Looking toward 2022, health insurers are going to be wrestling with all the ways COVID has transformed the health insurance industry and what it means for coverage, pricing and patient care for years to come. 

Some positive things have come from the response to the pandemic — the rise of telemedicine and a blunted cold and flu season both come to mind. But, more than anything, the pandemic has brought uncertainty that is going to take months, if not years, to completely work through, including within the health insurance industry. 

Telehealth

Before COVID-19, telehealth made up a sleepy corner of the health care delivery system. 

Held back by uneven reimbursement schedules, telehealth served as a niche solution for just a few healthcare problems. 

But as social distancing and government-imposed lockdowns swept the country, many people gave telehealth a fresh look. Perhaps more importantly, federal regulators changed how Medicare and Medicaid reimbursed telehealth appointments within their programs. 

A recent assessment by McKinsey showed a 38-fold increase of telehealth appointments during the core of the pandemic. And it makes sense. Patients were looking for ways to stay away from other people, but they still needed healthcare. Seeing a doctor from the comfort of their own couch was a great solution. 

But many patients also embraced the new healthcare delivery for other reasons. People with transportation challenges flocked to telemedicine as a way to avoid the commute to the doctor, and parents used telemedicine to help solve child care dilemmas. Plus, telemedicine was a convenient way for professionals to see a doctor from their cubicle during their lunch break. 

So, what started as a pandemic workaround looks like it may be here to stay. 

The question mark when it comes to telemedicine is whether the more generous reimbursements offered to providers during the pandemic will continue into the future. If insurers or federal regulators change back reimbursement schedules, many providers may pull back on virtual appointments, even if their patients are still asking for them. 

See also: On COVID Vaccine: Do the Math

Mental Health

One of the areas of healthcare that has thrived during the pandemic, including via telemedicine, is mental health. Therapy appointments don’t rely on physical evaluations, so they seem to be a natural for telemedicine technology. 

That still doesn’t mean that every patient who was looking for mental health services could find it, even though it is covered by all Affordable Care Act-compliant plans. An October 2021 report published on insurancequotes.com cited data from the National Alliance on Mental Health, which found that as many as 55% of psychiatrists are not accepting new patients, and that a third of people who want to find a mental health provider say they cannot find someone who would accept their insurance.

The lack of availability is bad news. According to the Kaiser Family Foundation, four in 10 adults reported anxiety or depression during the pandemic, up from one in 10 before. 36% reported having difficulty sleeping, 32% reported changes in eating patterns and 12% reported an increase in alcohol or substance use. 

Some industry analysts hope that innovations in telemedicine may continue to ease the bottleneck, but a shortage of mental health providers is likely to continue into the foreseeable future.

Pricing

COVID-19 has thrown a major wrench into the normally well-oiled policy pricing system. Because premiums are priced according to past years’ experience periods, the past two years pose a problem. 

For one, COVID-19 disrupted normal care patterns. Early in the pandemic, people avoided routine care, and many of those who did contract the virus faced astronomical ICU costs. Pandemic surges also forced some overburdened hospitals to delay elective procedures. 

In addition, most insurers have now stopped waiving patient shares of COVID treatment, and there is very little in the way of reliable pricing from the recent past to use to set future premiums. 

Other major challenges include the uncertainty about whether there will be future COVID waves, whether a relaxation of masking and social distancing will cause cold and flu cases to again surge and how two years’ worth of deferred or avoided care could affect morbidity when it comes to chronic conditions. 

With all of that, insurers run the twin risk of either over- or undercharging premiums for 2022. 

Political influences

Discussions of health policy and COVID cannot be had in a political vacuum. Whether the conversation is about vaccine hesitancy or employer vaccine mandates, tempers flare. 

The biggest question for health insurance providers is how the courts are going to handle so-called COVID surcharges. While the Affordable Care Act mandates that different premiums cannot be charged to similar people based on their health history, many employers are charging unvaccinated employees surcharges on their health costs. Employers are taking different routes, ranging from wellness programs to EEOC-endorsed incentive programs, but, no matter the legal justification, the issue is almost certain to land in federal court. 

Navigating the political waters is going to be a challenge for every health insurer for the year to come. 

See also: Mental Health in Post-COVID Era

Conclusion

COVID-19 will have a lasting impact on the healthcare industry. Navigating pricing, the future of telehealth and the political uncertainty is going to take a careful hand. 

But, for companies that respond deftly, 2022 also has the potential to offer a cautious return to normalcy, even amid massive uncertainty. 

The P&C industry has been on an automation path for many years. When the pandemic hit, it became a catalyst for accelerating automation and digital transformation. Straight-through processing, self-service portals, virtual inspections and digital payments are just a few of the areas that insurers put a sharper focus on. But automating tasks and workflows does not mean that machines will take over and leave industry professionals out in the cold. In fact, the opposite may be true. I believe that a case can be made that automation initiatives will increase the need for skilled professionals with deep industry domain knowledge.

All the automation occurring is good for the industry. And anyone who knows me knows that I am certainly not a Luddite or anti-technology. However, I believe there is one dimension of tech progress in the P&C industry that is being overlooked – skilled individuals. I’ve written extensively about how automation and AI will elevate the role of industry professionals and how relationships are still vital in the industry, especially in commercial lines. But in this blog, I turn my attention to another implication of task automation – the need to manage it. Several examples expose the challenges.

• Bots: Chatbots to automate interactions, robotic process automation to automate tasks and voice bots to respond to phone calls all take the burden of simple, repeatable tasks away from humans and speed up the process. Bots of these types are sweeping through the industry, and some insurers have deployed thousands. On balance, this is a good thing. Companies are realizing ROI on their investments and improving process flows. But many are now experiencing maintenance headaches. How should the inventory of thousands of bots be managed? What happens when a bot breaks? How are bots updated to comply with the latest regulations? These are important questions that must be addressed.  
• APIs: It’s an API world. You’ve probably heard that phrase. Even CEOs talk about APIs (application programming interfaces), and, again, it’s a great thing. APIs standardize and improve connections between systems and make integrations faster and easier. After all, integrations and data exchanges between systems have been some of the big challenges for the industry for a long time. But once again, as the number of APIs expands, there emerges a need to manage the hundreds or even thousands of APIs that might be relevant for a given insurer.
• Models: Rules-based or AI-based models are widespread in P&C, and their number and the variety of use cases continue to expand. Done well, they are helping improve product design, risk selection, pricing, profitability, claims processing and many other parts of the business. Model management is now becoming a discipline in its own right, and there is a need for strategy, governance and hands-on management of the models. And, in the case of models, the most important human contributions are in designing the models to address specific business opportunities, interpreting the models and then taking action.

Over all of this, layer the complexities of the insurance business, the trend toward more specialization and the evolving risk landscape: The picture gets even more complicated. The state-by-state regulation regime in the U.S., coupled with the variations by line, introduce multiple dimensions that must be managed for new tech solutions in automation. As customer risks become more complex (as in middle-market and large commercial accounts, specialty lines and workers’ comp), the intricacies of the business create challenges.

See also: Insurers Turn to Automation

Automation and leveraging AI for insights are good for the P&C insurance industry. But there will still be a need for industry experts who understand how to execute tasks that comply with evolving regulations, who can exercise judgment based on experience and who can manage all the automation activities. Some of that automation management will demand IT experts, but much of it requires an understanding of how business is conducted, the details of different customer segments and insurance products and the requirements imposed by the many regulatory bodies involved.

Will there be increasing levels of straight-through processing, bots and other automation in P&C? Of course! But does this mean that the machines will be in control? I emphatically say no! People and their experience and expertise in the industry will remain at the heart of the business.

In July, I wrote an article that criticized the newly authorized Alzheimer’s drug Aduhelm. Six months later, the market response is heartening and, in my opinion, a case study in what it will take to fix the way that we pay for healthcare in America. 

A review of the problem

The FDA approved the first new drug to treat Alzheimer’s in June. Of 11 scientists who reviewed the research and science behind the new treatment for the FDA, 10 voted against approval, and one was undecided. The FDA approved Aduhelm despite the lack of evidence that it either cures or slows the progression of the Alzheimer’s and has given the company nine years to conduct a confirmatory trial. Three of the scientists resigned as a result. The head of the FDA also took the very unusual step of asking for an investigation into unusual/informal contacts between the manufacturer and people at the FDA.

The drug price is set at a whopping $56,000 per year, and the real price tag is more like $100,000 when you include the cost of performing the infusion in a provider’s office, testing to monitor for brain bleeds, etc. With 6 million Alzheimer’s patients in America today, having just one in six get a prescription would drive costs of around $100 billion into the system. Total outpatient Medicare drug spending with pharmacy prescriptions was $136 billion for 2019.

A review of the last six months

Biogen and other analysts projected sales of $103 million this year, about $1 billion in 2022 and $5 billion-plus in 2023. However, the market has responded in a very encouraging way. Sales have just totaled $2 million thus far.

What happened? The Veterans Administration, several Blue Cross Blue Shield companies and most notably Medicare are not yet paying for the treatment. Highly respected medical institutions like Cleveland Clinic and NY City’s Mount Sinai have also chosen not to administer the drug. So have many well-managed, large employer health plans. All are waiting for real evidence the drug is effective in either slowing the development of or in curing Alzheimer’s disease. 

See also: How Synthetic Data Aids in Healthcare

How we will make real progress

The free market is the only viable solution -- if we can get to one in the way that we pay for healthcare.

I am often asked when we will see real progress in our insurance payment model. I typically laugh and say, “As soon as lobbying is no longer effective.” But that is not the end of the story. I more seriously share that we are seeing the problem get solved one employer at a time (another way of saying it will be solved by the free market). When employers build a health plan with a consultant that provides transparency around the actual cost of care and then build their plan to reward good consumption, it is amazing how quickly they can get to a place, where costs go down and quality goes up. 

For change that will affect the system more broadly, we need government to ensure that we have rules in place that require transparency. Until that happens, we will be stuck handling the problem one employer at a time.

Robotic process automation (RPA) can be used to automate manual, high-volume and repetitive data tasks — especially those where human touch does not add value. Think of all the needlessly manual data entry involved in your underwriting and claims processes. RPA can help automate those tasks to mitigate the risk of human error and return your staff’s focus to high-value work while increasing efficiency and speeds process completion.

As part of a larger content services strategy, RPA can be invaluable in solving business challenges by effectively managing digital workflows, improving process efficiency and accuracy, reducing operational costs and meeting growing IT needs.

Robotic process automation has been tried and tested, and it can deliver a quick return on investment with relatively little effort. But there is really no such thing as a one-size-fits-all RPA solution. How can you define the right strategy and find the most compatible RPA provider for your organization? What considerations should you take into account?

The following five tips can get you started on targeting the right solution — and vendor — for you:

1. Define your needs: Piecemeal or end-to-end RPA software provider?

Before you can start evaluating solutions and vendors, you need to understand the extent to which you can automate your business processes. Are there currently just a few high-priority tasks, or are you planning to automate more processes across business units in the future? Will a standard solution suffice, or do you need a tailor-made solution?

If your organization has relatively straightforward automation needs, implementing an off-the-shelf RPA tool can be the right choice. The same is true for upscaling simple processes.

When it comes to addressing larger and more complex processes – like underwriting and claims – you’ll likely want a more robust RPA solution with a comprehensive suite of tools, from process analysis to bot management. Additionally, that solution needs to be paired with a vendor that has a holistic automation approach and history of helping insurance organizations transform their processes. 

If your organization is looking to implement in-house automation in the future, it is important that your RPA provider can equip you with intuitive software so you can automate processes independently, preferably with a simplified deployment structure without extensive coding and customization to reduce reliance on IT.

2. Start small, think big: Interpret scalability for the use of bots

Starting your automation journey can be a relatively small and inexpensive endeavor, but to truly gain a competitive edge you need to think about scaling options well in advance. This is where a feasibility check would be wise. Ask potential RPA providers: What are the success stories when it comes to scalability (i.e., is it feasible to substantially increase the number of bots)?

Expanding RPA to more processes across your organization can help you leverage economies of scale and reap the holistic potential of RPA. However, not all RPA tools make this easy to do. It is essential for your organization to have the ability to easily scale and centrally manage your RPA solution in-house.

See also: What’s Beyond Robotic Process Automation

3. Extending RPA: Check integration options and complementary capabilities

Robotic process automation technologies don’t work in a vacuum. Most RPA deployments involve other systems from the start and expand to other departments and processes over time. Therefore, when selecting an RPA platform, it is important to consider its capabilities for integrating with your other systems, both those in the initial scope and those likely to be in-scope soon.

Additionally, you can often enhance the value of RPA with complementary capabilities. Intelligent automation technologies like advanced data capture or customer communications management (CCM) can not only take your process automation to the next level but can also dramatically improve user and customer experiences. To increase your chance of automation success, check the capabilities of available RPA software extensions and align them with your requirements and objectives.

4. Don’t overlook data security and compliance

By reducing human contact with your customers’ sensitive information, robotic process automation actually helps your organization reduce security risks and improve compliance with new regulations like General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). However, for this to happen, the RPA software itself needs to be secure.

Look for a vendor that adheres to a stringent secure development lifecycle methodology, resulting in hardened software with fewer vulnerabilities. Some vendors also invest in outside security audits and certifications of their products and may provide specialized solutions and best practices that help with your specific industry regulations.

5. Embrace the future of process automation

Self-learning bots are the future of RPA. The integration of artificial intelligence (AI), especially machine learning, ensures that your system learns from previous decisions, so it can handle rule-based processes independently.

See also: Here Comes Robotic Process Automation

A vendor that integrates intelligent technologies such as AI and machine learning can meet a wider range of business needs and minimize the need for bot maintenance.

Insurance, like most other industries, is loaded with tasks and processes that are unique to each organization. Robotic process automation can provide the flexible toolset you need to meet your specific needs. The key is determining those needs first.

As part of this month’s ITL Focus on telematics, we spoke with Dave Wechsler, vice president of growth initiatives at Hippo Insurance, on how far telematics has come—and where it goes from here.

ITL:

Given that you’ve been involved with telematics a lot longer than I have, could you start us out with a bit of history, to explain how we got to where we are today?

Wechsler:

There’s a huge opportunity for the insurance industry to move toward proactively caring for customers, helping beyond just indemnification. The insurance application of telematics has become integral in bringing us closer to creating a more protected future. For example, here at Hippo, we partner with our customers to help them avoid a loss in the first place by offering Smart Home devices alongside new policies.

The evolution of auto telematics in insurance is a great example of what will happen across the industry. Until recently, there was limited adoption by insurance companies due to price point, limited technology and concerns over consumer adoption. In the early days, auto telematics systems were expensive black boxes installed in an auto body shop for thousands of dollars. But with time, the technology transformed into a device that a driver could buy in a store and self-install in their car. Over that period, wireless networks significantly improved and became less expensive, which allowed for real-time data transfer. Ultimately, consumers became more comfortable with datasets coming from devices that they own, leading to the rise of usage-based, or “pay-per-mile,” insurance.

Just like with any other technology, when the adoption curve accelerates, prices drop and features improve. And as telematics technology improved, cell phone manufacturers began to install it into phones. Suddenly, a mobile phone was a powerful substitute to the installed equipment, and a no-cost app could be downloaded to monitor driving and enroll in a safe driver program.

ITL:

It feels like we’ve moved a fair ways up the learning curve, too, in terms of what people value. I was struck, speaking at a telematics conference a few years ago, that insurers were just learning that there were real issues with human behavior that they hadn't understood. Customers, for instance, were more inclined to value something like free roadside service free than they were a 5% discount. The roadside assistance actually cost the insurers less than the discounts they were providing – so insurers were paying more to give customers something they valued less.

Wechsler:

Leading with a discount is not the only way to attract customers - it’s the protection proposition that I think the industry needs to embrace. Telematics should be a part of a productive partnership that helps the customer decrease their anxiety and ensures they are aware that we are on their side. These are the right benefits for participation when our goals are aligned with the customer.

From a regulatory perspective, we need to be open-minded. Regulators are there to ensure that consumers are benefiting. So, start off by saying, “Well, here are other benefits that we can bring into the market that are received better by consumers and, in fact, give them more protection than a small discount on the policy.” I think there is a lot of openness right now as to what’s the best approach as we all learn together.

ITL:

From your current role with Hippo, you can see the uses of telematics in insurance expanding beyond cars, in particular into homes. How do you frame that opportunity?

Wechsler:

A few years ago, only very basic sensors were available for the home. And these products were both expensive and not particularly effective. Like auto telematics, these devices have matured, and prices have come down materially. We now have the potential for actual loss-avoidance at a feasible price point.

We have to understand that this is still new for the consumer. Realizing the full potential means enabling customers and educating them on where they can be protected and how they can protect themselves. It's about giving customers the tools - not only equipment but installation, professional monitoring or other services as needed. It's about understanding the power of sensory data to identify risks in the house and creating better technology to avoid loss.

We're seeing all these trends now accelerate, where the quality of the technology is much better, the price is much lower and the service offering to support telematics in the home is becoming self-evident. Most of all, customers are excited.

ITL:  

How close are we to being able to argue for wide deployment of sensors in homes on the grounds that the losses prevented will exceed the cost of deployment?

Wechsler:

Early systems were expensive, but prices are dropping and features are improving. Detecting water leaks with basic sensors is a good start, in my opinion. The automatic shutoff valves that these sensors can trigger used to cost thousands of dollars and required a plumber for installation. Today, you can find DIY home shutoff valves for as low as $150, and it’s doable for the homeowner to set one up themselves.

Insurance companies like Hippo can spur the market in terms of adoption by enabling and educating on the loss-avoidance benefits. Here at Hippo, we are focused on meeting the customer where they are, which is why we offer a variety of solutions, from self-monitored to professionally monitored smart systems. If you want a basic smart home system, great, we'd love to give you a range of sensors. If you want something very sophisticated, fantastic, you're an ideal customer for us as we aim to be a partner to our customers to protect their homes.

ITL:

I assume that, over time, a lot of safety features will be built into homes, as well, so there will be no need to retrofit.

Wechsler:

Our goal is to provide our customers with more proactive protection options. This includes looking at the structure and systems within the home itself. For instance, Lennar, one of the nation’s leading home builders, is installing a whole-home water shutoff water valve in every home that’s WiFi-enabled. These systems can work in partnership with our program at Hippo to reward customers with deeper discounts on their home insurance policy.

ITL:

How much of a help will the widespread adoption of 5G wireless be?

Wechsler:

It's almost impossible to imagine a home without connectivity at this point, and we're excited about the extra protection connected devices can provide. The biggest problem, in my opinion, is that most customers don't understand the impact of damage done from what can appear to be minor issues due to water leaks or small fires, until they dig into the situation themselves. You have to get the consumer to understand the benefits, which is our focus at Hippo.

Insurers can be the catalyst through discounts or through better services, whatever it might be. And a rising tide lifts all boats. Hippo is leading the industry in smart home integrations, but I hope to see the entire ecosystem improve so consumers can become aware that these devices protect their homes.

ITL:

To wind us up, I’ll ask you to blue sky things a bit. If you look out five or 10 years, what do you think the smart home could look like?

Wechsler:

We are on the cusp of an incredibly exciting time in the next chapter of smart home as it becomes more deeply married with home insurance products. What I’m most excited about in joining Hippo is that we’re trying to be a different kind of home insurance company. Through devices, data and services, we envision a more proactive future that challenges the traditional model and offers customers a new level of preventative care for their home.

ITL:

Thanks so much. This has been great.

Wechsler:

Thank you!

NOVEMBER 2021 FOCUS OF THE MONTH

Telematics

FROM THE EDITOR

In all my years covering all manner of technology, telematics may have caught me off-guard the most. When I first wrote about Progressive's auto telematics program, Snapshot, in 1998, it seemed like a slam dunk. Of course, it made sense to monitor how people drove and to price their insurance accordingly.

Or not.

It turns out that the devices didn't provide as much insight as expected -- was that a good hard brake, because someone did something stupid in front of you and you reacted quickly, or was that a bad hard brake because you were distracted and didn't see something you should have? I also underestimated how much people would be put off by even the simple process of installing a Snapshot device and how little people would respond to a discount in their premiums. 

I often tell people that my favorite line from my Silicon Valley days is, "Never confuse a clear view with a short distance" -- and I surely made that mistake with telematics. (I sometimes think I keep using that line as a reminder to myself to not make that mistake again.)

The good news is that things you can see clearly eventually come to pass, and that's happening with telematics. The analysis of driving is becoming more sophisticated. So are the sensors put into cars (which may now include cameras). Understanding of human behavior has progressed, and carriers are finding incentives that matter more than modest discounts. The inconvenience of installation has diminished, as many now use their cellphones as sensors rather than having to plug something into the car. 

Telematics have moved well beyond the car, too -- in particular, for insurance purposes, into the home. Sensors can now monitor for water leaks and other problems that can produce expensive losses and claims. 

As you'll see in the articles and the interview that follow, as part of this month's ITL Focus, we've come a long way since 1998, and there's a clear path forward. 

Not necessarily a short path, mind you, but a clear one that will deliver benefits to clients and to those insurers that figure out how best to help them. 

Cheers,

Paul Carroll, ITL’s Editor-in-Chief

---

---

INTERVIEW WITH DAVID WECHSLER OF HIPPO INSURANCE

As part of this month’s ITL Focus on telematics, we spoke with Dave Wechsler, vice president of growth initiatives at Hippo Insurance, on how far telematics has come—and where it goes from here.

“Telematics should be a part of a productive partnership that helps the customer decrease their anxiety and ensures they are aware that we are on their side.”

David Wechsler

---

WHAT TO READ

---

---

WHO TO KNOW

• 

• 

• 

• 

• 

• 

• 

• 

This summer brought a surge of natural disasters across the U.S. One in three Americans experienced a natural disaster this summer, according to The Washington Post. From wildfire smoke blanketing the Western skies throughout most of the summer to Hurricane Ida devastating the Gulf Coast to destructive flooding in the Northeast, no area of the country was entirely safe. And, according to the UN Climate Change report, the world will face extreme droughts, severe heat waves and catastrophic hurricanes for decades to come. 

When disasters strike, insurance companies can quickly become overwhelmed with calls and claims. This summer, the frequency and severity of natural disasters demonstrated the need for a distributed, scalable response team of knowledgeable and empathetic listeners. 

A Scalable Response to Hurricane Ida 

Hurricane Ida made a devastating impression in late August, reopening wounds left from Hurricane Katrina 16 years earlier. As the storm made landfall, more than one million people had no electricity, and the loss was insurmountable. 

In the days following the storm, residents began taking the toll of the damage and started calling their insurance companies. In this time of distress, they needed quick resolution and an empathetic ear on the other end of the line. 

At Liveops, a virtual contact center that provides customer care, we experienced the critical importance of having enough agents available in a time of great need. Our 27,000 agents, who can take calls for claims and assist insurance companies and their customers when disasters strike, responded to 14,000 claims just on Aug. 30 and 31. 89% of calls were answered in 20 seconds or less, providing customers a helping hand in the wake of a disaster. 

Providing Empathy and Peace of Mind

Living through and recuperating from a natural disaster can be stressful and traumatic. Without basic needs like power or running water, survivors of natural disasters are often entirely reliant on the help and generosity of others — including the agent processing a claim after a hurricane. 

Those recovering from a natural disaster don't need to experience long wait times, being placed on hold or even not connecting with an agent at your insurance company. Having them be able to make one phone call and reach an agent who demonstrates empathy and proficiency is invaluable. 

With the likelihood of natural disasters and the need for a 24/7 response team increasing, insurance companies will also need to consider what may happen if a natural disaster hits their headquarters or affects their workforce. If workers cannot come to work or offices become unfit for conducting business, a distributed, scalable workforce helps keep operations running smoothly. 

See also: 3 Keys to Leading a Team in a Crisis

The Unpredictability of Our World

Natural disasters aren’t the only circumstance in which a scalable response team is essential to processing an influx of claims. The last 18 months have demonstrated just how unpredictable the world can be and how the ability to adapt quickly is critical. When COVID-19 hit, for instance, the roads became eerily quiet, but people have started traveling again -- and car insurance claims volumes are skyrocketing. At Liveops, our call volume for our insurance clients has increased 134% year-over-year.

Insurance companies should thoroughly evaluate their response teams to assess their ability to respond to customer calls or even their own workforces’ ability to work when, not just if,  a disaster strikes.

2020 and 2021 taught us that the world is unpredictable. 2022 likely has surprises in store for us, too.

Keeping track of employees, an important function for corporate HR departments under normal circumstances, has been even more challenging during the COVID-19 pandemic. Eight in 10 employers say the pandemic taught them the importance of absence management, according to a recent Guardian study.  

Further, state laws around regulated leave can change, and federal regulations are highly complex. Complying with related state and federal leave programs is one of the greatest absence management-related challenges your customers’ HR teams will ever face.  

Managing absences, especially using spreadsheets, is hard in the best of times, but has been doubly challenging during the pandemic, with some employees working remotely and others returning to the office. It’s no wonder HR teams are overburdened.

The growing complexity has led employers to look to insurers for more integrated, turnkey solutions. It has also served as a catalyst for insurers to develop automated absence management systems. Employers want to be in compliance, have up-to-date customer data, reduce the cost and time for HR departments and see real-time employee absence patterns and trends. For their part, employees want better tools for monitoring their attendance and tracking vacation time and related benefits. 

The new generation of automated absence management systems can help employers stay in compliance and track employee absences by connecting to a greater digital ecosystem of HR management systems. These systems also have the advantage of easily integrating with federal and state regulations or third-party vendors that monitor and update regulations as they occur. By bringing all these systems together, insurers can make reporting and data analysis easier for HR teams.

But not all absence management systems are created equal. Ease-of-use should be a given, but the following features are important to ask about:  

Employees providing input

Automation lets your customers’ employees schedule their own absences or log sick days. Claims that don’t meet eligibility requirements can be auto-rejected without the involvement of your customers’ HR teams.

Knowing what to expect

An absence management system should provide additional information and avenues to next-stage claims management. For example, your customers should be able to create a rule that a certain type of absence indicates whether physical therapy is likely in store for that employee, or if an absence related to an accident can help trigger a related claim. 

The importance of centralized data to spot patterns

When all employee data is in one place, absence patterns are easy to identify. Maybe your customer has an employee who is absent every second Friday, or an entire team is requesting vacation time the same week. Absence management software can help uncover patterns with tracking and reporting.

See also: Designing a New Employee Experience

Integrating changing regulations

Absence management systems should have the capability to integrate with third-party vendors that manage changing regulations to remain fully compliant with all federal and state regulations related to absence, including FMLA, disability and ADA. They should also have the ability to integrate with internal compliance systems. This feature, which is driven by the need for technology based on application programming interfaces (APIs), is a game-changer for organizations that run across multiple states.

A link to HR/health systems 

When absence management software links to HR management systems and health management software, it’s easy to monitor all the functions together in a single, seamless ecosystem, which is the ultimate goal.

Managerial efficiency

Finally, absence management software should allow managers to access all leave requests in a central place, ensuring appropriate coverage and deadline management.

Giving your customers the ability to add data and analytics and communicate across digital platforms is critical. Absence management software can do just that – collecting, managing, analyzing and reporting on important data and giving HR teams the information they need to maintain compliance, increase efficiency and reduce costs simultaneously.

The vision of a metaverse laid out by Mark Zuckerberg last week is bonkers. Nutso on steroids. It won't be realized in my lifetime, yours or his, even if some of the wildest claims about longevity come true and we all live to be 150.

The vision is essentially a fever dream for gamers who'd love to immerse themselves in their online worlds and not have to worry about the messy details of physical existence, so it doesn't directly bear on the insurance industry. But there are still elements of it that could be dangerous to insurers if taken seriously.

The main problem is the underlying claim that the internet is about to morph into something very new -- and that we all need to start preparing. It won't, and we don't.

The story -- and there's always a story to these flawed technovisions that appear from time to time -- is that the version of the internet that appeared in public view in the 1990s was essentially a broadcast medium. Companies posted news, advertised their wares, etc., and people consumed that information in front of their computers. In the 2000s, Internet 2.0 arrived. It went beyond broadcast and became interactive. We didn't just consume what companies put in front of us. We interacted with companies and their products and with each other -- pioneering companies, Facebook among them, actually turned those interactions into their "product." So, here we are, a decade-plus later. That must mean the internet is ready for another leap forward, right? I mean, what has it done for us lately?

While the capabilities of the internet will continue to expand exponentially, the power will come from the explosion of information it will have at its disposal (including from billions of new sensors and hundreds of millions of additional cameras), from the increased speed and ubiquity of wireless communication. from the continued surge in computing power generally described as Moore's Law and from the ever-growing reach of artificial intelligence (including AI that makes the AI better--a mind-blowing proposition).

Those gains, while wildly powerful, won't lead to a multiverse for two main reasons: the technology and human nature.

The technology is actually the lesser of the problems, even though virtual reality -- the core piece -- is nowhere close to being ready as the entry point into a world where our primary existence is virtual. VR wasn't ready when it was the hot new thing 30 years ago. It wasn't ready when it staged a resurgence in the 2010s (when Facebook bought Oculus for $2 billion, in 2014). And it won't be ready any time soon. We humans have experienced the world in a certain way our whole lives, and we won't go into a virtual world until it gives us that same experience.

Even when the video gets far better than it is now -- people still often get motion sickness -- some things simply can't be simulated. You can only move so far while wearing VR goggles -- lest you trip or run into something in the real world. Some sensations, such as, say, bungee-jumping, can only be simulated so well even if your goggles tell you you're diving off a bridge. Textures and smells will be limited, too, as least for generations of the technology.

Other technologies that are just assumed in the Zuckerberg multiverse, including brain-computer connections, also have a long way to go before they could undergird a virtual world that more than hard-core gamers would want to live in. In the technology world, whenever anyone says that something is "only 10 years away," what they're really saying is that the claim might be science fiction -- and I don't know anyone who sees commercial possibilities for brain-computer connections even in a decade.

Human nature is the intractable problem. I think of a front-page story I wrote for the Wall Street Journal in the early 1990s about a prominent scientist who had written a book arguing that we'd soon be able to transfer our memories and consciousness into a robot -- at the small cost of the destruction of our physical brains and loss of our bodies. The article ran under this headline:

Good News: You

Can Live Forever;

Bad News: No Sex

In theory, Zuckerberg can argue that it's just as cool to dress up your avatar and send it to the top of the Eiffel Tower in the metaverse as it is to go there in person, but we all know that isn't true. Many things just can't be simulated.

Zuckerberg can do all the promotion he wants for the idea that a new version of the internet is in the offing and that it will become the core of our existence, but that's simply not the right way to think about what's coming. (In fact, as some have noted, the term "metaverse" comes from "Snow Crash," a 1992 sci-fi novel by Neal Stephenson, that is set in a dystopia.)

Even if we give Zuckerberg the benefit of the doubt and don't think his metaverse vision and the name change to Meta for Facebook are designed to distract from the company's many PR problems, he's falling into a trap that catches many smart technologists: He's lost touch with the real world.

As I detailed in this piece from early 2015 on a misconception by Google about the nature of the internet that isn't that far off from Zuckerberg's, many technologists have gotten so locked into their worlds that they lost track of key considerations in the one that really matters. But the fact that so many have been so wrong actually makes dealing with the metaverse easier -- we can see the pattern of error and avoid it.

There will, as always, be opportunities to participate in online worlds, including those that gamers spend so much time in now and that will continue to expand. The Biden campaign bought "yard signs" in a virtual world in 2020, and there will be opportunities for insurers to likewise at least advertise in virtual environments. But those virtual environments will be supplementary; they won't become the focus of our lives.

You already have enough on your plates as you try to, among many other things, figure out how to interact digitally with increasingly demanding customers. I assure you that you don't need to worry about shrinking your businesses to fit into Zuckerberg's metaverse, no matter how many awkward videos he produces that try to convince us otherwise.

Cheers,

Paul

As the adoption of artificial intelligence (AI) continues at pace across industries, there is increasing awareness of the risks it can pose. Recent high-profile examples have highlighted the risk of unjust bias regarding race and gender, such as those found in some law enforcement or recruitment algorithms. Other examples have highlighted the reputational risk from poorly communicated AI use cases, such as an online insurer’s recent claims of using facial emotion recognition to detect fraud. Perhaps most damagingly, AI models seem to have failed to meet expectations when it comes to mitigating one of humanity’s biggest challenges, the COVID-19 epidemic. 

Not surprisingly, regulators have become increasingly vocal. Earlier this year, the European Commission published a draft of its proposed AI law, which prohibits certain uses of AI and defines several other high-risk AI use cases. The Cyberspace Administration of China has just proposed far-reaching rules on the use of algorithmic recommendation engines, including a requirement to ensure gig workers are not mistreated by AI "work schedulers." In the U.S., federal banking regulators completed a comprehensive industry consultation exercise around AI risks in the sector earlier this year. The Securities and Exchange Commission has recently initiated a similar consultation on the use of behavioral algorithms and other digital engagement practices in retail investment (brokerage) platforms. And in April, the Federal Trade Commission warned companies to “hold yourself accountable – or be ready for the FTC to do it for you.”

Risk management professionals could claim that (a) these types of risks are highly technical and require specialist knowledge; and (b) AI/data science teams and their business stakeholders should have primary responsibility for managing them. They would be right on both counts. However, they should not underestimate their own enabling role in this space. 

Managing the risks from poor-quality AI is too important to leave purely to the specialists. Such risks must be viewed from a holistic, organization-wide perspective rather than a narrow technical lens. Risk management professionals should embrace this mandate -- as a way of supporting the digital transformation of their employers but also as a means of continuing their own professional growth. 

So how can they go about it? 

First, they must invest in learning more about AI, its potential and limitations and the ways in which the latter can be addressed. Not everyone has to become a data scientist, but the ability to ask the right questions will be critical. In particular, they should keep in mind that

• The workings of many AI models are far more opaque than traditional models. The most common type of AI algorithms (machine learning) creates models based on the data used to train them. As a result, the data scientist’s understanding of how the model actually arrives at its conclusions can be limited. This poses a challenge in convincing stakeholders – business line owners, risk and compliance teams, auditors, regulators and customers – about the algorithms' suitability for large-scale use. 
• AI models’ dependence on the training data can make them prone to particular weaknesses. Compared with traditional models, AI models are more likely to "overfit" or exaggerate historical trends. They may lose their predictive accuracy more easily in the face of changes in input data, such as those triggered by, for example, the pandemic. Finally, they can exacerbate existing biases present in the training data, such as biases regarding gender or race. 

Second, risk management professionals must connect the dots between these narrow data and algorithmic risks, and mainstream business risks. This requires a systematic and comprehensive mapping of AI risks to the broader risk landscape in the industry. For example, in banking, the most obvious risks related to large-scale AI use may already be covered as part of the specialist review of model risk and data risk. Model risk answers questions like, “Is the AI model reliable?” or “Is it working as intended?” Data risk answers questions like, “Is the data used to train the model accurate and representative of the target population?” or  “Is the AI model using or uncovering protected personal data elements inappropriately?” 

However, risk teams must go further and assess whether the use of AI accentuates one or more other existing risks, such as:

• The risk of treating a customer or staff member unfairly -- for example, by discriminating against certain groups when making lending or hiring decisions
• The risk of causing market instability or collusion due to malfunctioning algorithms
• The risk of “mis-selling” to a customer due to an algorithm that is not generating investment advice suited to the customer’s profile
• Business continuity risk due to lack of fallback plans in case of AI failure
• The risk of intellectual property theft or fraud due to adversarial attacks on the AI system

Third, and perhaps most importantly, risk management professionals must work with their business, data and technology colleagues to create mechanisms to manage such risks in a systematic manner. Left to themselves, individual data scientists and their business sponsors might well manage these risks in an ad hoc, case-by-case manner. Risk management professionals can help define risk appetites, standards and controls that enable such risks to be managed consistently and effectively.

See also: 3 Big Opportunities From AI and ML 

In this, they can call upon an increasing body of academic research and commercial tools to analyze AI models, explain the underlying drivers of the model outputs accurately and monitor and troubleshoot the model’s performance on a continuing basis. For example, such tools can allow organizations to: 

• Create transparency around the key drivers of the model’s predictions/ decisions (“Why did this radiology report not flag cancer risk?”)
• Assess any potential biases in model predictions and the root causes (“Do female applicants have a higher probability of getting short-listed for a particular job application than their male counterparts? If so, is that justified?”)
• Monitor model and data stability over time, trigger alerts when they breach pre-defined thresholds and identify the root causes of such instability (“Is our supply chain management model causing a higher number of parts shortages this month?”)
• Identify potential parts of the population for which the model is unreliable (“Are the model’s predictions for over-60 white collar workers based on too few data points?”)
• Identify potential changes in data quality that may affect the predictive accuracy of the model (“Can the bank’s lending model survive the massive changes in the economy due to COVID-19?”)

***

Increased transparency and control over AI are allowing organizations to become more sophisticated about the manner in which they use AI. The ability to manage these risks effectively can become a source of competitive advantage in the future.