently monitor the accuracy of the model," emphasizes Salvi.

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
"SAS is our tool of choice for accessing our customer data, to analyze it, disseminate it and ultimately to support us in making strategic decisions. By working on these types of isolated projects within ZKB, we can demonstrate to the group as a whole how these types of best practices can be applied upwards and horizontally throughout the entire organization," Salvi explains.

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
Founded in 1870, Zürcher Kantonalbank is Switzerland's largest Cantonal Bank and the third-largest Swiss bank. It is also a market leader in the area of Zurich, the most populous of the Swiss Cantons with wealth levels that are among the highest in Europe. With about 50 percent of the market share, in 2002 ZKB achieved total assets of CHF80.5 billion (US$59.8 billion) and client assets of CHF74.5 billion (US$55.3 billion). Its wholly owned online real estate subsidiary, www.homegate.ch, is Switzerland's largest online real estate listing service. ZKB is ranked with a AAA rating by the rating agency Standard & Poor's.

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