AI Underwriting: Enhancing Risk Management for Employee Benefits Providers

January 29, 2025


FinTech Buzz

By Stan Smith


Gradient AI empowers agencies like Michigan Planners to deliver tailored, cost-effective healthcare plans through predictive insights and proactive risk management.


As healthcare costs continue to rise, employee benefits agencies are experiencing increasing pressure to deliver customized, cost-effective health plans for employer groups. Michigan Planners, a full-service employee benefits agency specializing in group health solutions addressed this challenge head-on as they expanded their offerings to employer groups of varying sizes.


To meet these demands and to evolve its business model, Michigan Planners implemented an AI underwriting solution to gain deeper insights into risk and improve the quality of their group health offerings. By leveraging AI-driven insights, Michigan Planners has been able to completely change the way the company designs health plans, providing more personalized and cost-effective solutions to their clients.


Challenge: Limitations in Traditional Risk Assessment
Like many agencies, Michigan Planners struggled with constraints when trying to assess risk, especially for employer groups in the range of 25-500 lives. Limited bandwidth and access to adequate data meant that most of their decisions were based on historical claims information, providing only a backward-looking view of risk. This left them unable to offer forward-looking insights that could help employers better understand and predict future healthcare costs.

“As an agency, we had access to claims data, but we were essentially driving while looking through the rear-view mirror,” explains Aaron MacDonald, chief strategy officer at Michigan Planners. “This made it difficult to tailor plans or prepare for high-cost claims in the future.”


Solution: AI Enhanced Underwriting
AI is completely changing the underwriting process by automating complex tasks and delivering advanced insights into risk evaluation. Advanced algorithms can analyze massive datasets at speeds unmatched by humans, uncovering subtle patterns and correlations that traditional methods often miss.


Michigan Planners chose Gradient AI’s SAIL as its AI enhanced underwriting solution and it its empowering Michigan Planners to move from a reactive approach to a proactive one. The solution provides predictive insights that allow for more precise risk assessments. It also allows the underwriters to analyze vast amounts of data including historical claims data, to identify patterns and trends that were previously undetectable. Michigan Planners can also tailor plans according to the unique needs of each employer group, improving pricing accuracy and delivering better outcomes for both insurers and the policyholders.


“Thanks to SAIL, we can look through the windshield instead,” says MacDonald. “We have a much better idea of what’s coming and can tailor our health solutions accordingly. In fact, the speed and depth of insights we now have access to have more than paid for itself.”


AI-Driven Insights for Better Decision-Making
One of the key advantages of Gradient AI’s solution is its ability to streamline data analysis. Michigan Planners can now access easy-to-understand reports that provide comprehensive views of risk, without requiring additional staff or complex data analytics expertise. This allows their team to spend less time crunching numbers and more time engaging in strategic conversations with clients.


Other AI-driven insights has helped Michigan Planners address some of the most pressing issues challenging employer groups today. For example, in the case of a rapidly growing client following an acquisition, SAIL identified that self-funding was not a viable option. This discovery saved the client tens of thousands of dollars and prevented them from taking on unnecessary financial risk.

In addition, AI empowers Michigan Planners to provide better risk projections for clients dealing with high employee turnover or companies involved in mergers and acquisitions—common scenarios where historical data may be lacking or insufficient.


Custom Solutions That Save Clients Money
Michigan Planners now has the tools to offer highly customized health plans, which have led to significant cost savings for their clients. The AI-driven insights not only improve decision-making but also enable smaller employer groups, which traditionally lack the resources for detailed claims tracking, to make more informed decisions regarding their healthcare offerings.


For example, when working with smaller clients, Michigan Planners is now better equipped to offer insights into the pros and cons of high-deductible health plans and self-funding options. This level of customization helps employers optimize their healthcare offerings, ultimately leading to better financial outcomes for both the employer and employees.


The Future of Employee Benefits
As AI continues to reshape industries, employee benefits agencies like Michigan Planners are leveraging these new tools to offer more tailored solutions that meet the unique needs of their clients. The adoption of Gradient AI’s 
SAIL solution is just one example of how forward-thinking agencies are using technology to enhance their risk management processes and improve outcomes for employers and employees alike.


Michigan Planners is a great example of what’s possible when you combine deep industry knowledge with cutting-edge AI technology,” said MacDonald. “By enhancing our ability to forecast risk more accurately, we are creating more meaningful and cost-effective benefits programs for our clients.”


As healthcare costs continue to rise and businesses are restricted by tighter budgets, the ability to predict and manage risk will become even more critical. With the help of AI-driven solutions, agencies can continue to adapt and deliver smarter, more affordable healthcare plans to employers across the country.


Kim Wiswell, Gradient AI


Stan Smith, Gradient AI


Stan Smith is the founder and chief executive officer of Gradient AI


This article first appeared on FinTecBuzz.



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