How To Beat The High Cost Of Employees’ Life Insurance Policies

InsurTech can help reduce the cost of insurance underwriting

It’s hard enough to attract good employees these days. For many companies, it’s proving even harder to hold onto them. 

As businesses search for ways to retain valuable employees, they often think about expanding their benefits. And for good reason. Roughly 50% of employees see benefits as one of the top factors influencing their decision to stay or leave their current jobs. 

Life insurance is one benefit that can help employers stand out from the crowd. Offering life insurance to employees can help them feel that you genuinely care about them and their families. Unfortunately, most basic group life insurance policies have fairly low coverage. The financial protection such policies may offer employees’ families or dependents is very limited. 

While many employers allow workers to purchase supplemental life insurance to raise their coverage, the approval process can take weeks and be fairly expensive, mainly because underwriting is a complex and expensive process for insurers. Processing a single life insurance policy can cost up to $2,500, depending on the complexity and policy parameters, and underwriting is a high percentage of that cost. 

In other words, expensive underwriting drives up the overall cost of an individual or supplemental policy. This high cost is what keeps two-thirds of uninsured Americans from getting coverage. If businesses hope to decrease that number and provide affordable insurance options for employees, they need to uncover the root cause of these high costs and find ways to bring them down. 

Plus, as the world emerges from the Covid shutdown, this is an especially good time to address the problems in the life insurance industry. Roughly a third of consumers have said they are more likely to buy life insurance now than when the pandemic began. 

Why Is Underwriting Expensive? 

So, why is life insurance underwriting so expensive? Well, because it is not an easy thing to do. Underwriting is how insurers determine whether someone is eligible for insurance and how much the premiums will cost. Therefore, an underwriter needs to be an expert who can dig into mounds of data to determine the level of risk for an insurance prospect. Finding and sorting through all the relevant data needed for an accurate assessment takes time and effort, so hiring a good underwriter tends to be expensive. 

Here is how the process usually works: A life insurance agent reviews a prospective client’s application to confirm any information if necessary. Then the policy goes to underwriting. The underwriter may have additional questions beyond the initial application, and they will likely need information from third-party medical sources. But getting the data can take a lot of time and effort, especially since the health care industry as a whole has been overwhelmed since the outset of the pandemic. After collecting all the relevant data, the underwriter has to apply expertise and personal judgment to determine the outcome. 

In all, the process could take weeks or months and require dozens of hours of effort for an experienced and highly-trained underwriting expert. Thus, underwriting for life insurance is unusually labor-intensive and time-consuming: i.e. expensive.  

Hurdles for Insurers

One way a lot of insurers have tried to bring down underwriting costs is through accelerated underwriting, which eliminates the need for a medical exam. The convenience of this process is very appealing. About half of Americans say that they are more likely to buy life insurance with simplified underwriting compared to the traditional underwriting process.

But since simplified underwriting does not pull together the same kind of data as traditional underwriting, it brings more risk to insurers. To offset the risk, some life insurance companies charge more for policies based on accelerated underwriting, which means these companies are in effect reducing insurance options for individuals with limited financial means. 

Because of the increased risk, not every insurer offers accelerated underwriting, so many policies still require an exam and extensive medical data. So, despite the length and complexity of the traditional underwriting process, it continues to be the backbone of life insurance today.

Traditional underwriting has additional issues beyond its cost. For example, personal bias will always be a part of traditional underwriting, since it is all up to the individual underwriter how much the policy costs and whether or not an individual is qualified. This raises all kinds of issues regarding the fair treatment of people across gender, race, socioeconomic status, and other demographic categories. 

Can Insurers Solve the Issue? 

These problems have led many people, both within the industry and from the consumer side, to call for replacing traditional underwriting with a process that is data-fueled and automated. Change will not come easily in such an entrenched industry, but one major factor effecting change will be the rise of insurtech companies — carriers that rely on cutting-edge technology to provide insurance. As a result, life insurance may become more accessible to millions. 

Automated underwriting based on AI and machine learning algorithms can save much time and effort. Insurtech companies have already started using automation and artificial intelligence for claims processing, thereby reducing the amount of manual work required by around 80% and cutting processing time in half. Applying the same kind of automation to underwriting could allow insurers to collect and process large amounts of data with ease. 

What is more, the objectivity and faster processing speeds of automation and AI may help remove bias from the underwriting process. Questions remain, however, about whether automated underwriting could increase risk for insurers through inaccuracies or inadequate data sources. 

Data-fueled automated underwriting may be particularly helpful for creating better group life insurance offerings through employers. This is where businesses and HR can help bring down costs. Insurtechs are fueled by the data, and businesses generally have a lot of that employee data on hand already, and because that data is generally high quality and reliable, this helps reduce the risk for insurers. 

The result could be a dramatically accelerated underwriting process for group life insurance plans — and, in the future, enhanced individual plans that employees can opt for to increase their coverage, offered through partnerships between insurers and individual companies. 

So in the end, reducing the cost of life insurance underwriting comes down to big data. Underwriting pulls in data from a vast number of sources and then an underwriter has to make a decision based on all that data. But by leveraging automation, AI, machine learning, and data sources provided by employers, insurers can largely automate underwriting while keeping estimates accurate, keeping premiums relatively low, and cutting down on work hours for insurers and insurance agents. 

There is no easy answer to the high costs of underwriting in a huge industry that is slow to adopt new technologies. Still, insurtechs have already started to lead the way. The technology is available. Providers that make use of automated underwriting and leverage big data can reduce costs and thereby make insurance more accessible to a wider client base. 

Bob Gaydos, an insurance expert, is the CEO of Pendella.