Things as certain as death and taxes can be firmly believed. Believable, too, is that life is volatile and the cost of living highly variable. Because of these things, protecting your estate from taxation is one of several reasons why life insurance exists. How you structure this protection, transferring ownership of your policy and ensuring the payment of premiums while excluding this asset from your estate, is critical. That you act is critical, as the Biden administration wants to change major portions of the estate tax.

To start, the Tax Cuts and Jobs Act (TCJA) of 2017 exempts estates valued at up to $11.7 million. Whether life insurance proceeds are part of the taxable estate depends on who owns the policy at the time of the insured’s death. If you want to preserve your legacy, the owner and beneficiary of the proceeds from your life insurance policy must be another person or legal entity.

Choose wisely, because the owner of the policy is the person who is responsible for maintaining the policy. Because you do not want the policy to lapse due to failure on the owner’s part, or if the owner is a minor who is not able to pay the premiums without the approval of a legal guardian or trustee, make sure procedures are in place — perform the necessary due diligence — to make ownership convenient and secure.

An irrevocable life insurance trust (ILIT) is another means to a similar end, regarding estates and specific tax thresholds. In this case, the policy is owned by a trust. The proceeds are not part of your estate, nor are you a trustee in charge of the trust. You do not retain any rights to run or revoke the trust. The advantage here is the assurance that what must be done will be done, that premiums will be paid without delay, that the trust will honor its legal responsibilities. 

An estate planning adviser can also determine if you can transfer money — funds relating to gifts — to the trust, thus reducing whatever taxes your estate may owe.

If the beneficiary is a child or an adult with special needs, an ILIT lets you name the trustee — a person you trust — to whom you entrust the handling of money on behalf of your child or children, according to the terms of the trust document. 

In a word, documentation is key to any estate plan. 

See also: Breathing Life Into Life Insurance

Documentation is verification of trust, affording you the peace of mind you deserve. Regardless of who owns the policy, whether the owner is an individual or an institution such as a legal trust, proof is in the paperwork; legal documentation is proof of ownership. 

Do not tarry in attending to this work, lest the government be fastidious in its work of taxing the proceeds of your estate. 

Trust, too, that the government will tax your estate unless you safeguard your estate.  

For the good of your estate, with the opportunity for future generations to continue to do good, do what is right. 

Exercise the rights life insurance provides.

This article was written by Ronnie Klein for the International Insurance Society, a sister organization of Insurance Thought Leadership, under the umbrella of The Institutes. To see more IIS articles by Ronnie and other IIS experts, visit internationalinsurance.org.

What is happening in the world of life insurance?

The Hartford discontinued sales of individual life insurance policies in 2012.* MetLife spun off its life insurance business into Brighthouse Financial in 2017. VOYA Financial exited the individual life insurance business in 2018. AXA sold its share in Equitable, its U.S.-based life insurance business, in 2019. AIG announced that it will split off its life and retirement business in 2020. Prudential plc, of the United Kingdom, announced the demerger of Jackson National Life, its U.S.-based life and retirement business. The American firm Prudential Financial announced that it will sell its retirement business and is considering further “de-risking” of its annuities and other products. And these are just a few of the announced divestitures from the life insurance business by major insurers.

Is the sale of individual life insurance coming to an end? Insurers are certainly still selling it, but in this lingering environment of ultra-low interest rates, pressure is mounting from shareholders to sell off all or certain blocks of life insurance. That is why one prominent insurer’s CEO said, “I think that life insurance is a mutual company product.”

Not only are low interest rates making it difficult to earn a decent return on these products, but some insurers also have products on the books with minimum guarantees that they just cannot keep up with any longer. To add insult to injury, insurers must also hold regulatory capital against these policies and manage costly legacy administration systems. Announced changes to insurance regulations are tending toward increasing regulatory capital for long-dated guarantees, rather than decreasing it. Updating systems for old insurance policies does not seem like a good use of shareholder money.

Shareholders Demand Better Returns

Shareholders are becoming increasingly vocal about the returns on capital for life insurance. This is especially true for companies that must adhere to Solvency II regulations, which require insurers to hold excessive capital in support of long-term guarantees. A combination of low yields on assets and overbearing capital requirements makes life insurance increasingly difficult for stock insurers to maintain. One prominent board member of a life insurance company aggregator said the insurers that do not sell certain blocks of life insurance business “run the risk of activist investor action." While life insurance is generally thought of as a long-term business with many policies in force for decades, activist investors generally represent investors with much shorter time horizons. This mismatch of expectations can wreak havoc for life insurers and their policyholders.

The life insurance industry has focused on Baby Boomers for decades, and for good reason. Baby Boomers still hold over 50% of total household wealth (see Figure 1). This large group of people born between 1946 and 1964 purchased pure protection products to pay off mortgages and college costs for their children in case of premature death. Then they purchased life insurance savings products as they advanced in age and became more affluent. Then they purchased annuities to protect against outliving their retirement assets.

However, this era is coming to an end, as the youngest Baby Boomers are now in their late 50s and most are well into their 60s and 70s. Life insurers now realize that they have to invest in new technologies to attract other demographic groups, such as millennials. Freeing up large amounts of capital backing life insurance products to invest in technology seems like a better use of this money — and it is what shareholders are demanding.

The life insurance business is still extremely important and will continue to be so. It protects breadwinners from the financial consequences of premature death, disability or outliving their assets. According to the Financial Stability Board, insurer assets in 2019 amounted to $35.4 trillion. In 2016, the International Monetary Fund estimated that 85% of insurance assets can be attributed to life. That means that the life insurance industry is responsible for approximately 7.5% of the $404.1 trillion of financial assets worldwide. Not too bad for an industry that seems to be selling off its businesses.

Not only does the industry invest these assets into corporate bonds, infrastructure and government bonds, but benefit payments in the U.S. alone amounted to over $530 billion. The life insurance industry continues to be a noble undertaking.

Divestiture Strategies Vary

Insurers can use several different methods to offload blocks of life insurance business. They can stop writing new policies and manage the old policies as a run-off business. They can reinsure the old policies but continue to service and administer the policies. They can spin the business off into a separate company. They can reinsure the business and transfer the servicing and administration. Or they can sell the business to another organization, most likely to an aggregator. Each technique has its benefits and drawbacks, and hybrids may also be used. This paper will focus on the aggregation model, which has become more prominent during the past few years.

Through economies of scale, aggregators service and administer policies and may be able to invest a bit more efficiently than the seller was. Recently, the aggregator business has become quite competitive, with many new entrants, especially in the U.S. market. Aggregators can also domicile in jurisdictions with the most favorable capital requirements for their specific business models, thus reducing regulatory capital and increasing returns to shareholders.

The economics for this type of business seem to be working for both buyers and sellers, but what about the policyholder? This is exactly what insurance regulators around the world are exploring. With the increase in activity, regulators are “looking into the financial, operational and investment risks associated” with these transactions, according to recent conversations with four regulators. They are also concerned with policyholder protection. However, the chair of the board of a major aggregator recently said that regulation is “driving this business, not impeding it.” The president of another aggregator said that, as long as there is “sufficient capital to back the policies, regulators are happy.”

But there is more to in-force life insurance than simply paying benefits. Policies need to be updated as family circumstances change. If an aggregator is running off a block of business, the policyholders may not be receiving important services they need to keep their policies up to date. Aggregators will say that they actually do a better job servicing the policies because run-off is their core business. Their systems are newer and designed specifically for this business model, and the aggregators do not have new sales to offset lapses. Therefore, they need to maintain or improve persistency to meet shareholders’ expected returns.

Because most aggregators do not offer new policies, many policyholders may not be offered updates in coverage to meet changing needs in their lifecycles. The selling company will say that its agents and brokers will continue to treat these policyholders as customers, but regulators are becoming wary. One prominent European regulator said he would not approve the sale of a block of life insurance business when a third party services the policies. This regulator believes that the biometric and policyholder-behavior risks need to be with the same company as the administration. This, however, is not the norm in the U.S. or even other parts of Europe.

Another issue raised by regulators is the large — and growing — life insurance protection gap. Swiss Re estimates that the global mortality gap has reached $408 billion in 2020, a 6% increase from 2019. It seems unfathomable that the protection gap increased during a pandemic, when people were focused on their own mortality and that of family members. Others will argue that the pandemic impeded agents’ ability to sell policies by making it difficult to schedule paramedical exams and keeping people out of the office.

However, many insurers increased non-medical underwriting limits, making it easier to purchase life insurance without any additional exams. The Life Insurance Marketing and Research Association (LIMRA) announced that, while new life insurance policy sales in the U.S. increased 2% in 2020, annualized premiums dropped 3%. People were definitely considering purchasing life insurance during the pandemic, as the Medical Information Bureau (MIB) showed an increase in applications during 2020 (see Figure 2), but many did not complete the purchase. Some refer to this as the intention gap, another disturbing trend that needs to be addressed. Flat life insurance sales during the worst pandemic in 100 years is disappointing, nonetheless.

Technology Can Help

There has been a lot of talk in the industry about technology. Life insurers are investing millions of dollars and dedicating much time to start-up companies that claim to issue policies in minutes and to have developed more efficient underwriting and better fraud management. Willis Towers Watson (WTW), in its “Quarterly InsurTech Briefing Q1 2021,” announced that investment in insurtech for Q1 2021 reached a record $2.55 billion, spread over 146 deals (see Figure 3). About 31% of this funding is associated with the life insurance industry. WTW says that it will soon have to drop the term “insurtech” as these new technologies are becoming the norm. Even with the multitude of start-ups and insurtech investments, worldwide life insurance sales have been flat at best. Will these new ideas eventually gain traction that turn into tangible insurance sales?

One area of increased interest is in the field of artificial intelligence (AI). However, this technology is not as advanced as people might believe. Try asking an automated assistant to dial the phone of a friend with a foreign name. Sometimes, no matter how many times you say the name, the assistant just cannot understand it — until you receive a response such as “Ordering pizza.” (Although nice, hot pizza may take your mind off of whomever you were trying to call.)

In the insurance industry, AI has mainly been used for non-life insurance — particularly in fraud detection. With vast amounts of data now available, machines can comb through seemingly endless numbers of claims to search for patterns in suspicious claims submissions. Machines can find certain repetitive behaviors not easily discovered by humans. Not only can claims managers use AI to assist in identifying potential fraud, AI can also help find ways to prevent fraud.

AI is also being used more and more in the field of auto insurance, especially with telematics and autonomous vehicles. A newer use of AI is to match up a caller with the correct servicer. Using data such as previous issues, age, location and policy type, machines can learn how to increase sales and decrease lapses. Call-center activity is vitally important to the success of auto insurers, yet this activity is typically delegated to operations or IT. Perhaps it is time to realize that call centers should be under the control of the sales team.

For life insurance, the only real use of AI has been in the field of medical underwriting. Risk assessment is probably the most important aspect of life insurance, and companies spend a lot of money choosing their risks carefully. This typically involves costly paramedical exams, blood tests, nonmedical questionnaires and perhaps stress tests. These tests are not only expensive, they are time-consuming and can severely delay the delivery of a policy. Agents complain that lengthy delays in policy issuance are a major cause of non-taken ratios — which could increase the intention gap. Using AI to select risks more quickly and without time-consuming and expensive exams could lower prices and speed delivery of policies. This can help close the intention gap and increase sales.

Another use of AI for life insurance could be for in-force management. Given the robust market for blocks of in-force life insurance business and the continuing need for protection, it may be time for a change to the current business model. Imagine using AI to examine in-force policyholders and determine which were in need of policy changes — increase in face amount, sale of new products (annuities, long-term care, disability, etc.), decrease in face amount (could prevent an imminent lapse and help build customer loyalty). Using AI as a tool to assist agents in identifying customer needs could be very powerful.

Aggregators could use AI to sift through in-force life insurance policies to determine which are best-suited for policy changes. If the aggregator does not issue new policies, it can contract with third-party insurers to write the new policies and receive a commission. This would be good for all parties. The aggregator makes extra returns for its shareholders by marketing a highly valuable asset — its policyholders. Insurers have a great source of new business — people who have already purchased life insurance and who have been identified by AI as likely to purchase additional insurance. AI companies can sell their software to aggregators and insurers. And, most importantly, policyholders are given the opportunity to purchase important products to help secure the financial well-being of their families.

Conclusion

Life insurance is a very involved business. Insurers must develop complex products that can last more than 50 years. Then they must market and sell these products using an array of channels. Applications must be underwritten carefully to mitigate the risk of anti-selection. Once a policy is sold, it must be administered, which includes allowing for a host of policy changes. Reserves and capital held against these policies must be invested prudently, according to strict regulatory guidelines. Claims and other benefits must be paid with a watchful eye for fraud.

Traditionally, these completely different competencies have typically fallen under one roof. But there seems to be change in the wind. With a combination of a low-interest-rate environment, the Great Recession, a once-in-100-years pandemic and stricter regulation, it is becoming more and more difficult to manage all aspects of life insurance while meeting shareholder expectations. The life insurance industry is decentralizing before our eyes. It is too early to say whether this new approach will succeed, but, if interest rates remain at record lows, the odds of this happening increase.

Regulators will continue to scrutinize this evolving business model with the goal of protecting policyholders. The worst thing for a policyholder, insurer and regulator is for a life insurer to be unable to make a claim payment, especially if the policyholder has been paying premiums for 30 or 40 years. One default could destroy the entire model.

The sale of individual life insurance may well be best-suited to mutual companies, but the new model that is emerging might be well-suited to insurers, aggregators, shareholders, regulators and, most importantly, policyholders. Bringing the many activities that life insurers currently perform under one roof to separate companies that excel in one or two of these competencies may be the wave of the future. New technologies such as AI can assist in meeting policyholder needs. Regulators will have to show some flexibility and patience. It will be very interesting to see how the life insurance industry evolves.

Who said the life insurance industry is dull?

*This article originally said the Hartford had discontinued sales of life insurance. In fact, while it no longer sells individual policies, it still provides group policies.

Read more at internationalinsurance.org.

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Insurance is, at its core, five things: underwriting and pricing risk, selling and distribution, claims adjudication, servicing and, finally, investment management. Of course, there are hundreds of other skills and important areas, but these are the five central pillars of any insurance company.

Technologies are emerging that enable omnipresent, real-time connectivity between the people and businesses being insured and their insurers, and that is fundamentally changing the business of insurance. Here’s how.

Underwriting: Retrospective to Prospective

Underwriting and pricing is all about data and information at both the macro and micro level. Understanding socio-economic market trends, segmenting and accurately predicting how those may move and change is important. But the most critical data of all is at the individual customer level – the person or business you are about to insure. The more you know about their risk profile, the more accurately you can price their insurance and therefore the more competitive you can afford to be in selling and marketing.

Imagine if an insurer knew virtually everything about the behavior of the insured. Not only where they live but how they live, how they drive, their health and their daily habits. And imagine if the insurer had access to all the historic and predicted natural risk data about where the insured lived and worked and traveled. And imagine if there were computer programs powerful enough to gather, store and use this data to create an accurate and dynamic risk profile of the insured. No need to imagine – those capabilities already exist and are being refined and expanded. The debate over whether ZIP codes or credit scores are a fair and proper proxy for insurance risk will soon be moot, along with all the other retrospective information that has until now informed the underwriting process.

See also: Ready for the Fully Connected Future?

Usage-Based Insurance Evolves to Hyper-Personalized Insurance

A good example of this evolution in insurance is the well-publicized auto insurance product known as usage-based insurance (UBI), which is enabled by telematics – the joining of two sciences, telecommunications and informatics such as computer systems. In its infancy, UBI purported to offer auto insurance discounts based on driving behavior as reported by a device connected to the insured’s vehicle. In fact, these early programs were little more than clever marketing programs and were mostly counter-productive and unprofitable. Adoption rates grew slowly, initially attracting mostly better drivers willing to share their information. But, as smartphones proliferated and became more powerful and capable of reporting more critical driving metrics, these programs have evolved to become effective enablers of accurate risk quantification. In fact, some of today’s more sophisticated reward -based telematics programs are shown to significantly modify driving behavior and reduce risk.    

The initial resistance of consumers to share personal information eroded as they began to embrace other tech-enabled programs such as Google, Facebook, Amazon, Spotify and Uber, which require extensive sharing of personal information for users to participate.  

We are already seeing the expansion of these connected platform ecosystems to include car makers, insurers and supply chain partners and transform the risk, accident and claims management process in terms of speed, cost and customer service. And, early-stage telematics programs have evolved and expanded to pay-per-mile, distracted driving avoidance and – while still early on – crash notification.

The future of connected auto insurance programs is promising as adoption rates increase and accident services enter the mainstream from various directions. One of the more important benefits will be the transformation of today’s reactive claim model into one that self-activates and makes the process easier and more efficient, from initiating a claim and every step through to reconstructing how the accident happened. This model will serve to make current breakthrough technology even more powerful and spontaneous -- for example, photo estimating. The possibilities to accelerate the claim life cycle and bolster service represent exciting new value propositions waiting to unfold.

Connected insurance is spreading beyond auto to include other personal lines of coverage such as homeowners, property, life, health, accident and travel and into commercial lines, including property, small business, fleet, ride-sharing, home-sharing and workers compensation. 

Digital Ecosystems: Opportunities Through the Internet of Things 

The Internet of Things (IoT) will transform the world in the near future, and networked devices and sensors will enable this change. According to McKinsey, in 2010 there were 12.5 billion networked devices, and it is estimated that by 2025 that number will exceed 50 billion.

See also: Designing a Digital Insurance Ecosystem

The IoT is becoming a routine aspect of the everyday lives of consumers globally and is transforming business models across all industries. This new digital landscape presents opportunities for insurers: to develop new products (such as parametric insurance), open new distribution channels (such as embedded insurance) and fundamentally reinvent their business and products to include risk prediction and avoidance and real-time assistance and support on a hyper-personalized basis.

Even the investment management function of insurance is changing as carriers form corporate venture capital arms and invest in third-party vehicles that fund and leverage insurtechs and innovative technologies that are not only transforming insurance business operations but are earning outsized returns on investment capital as they exit into public markets.

A Connected Insurance Industry

The connected insurance industry of the future will still be supported by the same five core pillars, but underwriting and pricing risk, selling and distribution, claims adjudication and servicing and even investment management will look nothing like they did in the last millennium – to the benefit of all stakeholders, including the customer.

Sufferers of long COVID are often referred to as “long haulers” because symptoms can last for weeks or even months. And it is not just a person’s health that is affected for the long-term; there are many other knock-on impacts of extended symptoms, such as impact on life insurance, that industries will now have to consider and adapt to.

Much remains unknown, but the first step to navigating this new territory, for life insurance is to understand the data we do have so far.

Symptoms of long COVID

What do we know about long COVID?

We know that symptoms — shown in Table 1 below — may occur continuously or in a relapsing pattern. The symptoms may simply persist for a long time following the initial infection of COVID-19, or, over time people may experience new symptoms. 

Interestingly, by far the majority of patients with long COVID test negative for the virus, indicating microbiological recovery. As such, the causes of long COVID remain uncertain. Possible explanations include organ damage from the virus, exaggerated immune or autoimmune responses and persistent but undetectable viral reservoir.

Classification of long COVID 

Experts have also started to classify long COVID in two different stages. The first, referred to as post-acute COVID, applies to cases where symptoms persist for more than three but less than 12 weeks after the initial infection. The second, called chronic COVID, applies to instances where symptoms persist for more than 12 weeks following initial infection.

Experts also suggest that an alternative way of classifying long COVID is according to the predominant residual symptom experienced. Based on this approach, sufferers can be classified as having post-COVID cardiorespiratory syndrome, meaning likely to suffer with breathing problems; post-COVID fatigue syndrome, meaning likely to feel persistent low energy levels; or post-COVID neuro-psychiatric syndrome, meaning likely to experience cognitive dysfunction such as depression, anxiety or brain fog.

Risk factors for long COVID

What do we know about who is most likely to develop long COVID?

Data suggests that patients hospitalized during the initial COVID-19 infection have an increased risk of developing long COVID (87%) compared with those treated with outpatient COVID-19 (10% to 35%). Hospitalized patients are also more likely to sustain organ damage from their initial infection, leading to prolonged symptoms.

What’s more, the number of symptoms presented at the time of initial infection appears to predict the likelihood of a person developing long COVID. The more symptoms at initial infection, the higher the risk of developing a long COVID syndrome of some kind.

Long COVID is more commonly reported in adults aged 50-plus, although it can occur in any age group, including children.

Individuals with co-morbid disorders, and in particular co-morbid psychiatric disorders, such as depression or anxiety, have an increased risk of developing long COVID after infection. The more co-morbidities, it appears, the higher the risk.

See also: Long-Haul COVID-19 Claims and WC

Long COVID and Morbidity

The link between long COVID and morbidity must be continuously assessed. At this early stage, not enough data exists to provide a clear understanding. 

That said, wide varieties of new-onset pulmonary and extra-pulmonary disorders, meaning conditions associated with the lungs, have been observed in long COVID patients, including interstitial lung disease and respiratory failure. Table 2 shows a list of the extra-pulmonary conditions associated with long COVID.

Additionally, according to a recent longitudinal study of more than 73,000 U.S. veterans with a history of outpatient COVID-19 infection, there was an increase in observed short-term mortality at six months, when compared with veterans with no history of COVID-19 infection. However, the picture is far from complete, and more research is required for an accurate understanding of the mortality associations of various long COVID syndromes.

Evaluation of long COVID for life insurance purposes

When it comes to evaluating the associated risks of a person experiencing long COVID, the predominant residual symptom profile should be used to guide the evaluation. For example, if the predominant symptoms presented are shortness of breath and chest pain, cardiorespiratory investigations such as lung function tests, EKG, echo or chest imaging should be conducted.

For more general symptom profiles, blood and imaging tests will need to be conducted, guided by clinical assessment, and may include tests such as complete blood count, liver and renal function analysis, urinalysis, D-dimer assay testing (which screens for clots or deep vein thrombosis), inflammatory marker testing (which evaluates the presence of inflammation) and NT proBNP testing (which detects signs of heart failure).

Underwriting considerations 

When it comes to life insurance underwriting, there is some early-stage guidance to help navigate this new territory. One of the most important factors to consider is adjusting ratings in the case of any evidence of organ damage. To date, though, for sufferers of long COVID with no evidence of organ damage, there does not appear to be any significant excess mortality risk to take into account when underwriting.

As with any emerging condition, the picture we have today, and the industry’s understanding of risk, will become a lot clearer in time. What’s needed now is continued study and analysis of patterns so new underwriting rules can be developed. One thing is for sure, though: The COVID-19 virus is leaving a troubling legacy.

You’ve probably seen it in your own life. A new gadget or software program promises to make life easier, but you can’t bring yourself to get started. 

Maybe it’s too complicated to set up. Maybe you’re not sure if it really works. Maybe you’re just set in your ways. So, you keep trudging through the old way of doing things. 

The same thing can happen at your insurance agency. Every month, you face decisions about what technology to use in your day-to-day operations, how to get the most value out of the services you already use and how to improve your customer experience. 

As the head of a company that offers those kinds of services just for the insurance industry, I have some insight into how to make those decisions and achieve what I think of as “digital balance” — a task that has only become more urgent since the coronavirus pandemic began. 

What Does it Mean to Have Digital Balance? 

Digital balance is the Goldilocks spot. At one end of the spectrum, there is too much technology. We we spend loads of time trying to use everything offered in hopes of some productivity breakthrough. At the other end of the spectrum, we are really not taking advantage of technology because we are relying too much on the comfort of old processes we think work good enough. Digital balance lies in the middle of the spectrum.

With the myriad of applications and software thrown at us as a means to improve our lives and our workflows, finding digital balance is really about learning to evaluate the technologies we use on a daily basis, so we can embrace the ones that improve our efficiency and productivity and let go of those that no longer provide value. 

The importance of this evaluation has become even more apparent within the past 18 months as we navigate through the ups and downs of the pandemic, striving to still provide our customers the best experience possible and give our employees the tools and support they need to succeed. 

A simple way to evaluate your balance is by breaking your company down into categories depending on your specific makeup. I will just review a few examples, but there are obviously others like human resources or accounting that could be reviewed much the same way. 

How to Review Your Digital Balance 

Here are the five main categories I will review: 

• Internal Communications: How we communicate with our staff.
• Workflow/Documentation: The processes by which everything gets accomplished and recorded as it moves through our system.
• Marketing: How we tell our story, position our brand’s value and reach potential customers.
• Sales and Customer Service: The way we deliver on the promise to provide the best customer experience possible.
• Data and Metrics: Measuring the results of our efforts and accessing information to make improvements.

See also: Digital Is the Assistant We Always Wanted

The way we evaluate our digital balance is by looking at each category across our company, creating an inventory of technology, evaluating each solution, identifying any pinch points, setting our priorities and making a plan to adjust our solutions to maximize efficiency and productivity. 

Internal Communications

Given the new dynamic of having, in some cases, onsite and remote employees, internal communications are more important than ever. Your employees need to communicate quickly and effectively. Failure in communication can lead to declines in productivity as well as employees feeling isolated.

Some of the questions you might ask are: 

• What are the processes behind how we communicate currently?
• What communicating technology are we currently using? Is it effective? Is it redundant?
• What are we relying on the most: email, phone calls, voicemails, sticky notes, instant messaging, intranet?
• How are we avoiding employees and departments from being/feeling siloed?
• Are we using technology to streamline communications?
• What hardware or software do we need to fulfil our communications needs?
• Have we considered all the security risks for communications on personal hardware and remote access for employees working out of the office? 

Workflow/Documentation 

All projects live somewhere. They may be new, complete, in progress or maybe in need of changes. The point is, to get things done, there needs to be a process by which workflow happens. Technology can create an efficient solution to make this happen and track the results. 

• Do we have a work-flow process that could be improved by technology? 
• Are different departments using separate technologies to get the same result? 
• Has staff using the technology been trained so they can maximize the effectiveness?
• Does remote staff have the same access? 
• Have we signed up for technology that we are not even using? 

Marketing 

Brand, perception, reach and awareness. So much technology has been developed to maximize the way we communicate our company’s value to the prospect. It is very easy to lose track of all the tools available. Often, many technologies overlap.

• What is the inventory of each technology we are using, and how is it used to achieve the desired result? 
• Is there a way to combine any of our marketing needs into one solution? Will there be an advantage? 
• Do our marketing needs require specialized solutions outside of other solutions the company uses? 
• Will the costs of technology used to acquire new customers exceed the value? 
• Do we have the staff, and are they trained to maximize the effectiveness of the technology? 

Sales and Customer Service 

From your customer relationship management (CRM) to building relationships and solving customer issues, technology plays a big role in providing the best customer experience possible. Processes can be greatly improved with solutions that put customer information at your fingertips. 

• Do sales and customer service have access to the technology needed to provide the best experience? 
• What is our customer lifecycle, and what technologies can we put in place to understand and improve that experience? 
• Are we using technology to track how we are communicating with customers during and after onboarding? How do we know where we can make improvements? 

See also: 1 Million Digital Life Presentations

Data and Metrics 

Knowing where we have been certainly helps us improve where we can go. Using technology tools that provide access to data and metrics gives us valuable insights, allowing us to make better decisions and make improvements. 

• What key performance indicators (KPIs) do we need to measure to give us the information needed to make better decisions? 
• Will one technology meet the needs of all my data requests? 
• Are we collecting data from technology but not using it? 
• Do I have the staff to effectively use this technology? 

Achieving Digital Balance 

These are just general guidelines for you to evaluate your technology footprint. I hope you can use this information to maximize the technology you are currently using and possibly look to introduce new technology to build a more efficient and productive work environment. 

When AI Doesn’t Work Paul Carroll, Editor-in-Chief of ITL Although I’m a big believer in the prospects for artificial intelligence, and we’ve certainly published a lot to that effect here at Insurance Thought Leadership, AI has also carried a ton of hype since it emerged as a serious field of study in the mid-20th century. I mean, weren’t we supposed to be serving our robot overlords starting a decade or two ago? To keep us from getting carried away, it’s good to look from time to time at the failures of AI to live up to the projections, to see what AI doesn’t do, at least not yet. And the attempts to apply AI to the diagnosis of COVID-19 provide a neatly defined study. continue reading > Majesco Webinar Join this webinar to learn how Group and Voluntary Benefits players have the opportunity to extend their reach through new, broader diversified plays that align to a new generation of employees and employers.   Register Now SIX THINGS How to Improve the Customer Experience by Denise Garth Increasingly, customers don't choose just a risk product but a combination of risk product, customer experience and services. Read More The Evolution of Frictionless Payments by Ed Whitehead The buying process needs to be easier for both the customer and the seller, to avoid all those abandoned shopping carts. Read More Small Commercial: Digitizing Distribution by Mark Breading Data pre-fill is the top project area for sales capabilities as it is a critical starting point for achieving straight-through processing. Read More Underwriting Small Business Post-COVID by Jeremy Stafford Carriers must go beyond traditional data sources to minimize the information gap and transform the underwriting of small businesses. Read More Adding Transparency to Life Settlements by Lucas Siegel Transparency prevents relationship-based decisions and gives all stakeholders confidence that the buying process is fair. Read More 10 Ways Insurers Should Lean on OKRs by Bastin Gerald Objectives and key results (OKRs), a tool developed by legendary Intel CEO Andy Grove, can guide insurers through digitization. Read More MORE FROM ITL Resilience Ratings: Triple-I Unveils Way to Measure Communities’ Risk Levels Peter Drucker once famously said that “what gets measured gets managed,” and the Insurance Information Institute is unveiling measures for U.S. communities’ resilience against natural disasters. In this webinar, ITL Editor-in-Chief Paul Carroll and the Triple-I’s senior economist, Michel Leonard, discuss what the measures cover, how individuals and communities can use them and where the Triple-I will take them from here. Watch Now AUGUST FOCUS: Cognitive Technologies This month sponsored by Intellect SEEC Cognitive computing is a funny beast. Every time you hit your target, you find that another pops up off in the distance. When I first saw a demonstration of speech recognition, some 30 years ago, I was mightily impressed that the computer understood a few words. If I had seen what would be possible today, I’d have been stunned. But now? Oh, that’s just Siri or Alexa. And why didn’t auto-correct guess exactly what I wanted to say? Keep Reading Digital Revolution Reaches Underwriting by Intellect SEEC Underwriting is evolving toward a service that will help clients prevent losses, rather than merely indemnifying clients afterward. Read More Partner with ITL to create expert thought leadership content. Custom Content Promoted Content Display Advertising Custom Webinars Monthly Topic Sponsorships ITL Partner Packages and more Learn more and get the 2021 Media Kit GET INVOLVED Write for Us Our authors are what set Insurance Thought Leadership apart. Get Started SPREAD THE WORD Share Share Tweet Forward SUBSCRIBE TO SIX THINGS

Thanks to large-scale ransomware attacks on technology providers like Kaseya, everyone involved — from cybersecurity practitioners to the business leaders who hire them, and from local policymakers to the White House — is thinking about how to reduce risk across the board. As cyber attacks grow in quantity and complexity, hurting downstream customers and interrupting business continuity, organizations need to take the right steps to implement proper security controls. 

Before, in-house security teams at organizations were scarcely involved with cyber insurers (if the organization had a cyber insurance policy at all). But in the face of an intensifying threat landscape, policyholders, brokers and insurers are working together to find solutions that benefit everyone involved. This newfound collaboration is enabled by technologies and solutions developed by insurtechs, taking the form of data-driven approaches to underwriting and more efficient implementation of best practices, thanks to up-to-the-moment data on security postures gathered by insurers and shared with brokers and policyholders. 

Let’s look at a few of the ways that insurers, brokers and policyholders are working together to improve security. 

Giving Policyholders Incentives to Adopt Better Controls

Policyholders should be encouraged to implement better cyber defense. Today, cyber insurers are looking for a new baseline of controls, which commonly includes multi-factor authentication (MFA), endpoint detection and response (EDR) and acceptable backup planning and strategy.

1. MFA is an authentication method that requires the user to provide two or more credentials to gain access to an account. Rather than just asking for a username and password, MFA requires one or more additional verification factors unique to the individual, which decreases the likelihood of a successful cyber attack. Insurers want to see MFA for access to email, remote access to the network and administrator-level access, as it will help thwart or at least slow down an attacker. While a determined threat actor may find a way around MFA, a company without MFA in use is low-hanging fruit.
2. Assuming a skilled threat actor does find a way in, EDR tools can provide an extra layer of threat identification and protection. They have all the benefits of regular antivirus software but go beyond just looking for known indicators of compromise. EDR tools can also identify anomalous user behavior on the endpoint and flag it as suspicious. And if implemented properly, the tools can potentially prevent ransomware from deploying fully. These tools may also have important activity data that forensics investigators can use to determine what the threat actor did in the system and data recovery functions that help a company get back up and running faster. Insurers are increasingly asking about EDR as a control, given it can at least lessen the impact of ransomware incidents. 
3. In connection with efficient data recovery, solid backup strategy and documentation of a disaster recovery or business continuity plan will help provide peace of mind to policyholders that they are prepared for the worst-case scenario. Security protocols that include immutable backups (a backup that is read-only and cannot be altered or deleted by anyone, including an administrator at the company) are often supported by top-tier cloud backup solutions, marking another important consideration for policyholder investments. Gone are the days where backing up to a separate server is sufficient. Many organizations are moving their backup solutions to the cloud or adopting a hybrid model for this very reason — but it’s how you protect those cloud backups that is key. Organizations need to invest in a solution that will prevent internal members from making changes to backups, because a threat actor that steals their credentials will attempt to access and delete backups as a way to force an organization’s hand at paying.

To fully harness the power of these protective tools, there are two main ways to encourage policyholder usage: fair pricing and education. The cost of cloud backup solutions and EDR tools has come down significantly in recent years, meaning these tools are no longer cost-prohibitive for most companies. For insurers, providing additional discounts on top of already reasonable pricing can be what pushes an organization over to compliance. The greater challenge is in prioritizing what controls to implement and identifying the right vendor (there’s a lot of noise out there!). This is where education can be key and where cyber insurers and brokers can step in to recommend solid partners and solutions.

See also: How Insurtech Boosts Cyber Risk

Enable Underwriters With Tech for Increased Visibility 

Cyber underwriters have traditionally relied on application questions, emails and underwriting calls for larger accounts to obtain cybersecurity information to underwrite an account. Insurtech in cyber insurance empowers underwriters with additional data points about a risk’s posture so they can take a data-driven approach to underwriting.

The ability to scan for threats, and identify risk levels based on existing data, enables underwriters to identify vulnerabilities and build a more meaningful analysis. While there’s no tech-enabled replacement for an experienced underwriter, being able to gain insight into an organization’s IT infrastructure to discover common risk factors (some they may not even be aware of) can streamline the process. The applicant is able to mitigate risk and improve cyber hygiene, which gives the underwriter the additional confidence to move forward. 

In the end, thanks to tech-enabled underwriting, the result is an insured organization. Given the current risk environment and hard market for cyber insurance, we can confidently say that, without the ability to pinpoint risk factors at an individual account level, far more insurers and their underwriters would have further clamped down on cyber limits, increased rates and perhaps exited the market entirely — meaning insurance would be inaccessible for most, if available at all.

Standardize a Threat Response

Cyber insurers and brokers can work with existing policyholders to identify new, active threats during the policy term and support them in their response. 

Once a policyholder is identified as at-risk, tech-enabled cyber insurance providers can consistently monitor the situation and communicate clearly, concisely and quickly about what’s happening. As more information becomes available, it is critical to not only alert the right people but provide extra context around the vulnerability, what the risk is if they don’t patch it and the steps needed to resolve it. This should be done in a way so that all types of team members (in addition to IT professionals) can understand the criticality and communicate it to the right stakeholders for resolution. 

See also: Wake-Up Call on Ransomware

Another method to support policyholders is to weave in prioritized cybersecurity recommendations. At Corvus, our “vCISO,” or virtual CISO, guidance is one way we help policyholders take a stance against threats. This starts with a short security assessment, and pairing of the responses with scan findings that provide the policyholder with a prioritized list of cybersecurity recommendations and resources to help them implement controls or remediate vulnerabilities. This type of consistent, close collaboration is core to the cybersecurity approach that modern insurtech providers are taking to make an enduring impact on risk, rather than checking off a few boxes at the point of underwriting and renewal. 

To boost digital resilience and strengthen cyber hygiene against outside threats, policyholders need to have both the context for why certain security controls are so crucial, as well as the ability to adequately implement them within their organization. Insurers and brokers play a pivotal role in guiding policyholders to make the best decisions to limit their risk, and solutions developed by insurtechs help get the process off the ground with data-backed guidance. As cyber attacks evolve, so will protection strategies — and the sooner companies adopt supporting technologies the easier it will be to get on the same playing field as cybercriminals.

Peter Drucker once famously said that "what gets measured gets managed," and the Insurance Information Institute is unveiling measures for U.S. communities' resilience against natural disasters. In this webinar, ITL Editor-in-Chief Paul Carroll and the Triple-I's senior economist, Michel Leonard, discuss what the measures cover, how individuals and communities can use them and where the Triple-I will take them from here.

This webinar discusses:

• How the Triple-I assembled the ratings over the past 18 months based on data from federal authorities, from academic institutions and from its own work.

• How those considering buying homes can use the ratings to understand the flood risk in the communities they may move into and be assured that insurance will be available at an affordable rate.

• How the Triple-I will extend the measures to cover additional types of natural disasters, including wildfires and tornados.

---

Speakers:

Although I'm a big believer in the prospects for artificial intelligence, and we've certainly published a lot to that effect here at Insurance Thought Leadership, AI has also carried a ton of hype since it emerged as a serious field of study in the mid-20th century. I mean, weren't we supposed to be serving our robot overlords starting a decade or two ago?

To keep us from getting carried away, it's good to look from time to time at the failures of AI to live up to the projections, to see what AI doesn't do, at least not yet. And the attempts to apply AI to the diagnosis of COVID-19 provide a neatly defined study.

I've long believed in learning the lessons from failure, not just from successes. To that end, while Jim Collins had done the work on the patterns of success in Good to Great and Built to Last, I published a book (Billion Dollar Lessons, written with Chunka Mui) a decade-plus ago based on a massive research project into the patterns that appeared in 2,500 major corporate writeoffs and bankruptcies. You can't just look at the handful of people who, say, won millions of dollars at roulette and declare that betting everything on red is a good strategy; you have to look at the people who lost big at roulette, too, to get the full picture.

In the case of AI, a recent article from the MIT Technology Review found that, to try to help hospitals spot or triage COVID faster, "many hundreds of predictive tools were developed. None of them made a real difference, and some were potentially harmful.... None of them were fit for clinical use [out of 232 algorithms evaluated in one study]. Just two have been singled out as being promising enough for future testing."

Another study cited in the article "looked at 415 published tools and... concluded that none were fit for clinical use."

What went wrong? The biggest problem related to the data, which contained hidden problems and biases.

The article said: "Many [AIs} unwittingly used a data set that contained chest scans of children who did not have COVID as their examples of what non-COVID cases looked like. But as a result, the AIs learned to identify kids, not COVID."

One prominent model used "a data set that contained a mix of scans taken when patients were lying down and standing up. Because patients scanned while lying down were more likely to be seriously ill, the AI learned wrongly to predict serious COVID risk from a person’s position.

"In yet other cases, some AIs were found to be picking up on the text font that certain hospitals used to label the scans. As a result, fonts from hospitals with more serious caseloads became predictors of COVID risk."

Some tools also ended up being tested on the same data they were trained on, making them appear more accurate than they are.

Other problems included what's known as "incorporation bias" -- diagnoses or labels provided for the data before it was fed to the AI were treated as truth and "incorporated" into the AI's analysis even though those diagnoses and other labels were subjective.

I'll add based on personal observation from 35 years of tracking AI that it's tricky to manage, meaning that issues should be expected. The vast majority of senior executives don't have a technical background in information technology, let alone in AI, so it's hard for them to evaluate which AI projects will pan out and which should be set aside. Even those proposing the projects can't know with much precision ahead of time. They can identify areas as promising, but nobody can know that they'll hit an insight until that insight appears. Add the fact that AI carries an air of magic, which can give it the benefit of the doubt even when good, old humans might do a better job.

The article's main general recommendation happens to be the same prescription that Chunka and I offered at the end of Billion Dollar Lessons to help head off future disasters: generate some pushback.

In our case, dealing with corporate strategy, we recommended finding a "devil's advocate" who would look for all the reasons a strategy might fail. The person would then present them to the CEO, who otherwise is often fed a diet of affirmation by people trying hard to make the CEO's brainchild look brilliant. Our research found that 46% of corporate disasters could have been averted because the strategies were obviously flawed.

In the case of AI, experts quoted in the MIT Technology Review article recommend finding people who could look for problems in the data and for other biases. That advice should be extended to considerations of whether a project should be attempted in the first place and whether claims made on behalf of an AI should be tempered.

As I said, I firmly believe that AI will play a major role in transforming the insurance industry. There are already scores of examples of successful implementations. I just think we'll all be better off if we keep our eyes wide open and anticipate problems -- because AI is tricky stuff, and problems are out there. The more pitfalls we can avoid, the greater our likelihood of success.

Cheers,

Paul

Despite the impact of COVID-19, the commercial insurance marketplace must provide the proper insurance coverage for small businesses that have survived, morphed, jump-started or stalled. Insurance carriers have needed to assemble a more complete snapshot of each small business’ individualized risks, but now that’s more important than ever. To do so, carriers need to go beyond traditional data sources to minimize the information gap and help to transform the underwriting of small businesses.

Assessing risks more accurately

One of the challenges in underwriting a small business is finding sufficient financial data about the business. According to a 2019 internal study conducted by LexisNexis Risk Solutions, approximately half of small businesses have a credit profile only in a single commercial credit bureau. When insurers exclusively use commercial credit for commercial rating, they are likely missing the true risk profile of the small business in their book. 

To properly protect a small business customer, insurance carriers need to make sure they’re collecting and analyzing available data. Fortunately, there is an abundance of data and analysis available to overcome this problem; it just needs to be aggregated, analyzed and provided in a readily digestible way. 

Gain from a multi-source strategy 

A multiple-source approach can address the gaps, but identifying and evaluating the right data sources is critical for pricing a risk fairly, for both the customer and the insurer. Our internal analysis shows that when insurers use three financial data sets in their underwriting, it results in an average scorable rate of 74% compared with just 52% with only one source.

Leveraging small business credit data also provides insurance carriers with extended visibility and financial data insights on small and micro businesses, and combining small business credit data with other available business data makes it even more powerful. Providing predictive modeling makes it easier for carriers to evaluate a business by its loss propensity at the point of quote, underwriting or renewal. 

With financial data from millions of small businesses, carriers can benchmark a customer against the industry at large and have financial insight that may not be found in commercial credit sources. This approach, with an incremental model of business data and small business credit data, can provide up to an 88% scorable rate coverage on small businesses and can match up to 96% when combined with business owner financial data.

See also: COVID-19 Trio Tops Global Business Risks

Create an inclusive approach

For commercial carriers looking to improve their book of business, begin by understanding your current and future target market. How do these types of businesses compare with similar entities in your book of business, and what financial products do they use?

Next, select the right sources of data for a particular business. Credit bureaus, non-traditional financial sources and personal financial data can all be used to better align to your book of business.

Lastly, create an underwriting program that leverages these data sources to better segment small businesses based on a more precise view of the business’ or business owner’s financial profile. This design, a predictive model, is built specifically to help you more quickly and confidently assess risks. Taking advantage of segmentation can increase the effectiveness of your program and improve your loss ratio contingencies. 

Insurers looking to remain competitive within the small business market need to evaluate the right mix of information on both the business and its owner to price the risks of each small business they insure more accurately. Embracing change and seeking predictive models with industry data can improve risk assessment and support more dependable decision-making.