While most insurers have started to implement AI, few are benefiting from the technology across all business processes. Carriers that take a domain-based approach focused on how each business area — such as claims, underwriting or distribution — can be optimized by AI, have shown the best results so far, McKinsey said in a report released last month.
This approach has helped insurers increase new agent sales conversion rates by 10% to 20% and grow premiums by about 10% to 15%, the consulting firm said.
In life and health insurance, natural language processing can help in sales activities, such as creating personalized outreach and conducting product research. Cognitive AI can then respond to prospective clients’ questions. Once a deal is made, robotic process automation can reduce human labour in form-filling and customer enrolment. During the policy’s lifetime, machine learning can be used in cost and risk reduction, such as fraud prediction and litigation reduction.
McKinsey notes that over the past five years, AI leaders in the insurance industry have produced a total shareholder return (TSR) 6.1 times higher than that of laggards. In other sectors, this lead is only two or three times.
The report identifies three major AI disciplines that can apply in the insurance industry:
- traditional analytical AI to identify patterns in data;
- generative AI, which enhances these capabilities through a better understanding of unstructured data patterns and allows for the addition of hyper-personalization and empathy in responses; and
- agentics, which can add unprecedented levels of automation to complex workflows.
Armed with this versatility, insurers are using AI in all key areas, including sales productivity and hyper-personalization; underwriting automation and accuracy improvement; improved claims management; customer service operations with voice agents; and transformation of back-office functions such as finance; actuarial and information technology (IT).
To get the most benefit from AI, the executive team needs to recognize it as an opportunity to grow the business, not just as an efficiency tool, McKinsey said. The leadership must align AI outcomes with measurable business goals and create a clear road map for how AI use can be aggregated in each business area rather than scattered across individual applications.
A major advantage of AI that can facilitate and accelerate its implementation is its reusable “modularity,” McKinsey said. The same underlying AI engine can be used in a wide variety of practical applications. For example, a generative AI capability can be applied to IT support, marketing content creation or legal document drafting.
At the employee level, the report recommends that about 80% of insurers’ digital talent should be in-house. A specialized human resources team can help attract and retain workers skilled in adopting technology, it said.
The report also notes the insurer’s technology stack should be scalable and flexible enough to support multiple AI applications. This will help the insurer quickly adopt new technology as it becomes available. Data should be embedded throughout the organization to make full use of institutional knowledge.
With files from Finance et Investissement.