Category Archives: Link Analysis

Premium Fraud – Piano Tuners and Window Washers?

Posted by Douglas Wood, Editor.

I came across a news article earlier this week regarding a business owner convicted of fraudulently avoiding worker’s compensation premiums. The link to that news article is below.

It brought to mind some fascinating work I was involved with a few years ago to help a state run Worker’s Compensation Bureau more effectively detect this kind of fraud.  Their biggest concern was recovering monies owed by companies who illegally misrepresent themselves for the purpose of reducing or avoiding the payment of premiums. Here’s how these scams work…

Intentional Misclassification: A crooked business claims that employees work safer jobs than they really do. Perhaps a high-rise window washer is falsely classified as a piano tuner. Much lower premiums, obviously.

Employee Misrepresentation: A business says it has fewer employees or a lower payroll than it actually does.

Coverage Avoidance/Experience Modification: A business simply doesn’t buy the required insurance, hoping state officials won’t notice. If the state learns of the avoidance, the company will simply close, then re-emerge as a ‘new’ company’ in order to avoid the payments.

So the state bureau I worked with needed to understand when, for example, a ‘piano tuner’ was requesting a permit for high rise window washing. Red flag, right?  Or when an five separate claims were filed by employees of a company who stated they had only 3 employees. Another red flag.

Oh, and what about a new company registrant whose owners, address, telephone number, and line of business are all suspiciously similar to those of a recently closed business who owed thousands of dollars in back premiums. BIG red flag.

The state itself had all of the data it needed to detect this fraud. The problem, as is often the case, is that the data sat in different jurisdictions. Working with our client, we helped those other jurisdictions – Business Registrations, Building Permits, Tax Departments, etc. – understand the value of sharing that data. That’s the key to this success story – data sharing. Without it, problems are much more difficult to solve.

Ultimately, we delivered a system that included business rules, anomaly detection, and social network analysis.  It provided the bureau with the ability to flag those anomalies using their existing data infrastructure and fraud alert output from those other state agencies.

With the tools in place to trigger those red flags, the agency immediately began recovering lost premiums, prosecuting offenders, and ultimately adding much needed revenue to the state coffers.

Fraudsters who choose to commit financial crimes are always coming up with new scams. Those of us committed to delivering true technology innovations through data sharing are starting to put a real dent in their chosen profession, though.

Maybe they can tune pianos instead. Do they need a building permit for that?

http://www.workerscompensation.com/compnewsnetwork/mobile/news/17511-investigation-leads-to-conviction-of-ca-business-owner-for-insurance-fraud.htmlgus

Posted by Douglas G. Wood. Click on ABOUT for more information and follow Financial Crimes Weekly on Twitter @FightFinCrime

SEC taking stock of analytics (and a cool use case for stock exchanges)

Image Posted by Douglas Wood, Editor.

I read with interest today an article about the SEC’s use of analytics in the ongoing fight against financial crimes. The link to that article is below. It reminded me of some work I once did with a major stock exchange around insider trading.

As a passionate anti-fraud technologist, I was thrilled with the challenge of helping the stock exchange better recognize cases of illegal insider trading. The results of the work we did was pretty cool.

The stock exchange – as do all exchanges – had a great deal of data at their disposal. They knew, for example, the names of each and every ‘insider’ within every company listed on their exchange. Insiders include senior executives, board members, legal counsel, auditors, and so on.  Basically, everyone who knew – or ought to have known – about an upcoming event that would likely cause a significant change in stock price.

They also knew, of course, the identity of investors who traded profitably prior to the public release of that information. The problem was exposing the hidden relationships that might exist between Insiders and investors.

Here is an actual example… Joe Blow was an associate partner at the independent accounting firm responsible for auditing the quarterly financial results of publicly traded Company A. By definition, Joe is an insider. He knows Company A’s financials. Jane Doe dumped her entire position in Company A mere days ahead of what turned out to be very poor results. The stock plummeted, and Jane was saved from significant losses.  She was seemingly a complete outsider. So, did she somehow know Joe Blow (or any other insider)? Or was she just one lucky gal.

Using link analysis, crime mapping, and behavioral analytics, we set about the challenge of finding out. Here’s what the analytics exposed:

Joe Blow, the insider by way of being employed at Company A’s auditing firm, shared an address with… oh, let’s call him “Rich Quick”. Rich held no positions with Company A whatsoever.  He did, however, own a pet food store with a lovely young lady.  Can you guess her name?  Yep.. Jane Doe. So, the analytics exposed that Company A had an insider relationship with Joe Blow. Joe lived with Rich Quick. Rich owned a business with Jane Doe. Coincidence? Not likely.

Without the ability to draw out hidden links between individuals and organizations, this case may never have been discovered.  It’s like Six Degrees of Kevin Bacon, only with much higher stakes. All of the suspects were investigated and prosecuted.

(Note: All the names in this example are fictitious, but the case is not. If your name happens to be Jane Doe, Joe Blow, Rich Quick… or if you work for an organization called Company A, rest assured that I’m not talking about you.)

Here is the link to the SEC article.  http://fcw.com/articles/2013/09/18/sec-taps-analytics-to-predict-risk.aspx?s=fcwdaily_190913 .

Prayers, Caregivers, and Breaking Bad – Selected Financial Crimes Snapshot 9/18/2013

Posted by Douglas Wood, Editor.  http://www.linkedin.com/in/dougwood

Does KYC mean Know Your Caregiver?

http://onlineathens.com/breaking-news/2013-09-18/savannah-woman-sentenced-51-months-federal-prison-embezzling-71k-elderly

Another great example of the need for systematic 314(b) programs?

http://www.chicagotribune.com/news/local/suburbs/joliet_romeoville/ct-tl-0926-sw-joliet-financial-crime-20130918,0,464668.story

Breaking Bad?  Financial Crimes Investigator indicted for fraud.

http://www.timesofisrael.com/senior-financial-crimes-investigator-indicted-for-fraud-theft/

Holy Fraud Scheme!  Better say their prayers.

http://greece.greekreporter.com/2013/09/16/sdoe-reveals-monastery-fraud/

Posted by Douglas G. Wood. Click on ABOUT for more information.