Make faster, better lending decisions

Jonathan Walker needed a faster, more reliable way to support risk management and marketing efforts at Local Government Federal Credit Union.

“We were trying to use Excel in a way Excel is not meant to be used,’’ recalls Walker, LGFCU’s Business Intelligence Manager. “We had big challenges consolidating our data across multiple sources.”

In particular, LGFCU needed faster, more reliable insights about the impact of loan delinquencies on the balance sheet.
Excel was slow and unreliable. Manual data entry made errors common.

“Honestly,” says Walker, “sometimes we would have to run programs overnight and just hope that something didn’t break in the process and cause us to do it all over again.’’

With SAS® Business Intelligence, analysis that once took hours now takes minutes.

“I was spending 80 percent of my time on data preparation before using SAS,’’ explains Xin Pan, a Business Analyst on Walker’s team. “Now that I spend less on data preparation, I can focus on building a credit risk management system.”

Anticipating customer needs

Because SAS makes it easier to merge internal and external data sources, LGFCU can better anticipate the borrowing needs and understand the financial circumstances of all 230,000 members.

For example, LGFCU analyzes economic conditions in each of the state’s 100 counties and merges the data with its member data for a more complete and accurate view of each community and customer.

“We’ve really been able to streamline the process using SAS,” Walker says. “We have completely automated output without the need for tools such as Excel.’’

Meanwhile, Marketing Strategy Analyst Danielle Brummitt has a better understanding of how to communicate with each member, thanks to the 360-degree customer view that SAS gives her.

“We can actually look at transactional data coming from the branches,” Brummitt says. “We could not do that before we started using SAS. It was too much data.”

Now we can work with billions of rows, and our processing time has improved, in some cases, from days to minutes.
Jonathan Walker Local Government Federal Credit Union

Jonathan Walker
Business Intelligence Manager

Easing the regulatory burden

Federal regulators keep a close eye on mortgage-assistance programs that many lenders, including LGFCU, offer to struggling homeowners.

In fact, one of the required compliance reports includes more than 70 calculated fields, which caused headaches using Excel.

“SAS has streamlined the process, allowing us to provide this data faster to the lending department,’’ Walker says. “A federal regulator told me that the way we use SAS and analyze the data is something few other credit unions do and that our methods are paying off. It’s just great having these SAS resources at our fingertips.’’

Chris Koontz, the credit union’s Data Integration Architect, applauds the ease of installation and the gains in computing power.

“It took about two days to install the BI component,” he says. “Now we can work with billions of rows, and our processing time has improved, in some cases, from days to minutes.”

Visualizing data

LGFCU is implementing SAS® Visual Analytics to give senior management a way to visualize data correlations across multiple variables and billions of rows to make faster, more informed decisions – whenever and wherever they need answers.

“Right now, we provide static dashboards – either in PDF or Excel format,” Walker explains. “With SAS Visual Analytics, senior management will be able to interact with the data whether on the road through a mobile device or at their desktops. They’ll be able to make decisions based on longer historical trends. And what they discover will spawn even more questions as they dive deeper into the data.”


Make sound lending decisions based on an increasing amount of internal and external data, and make marketing decisions that are more relevant to each member.



Dramatic reduction in data preparation time and run time for analytics. In some cases programs that took hours – or even days – to run now take minutes.

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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