Why employee data can optimize benefit programs

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Anyone who's worked in the life insurance industry for a while will know that many Americans are significantly underinsured. The latest statistics show that only 60% of Americans have some sort of life insurance. And of these people, 30% rely solely on group policies provided by their employers. To bridge this coverage gap, life insurance carriers will need to get more serious with pushing comprehensive coverage that only individual policies can provide.

However, to do so carriers will first need to convince employers that individual life insurance is a better alternative to group policies. That may require some careful discussions, as group life insurance is a pretty embedded part of most workplace benefits offerings. Fortunately, as I know from my own experience, it doesn't take much to change an employer's mind on that point. 

Peace of mind for employees

As we know, the purpose of life insurance is to provide financial security in the event of an untimely death. But that definition starts to look pretty hollow when you consider that the average payout of a group policy is about $50,000, which is the same as it was 40 years ago. In 1983, that would have covered about two years of salary for the average worker. But in 2023, $50,000 isn't even enough to cover half the average household debt.

Group policies also suffer from a lack of customization, non-portability, and premium costs that can increase over time. This raises the question of whether group policies offer anything of real value to employees. My personal view is that they don't, unless the employee also has an individual policy with the group policy as a supplement.

By contrast, an individual life insurance policy can be underwritten to suit the specific needs of each employee. They can choose their coverage amount and policy duration, add additional riders for other family members, and enjoy the full advantages of portability. This level of personalization makes individual life insurance a highly attractive benefit, providing employees with a sense of control over their financial security. Unfortunately, very few employers are currently offering this level of protection, which makes the ones that do really stand out in the jobs market. 

Some historical perspective

Group life insurance policies were never meant to serve as the core coverage policy for an employee. In the past, employees typically held their own individual life insurance policies, while group policies from employers supplemented their coverage. However, since the early 1990s, there has been a decline in the number of people with individual coverage. To my mind, two main factors contributed to this decline: the increasing complexity of underwriting processes and a decrease in the number of life insurance agents.

Consequently, people increasingly turned to the convenience and simplicity of employer-provided group policies. These policies required minimal underwriting and were often presented as a one-size-fits-all policy, thus simplifying the decision-making process for employees. But again, relying solely on group policies can leave employees feeling underinsured and lacking the tailored coverage that only individual policies can provide.

This context sheds light on the importance of reintroducing individual life insurance policies as a core coverage option for employees. By offering individual policies alongside group coverage, employers can meet the evolving needs and preferences of their workforce, reinstating the personalized protection that was once the norm. This revitalization ensures that employees have access to comprehensive coverage that aligns with their specific circumstances. As for employers, they gain the advantages of a more competitive benefits package and a greater sense of loyalty within their workforce. 

Leveraging employee data

Employee data holds great potential for maximizing the value of employee benefit programs. It offers a comprehensive view of employees' demographics, including their income levels and overall health, as well as whether they are single parents, homeowners, or empty nesters. This wealth of data enables a deep understanding of each employee's specific circumstances and helps identify the appropriate coverage and benefits they require.

However, what I've seen from talking with employers on this subject is that many of them are afraid of misusing employee data. I suspect that this fear stems from privacy and compliance concerns with regulations like HIPAA. Employers don't think they can use this data when in actuality they can. HIPAA says you must protect this data, but it does not prevent you from using it for the benefit of employees and legitimate business purposes. I'd even argue that employers have a fiduciary responsibility to leverage this data.
 
Furthermore, there's a misconception that sharing data with vendors violates HIPAA regulations as well. However, under HIPAA, businesses can establish associate agreements with vendors who are working on behalf of the employer for legitimate business purposes. This allows for the responsible use of data without compromising privacy. For example, employers routinely provide census files to insurance providers like Blue Cross, unaware that similar agreements can be made with other vendors. This opens the door to using big data and AI analytics for speedy and seamless underwriting of individual coverage policies.

Final thoughts

For life insurance carriers, convincing employers of the need to include individual life insurance in their benefits packages will become increasingly important in the coming years. At the same time, it is also crucial to address any hesitation or concerns surrounding the use of employee data and guide employers through the process.

By highlighting the legitimate business purposes of data utilization and emphasizing the potential benefits for employees, employers can leverage employee data in a way that is not only permissible but also vital to optimizing their benefits programs.

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Life insurance Customer data Employee benefits Big data
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