5 Data Analytics Strategies for Detecting Fraud

photo by Carrie Plummer

photo by Carrie Plummer

How Data Analytics and Actionable Intelligence Empower the New Breed of Fraud Analyst

At their most basic level, investigations are all about detecting patterns and making connections between people, places, systems, and events. This has never been an easy task with evidence scattered across multiple systems, involving multiple data types, and representing intentionally hidden activity.

Investigators have more and more electronic data available to them, but bigger is not always better. With less time and resources to wade through all this data, finding quality leads is a challenge. What you need is the right data and a fraud detection solution that extracts actionable intelligence to answer your most important investigative questions.

Taking advantage of this actionable intelligence with a few critical investigative building blocks—executed correctly from the start—can further improve your chances of success. The practices described below focus on enabling investigators to apply their experience and creativity in four critical areas of fraud investigations: targets, labels, situational awareness, and scope. With data analytics and visualization, investigators can then take the process even further.

This new realm of innovative technology (also called predictive analytics or big-data analytics) builds on the four critical areas listed and then applies technology so you gain actionable intelligence for your investigation. Like all good planning efforts, these building blocks will save you time and resources by increasing the efficiency and effectiveness of your efforts.

1. Rigorously define the targets you are investigating.

Properly defining what you are looking for will make it easier to notice when you see it, and keep you on target. For example, friendly fraud and account-takeover fraud both result in losses but can require completely different investigative approaches.

The same is true in healthcare fraud. A hunt for wasteful billing practices due to provider confusion can be completely different from a hunt for professional fraudsters who are adept at obfuscating their behavior and intentionally stealing millions of dollars.

The concepts of fraud and loss are generally not actionable without more precise definitions. It’s fine to measure aggregate losses, but without subject-matter expertise expressed in the form of fraud segmentation and labeling, your outputs (and you) will likely suffer from confusion, over-extended ideas, and unnecessary thrash.

2. Focus on the quality and consistency of your data labeling.

Having a sense of inter-rater reliability for fraud labels is critical, particularly when you are not only making binary decisions but also when you’re classifying accounts into different fraud segments. Pay special attention to the tools and data provided to you. Their ability to empower you to think creatively and critically is key to high quality decisions.

If possible, it can help to allow a set of transactions you would have blocked to go through, and then observe whether  they show behaviors consistent with the negative activity you expected (chargebacks, an unexplained surge in similar behaviors, complaints, etc). This control group logic is critical for many fraud fighting efforts because it relates directly to measuring false positives and optimization (see point #4).

There is also a fine balance to achieve with calibrating automated response test results. It’s quite common to see a model or rule return with abysmal performance only to realize after vetting that it had “caught” hundreds of transactions that were bad and simply mislabeled or not yet caught.


About securityteknews
Ralph Thomas is author of over 32 books on various aspects of conducting investigations, founder and director of The National Association Of Investigative Specialists,CEO of Thomas Investigative Publications, Inc, The Spy Exchange And Security Center and SpyTek Wholesale Imports. Thomas is a member of the Executive Security Council of Griffith Colson Intelligence Service, a private intelligence agency. Thomas's latest project is NAIStv on the Griffith Media TV Network. He has also developed A Native American Store in Georgetown Texas called Tribal Impressions. You can review his person home page off of: http://www.pimall.com/thomas

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