sascom voices - The sascom magazine blog

The recent article, Data-Driven Crime Fighting in Intelligent Enterprise reminded me of the feature we published in sascom earlier this year from Dr. Colleen McCue, a consultant who specializes in the provision of public safety and national security research, analysis and training. From the Intelligent Enterprise piece:

If there was a time when law enforcement agencies suffered from an information deficit, it's passed. Of the more than 18,000 law enforcement agencies across the United States, the vast majority has some form of technology for collecting crime-related data in digital form. The biggest city agencies have sophisticated data warehouses, and even the most provincial are database savvy.

From the sascom piece, Criminal Justice in the Post-9/11 Era:

While information sharing requires a cultural change and paradigm shift in the larger public safety community, advanced analytical techniques are available now. The same tools that were being used to prevent people from switching their cellular telephone service provider and to stock shelves at our local supermarkets before Sept. 11 can be used to create safer, healthier communities and enhance homeland security.

In September, I published a few posts from the Midwest SAS Users Group (MWSUG) conference, including coverage of presentations from SAS VP John Sall, SAS CIO Suzanne Gordon, SAS Consultant Kirk Paul Lafler and JMP Marketing Director Jon Weisz.

Now that the MWSUG organizers have published the conference papers online and announced the best paper winners, I want to highlight my favorite talk from the conference: Revolutionary BI by Charles Kincaid.

Charles, an Engagement Director at COMSYS, describes the ways he thinks analytics and business intelligence will be used and shared inside organizations in the future, and I think even George Jetson's employer Spacely Sprockets could benefit from his ideas.

If you've ever wondered how Web 2.0 will affect reporting and analytics in the future, Charles lays out the most comprehensive predictions I've seen yet. He looks beyond social sharing features like those you find on Facebook and Twitter, and describes intelligent reporting systems that will recognize common users of single data sources and allow report users to favorite or suggest changes to reports that are created by other users.

In addition to the MWSUG talk, Charles has presented his paper at other conferences, including SAS Global Forum 2009 in Washington, DC. In fact, he says his presentation at SAS Global Forum inspired one conference attendee to try some of Charles' ideas in his own banking organization, and that user is now presenting his results at SAS conferences too.

Read the full paper to understand Charles' vision for the future of business intelligence. Maybe you'll be inspired too.

Over at The Data Mining Research blog, Sandro posted a link to the presentations from a recent SAS Forum Switzerland. While browsing the presentation slides, I came across this great list of questions from a UBS presentation by Daniel Rüegge, Head of Business and Client Analytics.

Daniel calls these the top 10 paradigms in analytics to be questioned and asks, "Are they true? Are they of help? How do you apply them?"

What do you think? Which of the ten are true, and which are complete myths?

1. To make analytics successful, the CEO has to have a personal interest in it.
   
2. Analytical organizations have to be positioned in a central high-power position.
   
3. Every company in a competitive environment needs analytics to be successful.
   
4. Analytical expertise can/cannot be out-sourced/in-sourced/off-shored.
   
5. Getting data and technology in place is a long and cumbersome process.
   
6. Without data and technology you cannot do analytics.
   
7. Analytics is a thing mainly insiders and experts understand, and vice versa.
   
8. Communication of analytics is more important than analytical people think.
   
9. Analytics only should do things which have a measurable impact.
   
10. Analytics mainly is applicable in retail/standardized environments.

The customer intelligence event that I attended last month in Boston is making a stop in San Francisco tomorrow. The morning briefing includes a presentation from Forrester Analyst Surresh Vittal, followed by a panel discussion featuring Vittal, HP VP of Customer Intelligence Prasanna Dhore and Stanford University Graduate School of Business Professor James Lattin. Deb Orton, SAS Marketing Director, will be moderating the panel.

In Boston, discussion topics included:

• New rules for marketers.
• Analytics that start with the customer.
• Changing economy = changing priorities.
• Engaging the customer online and offline.
• Optimizing for success.

The opening talk from Vittal presents relevant statistics that reveal the changing roles of marketers. Vittal has practical advice for how to approach the change strategically and realistically.

At the Boston event, Vittal said marketing is undergoing a massive transformation, but most marketers are still playing by the old rules.

I love this idea of the analytics community being the "translation layer" within an organization. Customer Lori Bieda introduced the concept in the fourth quarter 2009 sascom column, Lost in translation:

For large organizations with many lines of business and deep, rich databases, making sense of information has become a business itself. What is needed now is a “translation layer” to ground businesses in fact-based decision making. The analytics community is ideally positioned to become the translation layer.

Bieda, who leads a team of 80 analysts at Canadian bank CIBC, explores this idea further in the new white paper, The Translation Layer.

The paper includes a useful chart defining and describing three roles for analytic workers in the tranlation layer:

• Analytics Community as SERVICE PROVIDER: Facilitates execution of analysis and research for the organization and provides analytical support to enable business decisions.
  
• Analytics Community as CONSULTANT: Acts as a centralized hub for all analytics and research knowledge and expertise in the organization and facilitates best practice information exchange related to that expertise.
  
• Analytics Community as BUSINESS DRIVER: Leverages domain expertise in analytics and
  research, combined with business knowledge, to filter, challenge and prioritize incoming requests for the benefit of overall business.

Which of these roles sounds familiar to you? Does one of them fit your job description? Or does your organization still need to create a translation layer?

Is it even possible to reduce fraud? This pointed question was asked Tuesday at the SAS Media Day fraud panel. After all, today’s fraudsters are smart, global, networked and hi-tech. As soon as you catch one, another steps in. And once you put a system in place to combat a certain type of fraud, a whole different type of fraud appears that you probably never anticipated.

“Fraudsters are very much like a pack of wolves,” says Chris Swecker, corporate security expert and former Assistant Director of the FBI. “And the financial institutions are the prey: They’re really trying not to be the next victim, and they’re trying to outrun each other or hide the best they can.”

But it doesn’t have to be that way. “I think those roles can be reversed,” says Chris. “With the help of analytics designed to look at ring-related network activity, you become the hunter and the fraudsters become the prey.”

Rex Pruitt, a Business Analyst at PREMIER Bankcard LLC, agrees that it is possible to reduce fraud, and he has the numbers to prove it. Using predictive models to anticipate fraud activity before it occurs, his organization reduced the rate of application fraud in its portfolio from an estimated 4 percent down to an estimated 3 percent.

“That equates to about $9 million in total revenue to the company,” says Rex. “You gain a lot by being able to identify those fraudsters.”

How does it work? The predictive model identifies fraudsters with a score during the application process. Applicants identified as fraudulent are eliminated from the portfolio before the bank has even incurred the cost of fraud. Rex says early identification can also free up volume capacity, so the bank can bring on more good applicants.

To build on the type of analysis PREMIER is already doing, Chris Swecker suggests banks use network analysis to identify rings of fraudsters that can be observed in the bank’s data. “You’re not going to eliminate fraud – but you can create better deterrents and a much higher risk environment for fraud,” he says. ” What I advocate, and the record is very clear: the way to get at financial crimes is to look at them, address them and detect them as a network.”

Chris worked with a large, international bank on a networked fraud detection project using SAS and was able to identify 40 new fraud rings almost instantly. “We had billions of transactions, hundreds of thousands of customer accounts, and myriad of products and services. SAS provided a way to look at the data and see the broad network activity that’s going on using our own data.”

Chris says there’s a clear supply chain that you can see when investigating networked crimes, especially with Internet crime: You have individuals that steal and sell the data, buyers who usually resell it, and eventually the data makes its way to the people who exploit it by manufacturing credit cards and debit cards, which then pop up somewhere in the hands of someone committing the detectable fraud act.

“I’m careful not to use the word ‘organized crime,’ because it’s ‘network crime,'’’ says Chris, and there's a difference. “It’s not like a hierarchy with a crime boss on top and layers below him in an org chart. Fraud networks are spidered out. It is a network, and we ignore the network at our own peril.”

Hear more from Chris and Rex – and learn about SAS fraud solutions by visiting the Media Day press kit or watching video snippets of the panel discussion by topic area: