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Pondera FraudCast Blog

Pondera FraudCast

Welcome to the Pondera FraudCast, a weekly blog where we post information on fraud trends, lessons learned from client engagements, and observations from our investigators in the field. We hope you’ll check back often to stay current with our efforts to combat fraud, waste, and abuse in large government programs.


Jon Coss
Jon Coss
Pondera's FraudCast Blog
The Problem With Knowing What You Know

The Problem With Knowing What You Know

I bet you cna’t bvleiee taht you can uesdtannrd waht you are rdnaieg. Unisg the icndeblire pweor of the hmuan mnid, aocdcrnig to rseecrah at Cmabrigde Uinervtisy, it dseno't mttaer in waht oderr the lterets in a wrod are, the olny irpoamtnt tihng is taht the frsit and lsat ltteer be in the rhgit pclae. The rset can be a taotl mses and you can sitll raed it whoutit a pboerlm. Tihs is bucseae the huamn mnid deos not raed ervey ltteer by istlef, but the wrod as a wlohe.

The preceding paragraph, which has made its way around the Internet for years, can be really fun to share with friends. However, it also serves as a caution to anyone involved in fraud detection. In many ways, bad actors, knowingly or unknowingly, have depended on how the human mind works to perpetrate fraud schemes. Like the old expression goes, sometimes the best place for fraud to hide is in plain sight.

This is especially true in government programs that process massive amounts of transactions and must adhere to a staggering number of program regulations. Traditional “top down” systems can analyze large data sets and find nothing wrong (after all, the first and last letters are in the right place). “Bottom Up” systems, on the other hand, will identify individual problems (the word is scrambled) but may miss the patterns in the data (this entire paragraph is scrambled). A common example of this is the medical provider that always “flies just below the radar” by maximizing claim amounts and frequencies.

The best detection processes take both a “top down” and “bottom up” approach. They can identify individual transaction problems as well as identify patterns of bad behavior over time. In this way, you can make the old “80-20” rule work in your favor. 80% of improper payments are likely caused by 20% of program participants. If you only address each individual transaction, you’ll never run out of work but you also never really improve your program integrity efforts.

Click here for an infographic on the "80-20 rule".

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