Library: Shift Technology Fraud Insights

December 2020 featured report:

Shift Technologies’ latest fraud insights report covers the fraud, waste and abuse (FWA) trends impacting the global healthcare payer market.

AI and ML can identify patterns and help combat fraud  

As a risk, cybersecurity has shot up the corporate agenda in recent years. The number of attacks have increased, as has the size of disruption and the losses.

But fraud is not isolated to cyber attacks and the actions of online criminals. A considerable amount is perpetrated through more traditional channels and against the insurance industry.

There’s a lot of it about

The Shift Technologies report from November 2020 indicates that FWA costs insurers and payers more than $600 billion globally (€500 billion).

Some trends are country specific. But there are some trends that are not confined to specific markets. Shift asserts that by identifying these scams can will put them on the insurance industry’s radar so they can close the loop on the fraud.

Eye on the prize

Most of the waste in the health care payer system is not attributable to fraud. But it is significant and prevents money being spent where it is needed. And it fraud in the healthcare market is not confined to consumers trying to extract maximum value from their policies. Providers and networks are at it, too.

The first case study covers a scam perpetrated by French opticians during the first COVID-19 lockdown of 2020. Optical health has the highest volume of claims and payouts of any line of insurance, says the report.

With most outlets closed due to lockdown in France, with a few open for urgent or emergency cases, the number of claims should fall. While the claims volume dropped noticeably, between March 17 May 11, the potential number of fraudulent claims identified rocketed. On some days, the detection rate was above 50%, adding up to potential losses in excess of €300,000.

General abuses

The report doesn’t indicate the typical baseline fraud under normal market conditions. But it certainly suggests a considerable amount of system abuse.

It’s not only opticians, either, says the report. Other providers are colluding to maximise the amounts spent on patient claims. In some cases, Shift has identified providers sending patients to each other for unnecessary services.

These includes examples of networks where general practitioners agree to prescribe unnecessary or increased amounts of medication, which are then dispensed by participating pharmacies.

In some cases, this was straightforward fraud. Some of these pharmacies provided fake invoices for patients who had never had the prescription at all.

There were also examples of GPs being rewarded for sending many patients to the same physiotherapist.

Room for specialists

Shift also found another major network, covering orthopedists ear, nose and throat specialists, gynaecologists, cardiologists and ophthalmologists, who have referred clients to one other, or forged claims related to patients they have never seen.

These fraud patterns are difficult to prove, but making providers aware that they can be identified offers a strong deterrent for the future.

International health policies – long a source of abuse – and the increasing incidence of health ‘tourism’ are also identified as areas that require greater vigilance.

A fresh pair of eyes

In order to turn the tide against fraudsters, artificial intelligence (AI) and machine language (ML) is needed to gain insights from unstructured data across many different languages, says the report.

In order to identify high risk providers, members or groups, this technology needs to be used on data outside of claims, which could include news reports, social media, etc.

There is a trend for health plan members to look on their benefits as a consumable. Those aware of their entitlements will max out their policy before the end of the year. In some cases, the network encourages the patient to take advantage of these benefits.

Shift has identified cultural differences to this form of abuse. Eyeglasses is the focus of abuse in France, traditional Chinese medicine in Hong Kong or Singapore and physiotherapy treatment in Canada, Singapore and Hong Kong.

Subrogation, subrogation, subrogation

Very little subrogation – claiming back costs – is done within insurance and far too little in health care and disability, says the report. It is most common in automobile insurance, workers compensation, public liability insurance, or from product recalls.

Maximising the opportunity for subrogation would greatly help, but the health payers must be aware these opportunities exist. However, the cause of an accident or illness may not be known at time of treatment and the payer doesn’t often get a chance to interact with the insured to understand the nature of the injury or illness.

Some payers are looking to AI and ML to identify claims that are likely to be the responsibility of a third party.

ML algorithms based on structured data, eg medical history, addresses, treatments, etc as well as unstructured data in the form of accident reports, phone call notes or practitioner notes can – and should – be used to identify potential subrogation cases, says the report.

Without a link between underwriting dealing with contract renewals and the team handling claims, it is difficult for these patterns to be identified. Which is where AI and ML tools can plug the gaps and turn off the FWA tap.

InsurTech may save us

That FWA is so apparently widespread and not confined to markets in less developed nations where controls may be less stringent must be a concern.

There is a major push for health records to be digitised, but this may not shut down all the opportunities for abuses from within the system.

Developing tech that can interrogate the myriad decisions involved in health claims to identify patterns of concern will reduce frauds and consequently, losses.

But the consumer is the biggest winner. Claims are always a point of friction for patients, but their experience will be greatly improved and funds will available in the right place at the right time.

For more, see the full report.

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