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Pacific Coast Companies, Inc. Detects Internal Fraud, Forecasts Sales with SPSS Predictive Analytics

  • 25 September, 2008 12:34

<p>With confidence among U.S. homebuilders at a record low, signaling no relief in sight from the worst housing slump in a quarter century, it’s crucial that homebuilders maximise resources and keep funds in check. To stay ahead of the curve, Pacific Coast Companies, Inc. deploys Predictive Analytics software from SPSS Inc. (Nasdaq: SPSS) to identify internal fraud, forecast sales and better analyze vendor and product supply for the company.</p>
<p>Pacific Coast Companies, Inc. is a central services company for Pacific Coast Building Products – a family of diverse manufacturing and distribution companies providing building materials, such as concrete block, terra cotta and roofing products, to the construction industry in the Western United States, Hawaii and Canada.</p>
<p>The organisation sought to proactively mitigate risk, generate revenue and control expenses, so it selected SPSS Predictive Analytics data mining technology for its ease-of-use and flexible architecture.</p>
<p>SPSS Predictive Analytics software enables the organisation to discover new insight on business problems, such as identifying indicators to fight internal fraud, saving the organisation time and money. Pacific Coast Companies uses SPSS Predictive Analytics to create segmentation models that identify internal activity anomalies, such as when an employee cancels an invoice or deletes a delivery document, which provides supporting evidence on potential internal fraud.</p>
<p>Pacific Coast Companies also uses SPSS Predictive Analytics to forecast sales by analyzing data on the correlation between when a building permit is submitted and when the organisation should expect to see building materials purchased – enabling the accurate prediction and forecasting of sales.</p>
<p>Additionally, SPSS Predictive Analytics supports Pacific Coast Companies’ effort to better investigate product pricing, consolidate the amount of products sold, understand vendor selection, cut down purchase order processing time and analyze error rates in accounts payable.</p>
<p>Anton Karnaukhov, business process technologies manager at Pacific Coast Companies, Inc., said, “In this tumultuous housing market, getting the right information to key decision makers quickly is imperative. SPSS software gives our organisation the ability to answer business questions with solid, data-driven results that we are able to act upon quickly.”</p>
<p>Jack Noonan, SPSS chairman, president and CEO, said, “SPSS Predictive Analytics software enables organisations to direct change to business processes by using fact-based data to predict future actions and outcomes to make more informed decisions, attract and retain customers, grow revenue, reduce fraud and mitigate risk.”</p>
<p>About Pacific Coast Companies, Inc.</p>
<p>Pacific Coast Companies, Inc. is a dedicated team of professionals that provide a comprehensive range of business services to the Pacific Coast Building Products Family of Companies and their customers. These services include Accounting &amp; Internal Audit, Environmental Consulting, Human Resources, Finance, Information Technology, Marketing &amp; Advertising, Risk Management, Legal Services, Tax and Treasury Management.</p>
<p>About SPSS Inc.</p>
<p>SPSS Inc. (Nasdaq: SPSS) is a leading global provider of Predictive Analytics software and solutions. The company’s Predictive Analytics technology improves business processes by giving organisations forward visibility for decisions made every day. By incorporating Predictive Analytics into their daily operations, organisations become Predictive Enterprises -- able to direct and automate decisions to meet business goals and achieve a measurable competitive advantage. More than 250,000 public sector, academic and commercial customers rely on SPSS technology to help increase revenue, reduce costs and detect and prevent fraud. Founded in 1968, SPSS is headquartered in Chicago, Illinois. For more information, please visit</p>

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