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Big Data Takes on Benefits Fraud
Data analysis is starting to make a dent in many benefits fraud schemes

In the world of benefits fraud, there are big fish and little fish. A lot of the big fish do get caught – or at least shut down – but what usually comes as a very nasty surprise to the little fish, who might have thought submitting one false claim was a small, victimless crime, is that they end up getting pretty thoroughly fried in the end.

How do people defrauding benefits get caught nowadays? It used to be that the only way anyone got caught was if there was a whistle-blower or a major slip-up of some kind. But not so much anymore. Now insurers can spot fraud the same way that Facebook and Google know your shoe size and send you ads for athletic footwear just when you’re thinking of taking up running again. But more on that later.

Sun Life Financial, in a very interesting paper on the topic, reports that 87% of benefits fraud comes from service provider collusion schemes of various types. What that means is that the bulk of the cost of fraud comes from organized schemes run by big-fish criminals to rope in little-fish employees with benefits plans to submit fraudulent claims.

According to the RBC Insurance fraud site, there are basically three types of fraud.

  • Plan member fraud – such as when an employee works off the books somewhere else while on disability;
  • Provider fraud – such as when a dentist performs a procedure not covered by your plan, but bills for something that is covered, or simply bills your plan for services that were not provided;
  • Plan-member and provider fraud – such as when an optical store sells you expensive designer sunglasses, but gives you a receipt for prescription glasses covered by your plan.

A lot of that member-provider fraud, by the way, is more-or-less “sold” to the patient by the health care provider, who passes it off as a minor technicality to help you out, or because “you’re entitled” or “you’ve got room in your plan.”

At the top of the fraud food chain, there are the out-and-out criminal schemes designed for the sole purpose of defrauding benefits plans. You read about them in the news – such as when the Toronto Transit Commission (TTC) recently parted company with 223 employees after such a scheme came to light. Most were fired, some allowed to resign, a few forced to take retirement. Many are facing criminal charges.

In that scheme, a provider of orthotic supplies such as compression stockings and sleeves, gave the employees fraudulent receipts and split the benefits payouts with them.

That TTC case first made news in 2014 after an employee called a tip line, and reports from honest people will always be important, but data analysis – the “big data” we hear so much about – is increasingly being applied by insurers to spot suspicious activity.

An insurance company with millions of claims can’t possibly review every single one – and probably wouldn’t spot anything out of the ordinary with most fraudulent claims anyway. But big data is not about spotting one fraudulent claim: it’s about spotting the very subtle patterns that identify the health care providers, the clinics and the workplaces that break the rules.

It may be a clinic that appears to be treating a higher number of patients with a certain condition than other similar clinics. Or a clinic with an oddly different average patient profile. Or a physician writing a disproportionate number of a certain kind of prescription. Or a workplace where employees appear to have an unusual number of similar claims. The permutations are almost endless and, unfortunately for the big-fish fraud artists, data analysis can spot most of them.

Of course, a statistical anomaly doesn’t automatically mean fraud. But it can certainly mean that investigators will take a closer look.

And when they do take that close look, all the little-fish plan members who went along with false or inaccurate or exaggerated claims will suddenly have some explaining to do.

Being caught up in fraud can be very serious and traumatic – one day, it’s “Oh, I don’t pay any attention to the paperwork,” or “Woo-hoo, I get a free pair of glasses,” and the next day it’s trying to explain why you shouldn’t be fired for benefits fraud.

Plan members can do a great deal to prevent fraud, protect the integrity of their benefits plans – and avoid becoming the little fish who end up being swept up in the net of benefits fraud investigations.

So here are some things you can do from now on.

  • Read up on the details of your plan. You are responsible, and you have to know exactly what you are and are not entitled to.
  • Keep your plan information, access to online systems, user names and PIN numbers as secure as you would keep our online banking information.
  • If a service provider offers to cut corners on your plan’s rules and eligibilities, walk away – and report the offer to your benefits administrator.
  • Take the paperwork seriously. Look over the claims documents carefully and make sure the services reported are what you actually received, and that they are actually covered by your plan.
  • Check your own online claims history to make sure nothing appears that you didn’t sign off on.
  • Do not sign off on blank claims forms.
  • Make sure that you deal only with legitimate health care providers with all the current and proper credentials.
  • If possible, submit your own claims online.
  • Carefully review all receipts and explanations of services provided.

It’s probably fair to say that high-profile cases such as the massive TTC fraud are changing the way insurers are looking at fraud. Part of the reason is that the software tools to spot problems is rapidly becoming available throughout the insurance world, and another part of the equation is that plan sponsors are holding those insurers responsible for “due diligence” in rooting out the costs associated with fraud.

If there is a topic that you would like me to write about, please email me at bill@penmore.com.

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