For consumer-oriented companies, split-second answers to questions about each customer can mean the difference between poor performance and profitability. Will this consumer pay on time? Is this new website visitor likely to make a purchase? Has there been any fraudulent activity associated with this customer? When companies have questions, eBureau has answers. In seconds, eBureau can assess a consumer based on tens of thousands of variables, and then deliver solid data that helps companies market their products and services more effectively, prevent fraud, and manage receivables.

“We can gather, mine and analyze content about a consumer, summarize the data into a profile, and deliver it to a customer in less than a second,” explains CEO Gordy Meyer. “Apple tools have enabled us to forge a new model for consumer statistical modeling and analysis that allows us to turn data around at lightning speeds with a high-availability, low cost IT infrastructure.”

Unique technological advantages

When eBureau was founded in 2004, both Meyer and CIO Jon Moog had several make-or-break technology decisions at hand. For the company’s core data-processing application, they needed the high-end speed and power that mainframes can deliver, but they had to closely manage costs. The company also required a custom data warehousing software solution, hundreds of terabytes of storage space, and desktop and laptop systems to keep employee productivity at its peak.

Technology, after all, is the company’s primary means of differentiating its services. eBureau develops and maintains its own custom databases, statistical modeling software, and proprietary predictive algorithms capable of slicing through up to 50,000 variables about a particular consumer—all in less than a second. The company has developed a unique predictive scoring architecture and its own codeX software, an extensible programming language that provides a common framework to integrate all the tools necessary for eBureau staff to manage, analyze, and process data. eBureau also prides itself on the vastness of the data used for predictive modeling. The company’s data warehouse consolidates more than 125 billion unique records on virtually every U.S. adult, more than 200 terabytes of continually updated data that can be mined quickly.

“Our first decision was easy: the return on investment for purchasing a mainframe simply wasn’t there,” says Moog. For data warehousing and analysis, Meyer and Moog decided to distribute processing tasks among several smaller servers, using hardware that is less expensive than mainframes. They considered a PC-based solution, but it did not offer the security and high availability eBureau required.