How cloud technologies can help agents serve more older Americans

Insurance needs become more complicated as people age – and we are aging. An estimated one quarter of the North American and European populations will be over the age of 65 by 2050. (It’s about 17% of the U.S. population, 20% of the Canadian population, and roughly 21% of the European Union’s population today, so we’re not exactly youthful now, either.) The same holds true for the 38 Organization for Economic Cooperation and Development member nations as a group.

An aging population means opportunity for insurance agents, but it also introduces complexity. The over-65 cohort is a diverse group in terms of health status, financial status and lifestyles. The fitness freak’s and the couch potato’s relative well-being, perhaps not so different when in their 20s and 30s, may now be as divergent as the spending habits of the retired CEO and the pensioned schoolteacher – and those spending habits also have insurance implications. In short, increasing age makes age-related generalizations harder, and that makes it more challenging for insurance agents to sell the right products to the right person at the right time at the right price.

Cloud technologies are already making a difference for agents, and they’re becoming more powerful by the day. Agents should expect insurers they represent to get serious about harnessing the cloud to help optimize agent-customer interactions – and, with that, boost sales and commissions – in two key ways.

The first is using generative artificial intelligence to put just the right information about a given customer or prospect and their probable insurance needs at the agent’s fingertips in real-time. The second is providing the back-end analytics that tailor products and services for customers and prospects that GenAI can then access for the agent’s benefit.

GenAI for real-time understanding of customers and their needs

GenAI can be game-changing for insurance agents. It can immediately and comprehensively present an existing customer’s portfolio of products and services, and trigger notifications as products are set to renew or expire. It can suggest product, service and pricing alternatives based on health, income, spending and other data, enabling the agent to quickly present a clear picture of what they can sell and how they can position it. Recent discussions with major insurers hinted at where all this is headed. The aim is to use GenAI to help agents maximize customer interactions – and not miss opportunities because of the difficulty in quickly grasping the customer’s use of the products they have and how they’ve used those products.

It's not far-fetched to imagine future GenAI copilots for insurance agents that combine dashboards distilling a client’s or prospect’s relevant data with GenAI-based natural-language capabilities. Such a system would not only guide conversations with individual clients or prospects, but also be agile enough to adjust potential offerings in real-time as the discussion evolves and suggest language proven to foster sales.

Back-end analytics as engine for an agent’s success

GenAI customer-interaction capabilities depend on cloud-based analytics to predict, understand and satisfy an older customer (or any other customer). In addition to vastly divergent health and income status, the silver set’s combination of wealth and declining health multiplies the number of potentially applicable products and services: wellness programs paired with premium discounts, plans with coverage for in-home or institutional long-term care, annuities, intergenerational plans, coverage and associated programs for chronic conditions, and so on. It’s about personalizing coverage, and that takes analytics.

The goal of such analytics is to synthesize from various data sources a broad-based view of past and current financial status, health, and behavior to predict future health and behavior. Then, based on that, GenAI can bring associated insurance products and services to the fore when an agent needs it. For the silver set, IoT and an increasing willingness to trade privacy for price breaks will play important roles in amassing the necessary data.

Just as drivers allow auto insurers to monitor their movements, those looking for better deals on health or life insurance will be increasingly willing to trade longitudinal data about their heart rate, blood pressure, blood sugar, cholesterol and other metrics for plans based on individual instead of demographic actuarial risk assessments. That data could come from HIPAA consents enabling the sharing of otherwise private medical information (for bloodwork-related data, for example) or smartwatch/Oura Ring-type heart-rate and movement-related data straight from the patient – the watches or rings supplied or discounted by the insurer.

Cloud-based analytics can harvest from these and other sources (demographic, geographic, spending-related, even public social-media posts) and create much more precise customer/prospect profiles than were previously possible – and have the information available to the GenAI copilots that agents will increasingly rely on.

Agents aren’t in a position to build their own cloud-based GenAI and analytics systems. But they can make sure that the insurers capable of building them, do build them. Harnessing cloud-based data will help agents sell more products and services to a silver population with complex needs. Agents, the insurers they represent, and their customers will benefit.

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Javier Gil is SAP’s insurance industry product marketing chief expert. Contact him at javier.gil@innfeedback.com.