Getting a 360° View

By Bob Violino  |  Posted 2009-07-28 Print this article Print

Server virtualization, self-service applications and service-oriented architecture give banks and other financial institutions the tools to increase their efficiency, cut costs and boost revenue.

Getting a 360° View

Boeing Employees’ Credit Union (BECU), the fourth-largest credit union in the United States based on asset size and membership, is using a combination of location intelligence, data quality initiatives and business intelligence (BI) to create a real-time 360-degree view of its customers.

Seattle-based BECU, which provides a full suite of financial services (savings products, mortgages, loans and wealth management services), wanted a way to access complete member records from multiple data sources using a single resource that’s quickly available to employees. It also wanted to transform this data into information that would drive critical analyses and decisions.

BECU had been using Data Flow, a data processing engine from Pitney Bowes Group 1 Software that implements data integration, data analysis and information delivery services. About 200 users in the field can access specific member information over the Web from reports created by in-house analysts. Another 60 to 70 power users do intensive analytical research to gain insight into member data, such as how well BECU markets a particular product to target members, which ATMs members are using and where members are conducting transactions.

In 2007, the credit union added a location component to its BI strategy when it implemented Pitney Bowes’ AnySite site analysis and decision support solution. The application is designed to perform display analytics and modeling functions, allowing BECU to incorporate data formatted by Data Flow and use it to analyze the relationship between the credit union’s performance and trade area demographics.

Calvin Bierley, market research analyst at BECU, says these technologies enable the firm to effectively conduct saturation and regression analysis and see where the greatest potential exists to add or close retail sites. “Regression analysis is used to predict the performance—loans, deposits and new customers—among branches based on the population characteristic of the surrounding trade areas and BECU’s existing member base,” he says. “These models explain about 40 percent of the difference in performance among the branches. It can then identify branches that are underperforming.”

BECU has used the technology as the basis for its decisions on where and when to open 10 new branch locations. With AnySite, the firm can see the demographic specifics and pinpoint areas where it needs to market more effectively or place a new branch. 


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