How insurers can use AI to help close the coverage gap

More than four in 10 American adults (42%), or about 102 million people, say they either don’t have life insurance or need more of it — a two point rise since 2021, according to LIMRA. 

Artificial intelligence can help close that gap by enabling life and annuity (L&A) insurers to lower costs while expanding product accessibility. However, just 21% of insurers say they have advanced data analysis capabilities, while only 19% use AI and machine learning, according to Capgemini.

To close the coverage gap, boost growth, and improve the customer experience, it will be crucial for L&A insurers to not only increase their use of AI and modernize processes — but to ensure they’re leveraging this technology in areas that will drive long-term growth and profitability. 

Transforming distribution

Although digital direct-to-consumer (D2C) platforms have increased in popularity, more than 90% of L&A insurance is still distributed through agents and advisors. By utilizing AI, L&A insurers can make the product distribution process more efficient and consumer-centric without sacrificing quality of service.

Streamlined data collection

One of AI’s immediate impacts lies in optimizing data collection and administrative tasks. Currently, agents spend a significant amount of time manually gathering information and completing paperwork. AI can alleviate this burden by automating data entry, ingesting and parsing information from numerous sources, and even conducting initial interviews with clients. This allows agents to focus on what they do best — offering personalized advice and building relationships with potential clients.

Improved underwriting efficiency and efficacy

For both carriers and distributors, AI can help enable a more efficient and robust underwriting process.

On the carrier side, AI can gather data from multiple sources to help underwriters make quick and more informed decisions. For distributors, AI can help to expedite these decisions while offering insights that allow them to understand the outcome of each case and improve their own screening process accordingly. 

Targeted product recommendations

AI can also provide product recommendations. Rather than relying solely on an agent’s experience or intuition, AI systems can analyze vast amounts of data to suggest the most relevant insurance products based on its configuration and underwriting rules. This ensures that policyholders receive coverage suited to their specific circumstances based on the full suite of products that insurance carriers have in market, helping close the gap between the products people are offered and what fits their needs.

Enhancing the customer experience

Today’s consumers expect fast, efficient, and personalized service. While the insurance industry has traditionally lagged behind other industries in this area, AI has the capability to quickly change that. 

At Zinnia, we’ve experienced this rapid transformation firsthand. Since implementing our proprietary AI-enabled data analytics solution in the company’s call center, we’ve automated several repetitive administrative tasks, including call transcriptions and summaries, quality assurance scoring, and the process of organizing this data into a structured and analyzable format. These automations have helped Zinnia better understand the types of calls coming in, which have led to further operational and customer experience optimizations. In just over a year since implementation, Zinnia has seen significant improvements to both operational efficiency and customer service within the call center.

By leveraging AI in a similar capacity, insurers can both streamline operations and provide its customers with a better overall experience. This consumer-centric approach enables insurers to better understand the needs of their customers and tailor solutions accordingly — ultimately helping to close the coverage gap.

Call transparency

With AI, insurers can generate summaries and transcripts of each call in a consistent fashion, helping agents get up to speed about a caller’s case history in the event of a callback — enabling smoother communication and faster issue resolution. By providing agents with the necessary details instantly and eliminating the need for customers to repeat their issues, this allows for a more seamless customer experience.

Management at scale

AI also plays a vital role in scaling managerial tasks within call centers. Rather than having to manually review a sample of interactions, managers can react to insights generated by AI to spot significant trends, like a high-volume of calls related to a specific inquiry or issue, and highlight specific areas of improvement for agents that need attention. This in turn gives managers more visibility into what is happening in the call center and allows them to refine their coaching programs and get direct visibility into customer feedback and sentiment.

Identification and resolution of key trends

Using AI, insurers can generate data signals that they weren’t capable of measuring before. This can help to identify trends in what people are calling about, how often their issues are resolved, and the pathway reps took or did not take to resolve the issue. 

Automation

Finally, automating customer service can greatly enhance accessibility. AI-powered virtual assistants can provide instant responses to common questions, even outside of business hours. This automation ensures that customers receive timely support, without needing to spend time waiting in a call queue.

Anticipating consumer demand & generating new products

When developing new products, L&A insurers traditionally rely on experience-based analytics and the past performance of similar products. AI is disrupting this model by offering insurers insights into consumer behavior, helping them anticipate demand and design products that meet the evolving needs of policyholders.

Automated product insights

AI can track how consumers interact with existing products, analyzing which features they value most and which ones they overlook. By continuously collecting and interpreting this data, AI can enable insurers to act more nimbly when developing products.

Product generation

Beyond refining existing products, AI has the potential to automate the creation of entirely new insurance products. Through its ability to identify current trends in consumer preferences and market demand at scale, AI can quickly design products tailored to specific demographic segments. This automation speeds up product development, allowing insurers to launch new offerings faster and more effectively.

Product simulation

AI can also help insurers model how a new product will perform without the risk of actually taking it to market. These predictive capabilities will allow insurers to make informed decisions about which features to include or adjust to ensure the product remains relevant given the fast-changing market.

Artificial intelligence can automate administrative tasks and optimize data collection across L&A operations, providing insurers more with streamlined distribution while enhancing the client experience. Further, AI can help insurers develop more relevant products through its ability to analyze consumer behavior and predict future demand or trends. By integrating AI solutions in these areas, insurers can both reduce costs and close the coverage gap.