From this article, we learn that:
(1) Knowing how to handle a basketball isn’t proof of intelligence, financial expertise or morals, and
(2) Having a medical degree isn’t proof of having common sense.
Why would anyone throw away a career over a few bucks? Massive risk for paltry rewards. Really.
There are 19 people facing jail time over trying to skim an NBA healthcare fund out of roughly $5,000,000. Net of cost and if divided evenly, each participate would net a little over $200,000 from the scheme. That would feed a cocaine or gambling habit for how long?
One is a doctor, one is a dentist, and one is an assistant coach with the Utah Jazz and a former player, while the rest either play or are retired from playing basketball. Of course, by the time this is done, they will be out of work.
The root of this case is insurance fraud: invoicing and filing insurance claims for medical services that were never required or delivered. How stupid is that?
The insurance industry isn’t perfect, and like credit card issuers and others, if the amount of money involved is small enough, they’re not really going to care. However, $5 million isn’t small. By consistently hitting the same insurance fund, eventually someone was bound to notice.
Two things the insurance industry does well are documentation (in the old days, “paper trails”) and data analysis. The latter basically focuses on unusual patterns of transactions. Once a good data sleuth sees an unusual pattern, he or she wants to know why it exists. That’s where things can get interesting. The copious documentation ensures that there is always lots of fodder to feed the pattern detection software. Advances in AI have sharpened that software. Together, that makes a formidable opponent.
Of course, the more people involved in a scheme, the more likely it is that one of them will do or say something stupid and blow the cover. As Ben Franklin famously stated, “three people can keep a secret if two of them are dead.”
So we have 19 people up on charges, lives potentially ruined, and for what? Enough money for a few months in Monte Carlo? How does that make any sense at all?
Reblogged this on Ned Hamson's Second Line View of the News.
My father was an internal auditor for Prudential Insurance – before they turned it over to data analysis/analysts. AI is good but well trained and experienced auditors can read people and the paper trail.
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That is absolutely true. AI’s strength is to “comb the ocean” to see what looks odd. With the vast number of policies, that’s a huge job for human eyes. Once AI has done the initial sifting, then the audit team has to sort it out. Data crunching can tell you something is out of norm, but not why. (Although some companies try to make it do more than it really can.)