LOUISVILLE, KENTUCKY, USA, March 18, 2024 /EINPresswire.com/ -- As Artificial Intelligence (AI) and Machine Learning (ML) continue to be integrated into business processes nationwide, insurers are jumping on the bandwagon to try to find the best ways to utilize these technologies for improving the application and underwriting process. Yet, inherent biases built into these technologies lack inclusivity and understanding, leading to potential for increased policy and benefit denials.

It all starts with the application process. Consumers receive numerous advertisements based on their internet searches, which attempt to capture more information that is in turn shared with insurers. The submission of an application can then lead to a phone call from an agent, whose job is to understand the needs of consumers and help guide them toward the best insurance products to meet those needs.

This process can be time-intensive, which is why insurers are looking for ways to speed up the process through automation. However, automating relies on machine learning models, which lack the ability to personalize the process and can miss the minute details needed to more completely underwrite consumers. Furthermore, biases in these systems can often exclude underserved populations that are most in need of insurance coverage.

“Technological tools are just that. They’re tools. It takes several tools, used correctly, to properly build something of value, says Bryan Simms, Co-Founder and President of Mammoth Life & Reinsurance Company. “A key is to use these tools to help make the insurance application and underwriting process more inclusive. The industry needs to show consumers the ability and want to understand their actual problems, and through that understanding, demonstrate our ability to become a trusted advisor to help make a traditionally complicated process easier.”

When leads are generated online, an important first step is to connect consumers with agents who look and sound like them, and who could have an easier path to understanding the unique needs of that individual. New data science tools can be used to map a consumer’s criteria and match them with agents that live in their neighborhoods.

Once that agent makes a connection, they can begin to walk consumers through the application process to better understand what products are best for them. Automated agents may miss a lot of the important minute details in these conversations, which can lead to immediate denials. Medication, for example, can be used against an applicant by automatically being tied to serious medical conditions. However, some of these medications are only taken after surgeries for a short period and provide little to no indication of the actual health of an individual. Context is key.

AI and natural language models are not trained to distinguish important nuances in application and underwriting interviews. For instance, older applicants who are having a hard time answering certain questions may have family members in the background talking to them to try to help with answers. A human agent can catch these moments and ask those individuals to assist their parents or grandparents in providing the correct answers.

Providing the right answers isn't just an important aspect of the insurance underwriting process. Proper discovery can also be the difference in whether insurance benefits are paid out to beneficiaries. A recent viral TikTok video discusses how a widower lost out on the death benefit of their wife’s life insurance policy due to incorrect answers during the application process. Digital tools are not necessarily equipped to catch factual omissions. But with more data than ever available to insurers, combined with properly trained agents, these errors can be avoided, ensuring that families receive full benefits after the tragic loss of a loved one.

“If used correctly, technology can help uninsured and underinsured Americans gain access to important life insurance coverage. Combining the latest technology with qualified agents can make the insurance process easier for underserved populations. Improved education, application, and policy design processes are important steps in helping families improve their protections versus financial shocks to the system, contribute to the wealth and well-being of their communities, and eventually begin to build generational wealth.”

Mammoth Life & Reinsurance Company was founded in 2021 as an inspired brand, reviving the legacy established by Mammoth Life and Accident Insurance Company, which was established in 1915 in Louisville, Kentucky by former slaves who pooled resources to self-insure after being marginalized and rejected by mainstream insurance markets. Mammoth Life’s mission is to deliver accessible and inclusive insurance products and solutions to the market aimed at the uninsured and underinsured life insurance demographics. MLRC is an agile, data-driven distribution company that achieves its mission by leveraging its unique and proprietary product engineering expertise, consumer engagement technology, and use of modern data science tools.

Daniel Mutter
MutterWorks
+1 305-926-1792
daniel@mutterworks.com

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