The world of insurance underwriting has been a steady and unchanging force for over four centuries. It’s a domain where risk assessment and pricing are deeply rooted in historical data, often locked away in PDFs and traditional actuarial models.
I’ve explored this in previous years, however, the winds of change are finally blowing, and they’re bringing with them the promise of a transformative shift with the integration of AI into the underwriting workflow. This is not just about automating tasks; it’s about reimagining the entire underwriting process.
Today, underwriting remains as much about navigating a labyrinth of often inefficient technology and processes as it is about assessing risk. Underwriters are often bogged down by manual data entry, poor access to underwriting information, and limited analytics capabilities. These tasks consume valuable time that could be better spent on core activities where underwriters’ expertise truly adds value for both the insurer and the customer.
A New Chapter
Despite these challenges, there is a growing sense of optimism as carriers actively test and explore AI technologies in a bid to change the role of underwriting for the better.
According to Accenture’s latest survey of underwriting executives, executives expect the use of AI-driven capabilities to considerably accelerate over the next three years, from 14% who use it today to 70% in the next three years. By integrating AI, including gen AI and agentic AI, insurance companies can enable faster time to market, achieve higher conversion rates and drive business growth. The potential productivity boost is significant, with some estimates suggesting a 22-30% increase.
However, the benefits extend beyond just efficiency increases. AI can help underwriters make more accurate and consistent decisions, reducing the risk of errors and omissions. It can also enhance the customer experience by providing more personalized and relevant insurance products
Going Beyond the Hype
The goal is to create a seamless and efficient underwriting process that leverages the best of human expertise and AI capabilities. For example, broker-facing chatbots and virtual assistants can handle routine inquiries, freeing up underwriters to focus on more complex work. Comparative analytics can help underwriters evaluate risks based on peer groups, providing a more holistic view of the market. Triage analytics can prioritize work and submissions based on risk and win capabilities, ensuring that underwriters are working on the most critical cases.
We’ve already seen insurers make notable progress. Intact Insurance UK is using AI to enhance underwriting by automating manual tasks, providing smarter risk insights, and accelerating decision-making. AI-powered data ingestion can process submissions at scale, identifying trends and unmet market needs, leading to improved risk selection, pricing, and product innovation, while complementing human expertise.
Additionally, Specialty insurer Hiscox is collaborating with Google to deploy machine learning and AI across its business. One successful proof of concept, and now scaled solution, has been in the use of ‘augmented underwriting’ in the submission processing for sabotage and terrorism process – taking that time from three days to three minutes and improving productivity by 40%. The use of this AI framework is being expanded to other business lines and other markets, enabling faster growth and increased efficiencies.
Taking it to the next level, Agentic AI can streamline underwriting by handling non-core tasks and making autonomous decisions, allowing underwriters to work more efficiently by collaborating with AI agents and delegating tasks effectively. We expect to see scaled innovation in the deployment of agentic AI announced in the coming months as the industry works on pilots and use cases.
A Holistic Approach
To fully realize the benefits of AI in underwriting, insurers need to take a holistic approach. This means not only integrating AI into the underwriting workflow but also addressing the broader issues that have hindered productivity and transformation. The first step is to break down siloes and foster better collaboration across teams. When data is shared freely and everyone is working towards the same goals, the entire process becomes more efficient.
Finally, insurers need to create a culture of continuous learning and development. Underwriting executives need to ensure that the AI tools they adopt are not just bolted on to existing processes but are deeply integrated into the workflow. It is not just about training; it’s about fostering a mindset that embraces innovation and new ways of working. Underwriters will need to develop new skills to complement the capabilities of AI, ensuring that the human face of underwriting is preserved even as the process becomes more automated. It’s not enough to have the technology; you need to have the people who can use it effectively.
A New Era for Underwriting
The digital renaissance in insurance underwriting is not just a possibility, it’s a necessity. The industry must break free from its historical constraints and embrace the future by combining the best of human expertise with the power of AI. By doing so, insurers can dramatically increase the volume of policies that they assess and improve accuracy and consistency of decision making.