Artificial Intelligence and Life Insurance: How It’s Changing Agents’ Jobs

7 November 2023

In a world that increasingly demands it, life insurance is on the decline. Companies in the life insurance sector are currently experiencing an unprecedented period of transition. Currently, policyholders over the age of 65 hold 40% of the Assets Under Management (AUM), which amounts to $7.8 trillion for the 40 largest global life insurance companies, according to Capgemini’s World Life Insurance Report 2023. These assets, as estimated by Capgemini, could be transferred to beneficiaries by 2040.

The life insurance sector is currently facing a significant outflow of assets under management (AUM)

The loss of market share in the life insurance sector, even in terms of market capitalization (as highlighted in the following graph), may seem paradoxical in a world where the population is living longer and more actively, and public welfare is decreasing

New Customer Needs and Expectations, but Old Products and Sales Models

The reality is that changes in lifestyle and society, coupled with an increasingly extensive use of technology, have profoundly altered the priorities and needs of customers approaching retirement. However, insurance products and their sales models have not kept pace with these changes.

Capgemini’s research highlights that customers’ preferred choices for financial planning and well-being in aging are, in order: banks (25%), financial advisors (24%), government officials (19%), and lastly, insurance agents, with 13%.

The strongest customer needs in the life insurance sector today are financial planning and maintaining their standard of living, rather than the traditional “succession” need, which focuses on intergenerational wealth transfer and is where insurers tend to concentrate their efforts.

Other reasons for the ‘disconnect between demand and supply in life insurance include:

  • Excessive complexity and standardization of life insurance products.
  • The burden of bureaucratic work and document collection.
  • A product-centered, ‘offer-driven’ approach that lacks personalization for customers.
  • The perception is that insurance agents are not seen as wealth planners.
  • Inadequacy of old insurance products in addressing new customer needs and expectations.
  • Delays in integrating physical and digital channels and adopting data analytics


The Solution: Artificial Intelligence to Put Customers (and Agents) at the Center

The advent of the digital age has dramatically altered the foundations of trust relationships with customers. While in the past, relationships were solely built on interactions with agents, and customers were loyal, often remaining for decades, the digital era has brought about intense competition. Today, consumers can research and make insurance decisions even before contacting an agent; they expect online options, personalized products, and experiences.


Insurance agency networks are and will continue to be the core of insurance distribution

Insurance agents have a deep understanding of their clients and their lives, and this is even more significant in rural areas and outside major cities. An insurance agent not only knows the marital status of their clients but also when they might have a child, buy a house, retire, and so on.

Furthermore, agency networks are associated with well-established and recognized insurance brands. The challenge for today’s insurance companies is to meet the specific needs of consumers at the most relevant times and in the ways that matter to them.

The promise of artificial intelligence is to create a ‘virtuous’ system by combining the knowledge of insurance agents with insights gained from digital interactions.

Transforming Insurance Agents into ‘Super Advisors’ with AI

  • Creating a Customer DNA by Combining Analog and Digital Data. The data held by insurance agency networks, often of high informational quality (think of data from IDD profiling, for instance), must be integrated with data from various digital channels. Agents should have access to all customer data, history, interactions, and preferences at any time. Customer profiles and knowledge of their needs and goals serve as the foundation for more personalized interactions across all channels.
  • Planning ‘Insurance Well-Being’ Together
    In reality, life or health insurance is nothing more than a legal and financial ‘wrapper’ for a promise of security and peace of mind. An AI-based personalization platform allows for the specific definition of each customer’s needs, their main tendencies, and the measurement of how well these life needs are met by the products they already have. The customer’s insurance wellness can be quantified. This allows insurers and customers to work together in a planning perspective with shared objectives.
  • Enhancing the Quality of Insurance Agents’ Work
    A recent BCG study on the impact of generative AI in the insurance sector estimates that insurance agents spend about 35% of their time retrieving information on existing policies, contract terms, and other types of documents. With the help of AI, document collection and ‘bureaucratic’ tasks can be automated, freeing agents from mundane and repetitive tasks and allowing them to focus more on their clients.
  • Tailored Policies and Pricing
    Through systematic customer data collection and the application of machine learning techniques, insurers can generate personalized policy options, aligned with the specific preferences, lifestyle, and risk of each individual. There are already health (and even auto) insurance policies that offer discounts to customers with virtuous behaviors in terms of lifestyle, such as healthy eating, not smoking, and regular exercise. What makes this personalization possible is not the generosity of the insurance companies but the fact that the risk of a virtuous customer is significantly lower. Looking at companies like the US digital broker ModernLife or the Italian operator ViteSicure, it’s clear that the path to personalizing life insurance is not futuristic; it’s already a reality.


The Wealthype solution: a Business Case

If you take a look at our website, you’ll discover that we’ve developed an AI-based platform that, by leveraging data, enables complete service personalization for networks of banking and insurance advisors.

Back in 2018, when AI and data analytics were not as prevalent, our team had designed a platform to transform a network of agents specialized in selling auto insurance into financial planners focused on retirement and life insurance products. Although the project was not completed due to strategic reasons (the company was acquired), a project of this kind is more achievable than ever today.

At Wealthype, this is precisely what we focus on, and we have already helped thousands of advisors improve their work. For a demo of our tools, you can contact us using the link below and discover how to apply Machine Learning principles to your business processes.