B2B Payments

Navigating Workers' Comp In An Unprecedented Market

The continuing boom of InsurTech innovation is a reflection of just how vast the opportunity is for technologies like machine learning (ML) to disrupt an industry that has relied on legacy processes for so long. Areas of commercial insurance like workers' compensation have been a necessity for decades, yet it's only recently that sophisticated data analytics tools have optimized workflows and financials for employers, employees and insurance companies alike.

The value of ML exists in its ability to quickly analyze troves of historical data to assess a situation and provide actionable insights into the best course of action — a valuable tool for an insurance adjuster and claims teams that need to understand everything from which healthcare providers might be best equipped for a case to whether the claim is valid at all.

But when an unprecedented social and economic event like COVID-19 comes around, there simply is no historical data upon which analytics technologies can rely to determine the best course of action for workers' comp insurance claims adjusters.

In a recent conversation with PYMNTS, CLARA analytics CEO Gary Hagmueller spoke about the early signs of disruption stemming from the pandemic, and why machine learning is more important than ever for the commercial insurance industry to embrace as part of its ongoing digital transformation journey.

Tackling Unprecedented Events

The value proposition of machine learning for insurance claims teams is significant, explained Hagmueller. While humans may be able to analyze data from their previous claims to understand the best course of action, automated technology can quickly collect information from similar past claims across other insurance companies and employers to provide the most accurate insight. With as much as 10 years of historical data to draw upon, ML tools can not only enable greater accuracy, but ensure speed.

The age and gender of the claimant, previous medical conditions, location and other metrics all combine with historical data about past cases with similar claimants and scenarios to enable insurance adjusters to quickly identify any anomalies that could otherwise lead to lawsuits or fraudulent claims if not detected quickly enough.

The pandemic has introduced many anomalies into the workers' compensation insurance field, however, and while machine learning is particularly valuable for its use of historical data, Hagmueller noted that the technology is agile enough to learn quickly and build upon what data does exist to help insurance companies navigate the often uncertain road ahead.

"Insurance carriers are prepared for a variety of new claims," he said. "There are a lot of different facets of what is going on, and machine learning is able to react to those things much more quickly than humans are going to."

Employees working from home who get hurt on the job, or even professionals that may be infected with coronavirus, introduce unfamiliar territory to the claims process. Machine learning means insurance companies don't have to retrain existing teams to respond to new claim scenarios arising out of the pandemic, with data analytics wielding market-wide data — not just information within a single employer or single insurance company — to enable more robust insight into how carriers can best respond.

Ultimately, this means insurance companies and employers can save money, and employees can get back to work safely and more quickly.

Reacting To Today, Preparing For Tomorrow

Automated data analytics can be a useful tool for insurance adjusters, but the unprecedented nature of the current market climate means there will undoubtedly be disruption in the industry. According to Hagmueller, insurance companies are bracing for a cash flow slowdown — the result of a reduced workforce — as well as a few patterns that tend to emerge during times of an economic downturn.

That may include the reopening of old claims, he said, as well as the filing of new claims that may ultimately be fraudulent: more employees may attempt to file a claim out of fear and in search of a secure source of money, and with work-from-home mandates, many of these alleged injuries may occur without anyone else there to witness the event.

Again, artificial intelligence and ML tools are more equipped at detecting anomalies that could signal a potential concern. An employee with a legitimate injury will have medical records that look very different than an employee without one, noted Hagmueller.

While some trends are to be expected, the pandemic will undoubtedly introduce new and unfamiliar claims and litigation, and insurance companies and employers will be forced to navigate uncertain waters. Automated analytics technology is important to steering the ship, and as Hagmueller said, many insurance companies are accelerating their adoption of such technologies in an effort to get ahead of any issues that may arise as the data begins to trickle in.

While it's still too early to tell exactly how the pandemic will impact the workers' comp space and broader commercial insurance market, it will certainly introduce long-lasting changes to the industry as data analytics tools become the norm.

"We need to start to think about how to get adjustors working with a different reality," said Hagmueller. "Machine learning allows them to be more nimble, to address these things proactively — instead of the old-world ways things were done, of calling claimants every month or week. That just might not be enough anymore in an environment that's moving very quickly."

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