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By Will Sellenraad, Insurance Principal 

You know the spiel: underwriters are retiring, insurers have to act fast, there’s a big knowledge gap, etc. But just how big of a deal is this? I’ll let the numbers tell the story:

Insurance industry employees will retire between 2023 and 2028.


Of insurers plan to increase their investments in reskilling programs from now until 2021.


Of insurers cite a growing skills gap as the top factor influencing their workforce strategy.1

When you look into the retiring underwriter issue, there’s a wide range of suggestions and advice ranging from increasing awareness of the profession to investing in reskilling programs. Of all the advice I read/heard though, there are a few strategies that stick out to me as being the most valuable and realistic — and these do not include adding LinkedIn job posts for underwriters.

Retiring Underwriters: How to Deal With This Issue

Tactic 1: Nerd-ify Your Team

Instead of replacing retiring underwriters by training entry-level underwriters and hiring more underwriters, you should look to fill different roles — more specifically, tech roles.

In a recent article in the LOMA Resource magazine titled “Reshaping the Workforce,” the author talks about how AI is taking the industry by storm. To prepare for this, there are two things insurers need to do:

  1. Grasp how machines and people can collaborate. Employees will have to work with systems to ensure that they accomplish tasks in the appropriate manner and achieve the desired outcome. This goes hand-in-hand with the next point, that insurers need to…
  2. Look for skills and employees that are better-equipped to work with tech and AI. The author predicts that AI will reconfigure exiting jobs into three new categories:
                         • Trainers will assist computers as they learn to ensure that computer algorithms accomplish tasks correctly.
                         • Explainers will interpret results of algorithms to “improve transparency and accountability for their decisions.”
                         • Sustainers will be responsible for ensuring that “machines stay true to their original goals without crossing ethical lines.”

This basically means confirming that machines don’t have bias or drift towards specific outcomes. An additional role that might stem from this is Ethics Compliance Managers. Their job would be to guarantee that AI systems don’t discriminate against certain categories of customers.

Embracing AI will definitely require change and growth, but that is exactly what will help your organization gain more clients, break into new markets, and help you breeze past the oncoming retiring underwriters challenge.

Tactic 2: Change the 70:20:10 Model for Learning and Development

Last year, IBM published an AI blog titled “Gray matters: Addressing the loss of insurance industry knowledge as aging boomers retire”by Carl Sherzer. Sherzer explained an interesting concept called “The 70:20:10 Model for Learning and Development.”

It is a “commonly-used formula within the training profession to describe the optimal sources of learning by successful managers.” This is how it breaks down:



Job-Related Experiences


Interactions With Others


Formal Education


Why This Model Needs to Change to Work Within Life Insurance

When senior underwriters retire, their experience and interactions with new underwriters (mentoring and teaching — aka 90% of how a person learns) leaves too.

How can we solve this? Change the numbers.

Change the numbers so your new underwriters don’t have to rely so much on senior underwriters but rather on technology.

One way to do this is to invest in technology that aids in the decision-making process (i.e. reduce the 20%).

Cognitive underwriting technology is one option. When you have a system that learns the more it is used, it becomes more and more reliable and capable. Cognitive underwriting technology can aid in decision-making, let’s say for example when deciding to approve or deny a life insurance applicant. It takes out the guesswork by analyzing data and medical history information for you and recommends a decision based on your underwriting guidelines so you can fast-track applications.

Another option is RPA or robotic process automation. RPA is great because it too eliminates manual data entry, increases processing speeds, reduces the need for human capital and makes processes more consistent and scalable. Combine it with artificial intelligence like I mentioned above, and you’ve got a silver bullet strategy.

Tactic 3: Get Moving!

All this information can be a bit daunting. Implementing AI and cognitive into your underwriting system is no easy feat. If you need a partner to offer advice or guide you through the journey, let us know.

I’m no software guru, so I “borrowed” four major steps to follow to get started in all this from a white paper my colleague wrote.

  1. Establish your purpose. This includes understanding your goals, what you want to get out of a new system, and the overall plan.
  2. Groom your team. Determine which roles and duties employees will need to fulfill to make your new and improved underwriting system successful (think about tactic 1 above!).
  3. Craft the technology/system. This consists of designing the system architecture, thinking about integrations, your content repository design, etc.
  4. Set up your development process. For this step, you’ll develop document requirements and determine a strategy for deploying and maintaining the system.

Hopefully you see these changes in the industry as incredible opportunities to reach more people and improve your company’s longevity.