The GenAI revolution in insurance – how carriers can deploy widely based on strong governance

EY’s Anita Sun-Young Bong, Ed Majkowski and Phil Vermeulen examine the impact of GenAI on the (re)insurance sector.

Few, if any, technologies have achieved mass adoption in a shorter period of time than ChatGPT, thanks to its massive accessibility and highly intuitive interface. Not only has ChatGPT harnessed the extraordinary power of generative AI (GenAI), but it’s also incredibly easy to use. That’s why GenAI will be adopted widely across the business, and why strong governance models are necessary to guide adoption as the technology is democratised.

Insurers are already using GenAI to automate processes and integrate diverse datasets, analyse customer behaviour and tailor marketing communications. In actuarial and underwriting, GenAI streamlines the ingestion of large datasets, freeing underwriters to focus on high-value analytical and risk assessment work. In IT, cyber teams use GenAI to analyse operations data for attempted fraud, monitor network security and document attacks for regulatory reporting.

More sophisticated deployments are not far away; smarter “co-pilot bots” will make knowledge workers in underwriting, actuarial and claims even more productive. GenAI will streamline decisioning in life insurance underwriting, replacing today’s lengthy application processes. It will automate many compliance and risk management activities. Translation and regeneration of code across languages is potentially transformative for carriers with COBOL-based applications.

The biggest impacts will come in customer-facing operations. More precise analysis of market trends and customer sentiment will enable insurers to personalise and, ultimately, individualise customer experiences. Virtual sales and service agents will soon be able to resolve complex issues and provide tailored advice and even a personal touch in digital channels. AI-generated recommendations for next-best actions will enable call centre reps to have more empathetic customer conversations, rather than simply collecting information. Such “human-in-the-loop” processes are among the most compelling use cases.

Optimising adoption and ROI via effective governance

To boost returns on their investments in and promote responsible use of GenAI, insurers will need to deploy widely across the business and develop robust governance frameworks.

Embedding GenAI more deeply within products, processes and applications requires adding new data (including content and images) and integrating existing data sources into the AI models that produce quality outcomes. Insurers must design and manage those models carefully, ensuring that outputs are accurate and that customers’ confidential data is protected at all times. Monitoring third-party data feeds can help minimise the risk of data breaches and the introduction of “bad data”.

Insurers will also need new talent (e.g., prompt engineers). AI “factories” or technical centres of excellence (CoE) can centralise scarce skills and promote organisational policies and ethical standards. CoEs can also provide change management support by communicating the “why” behind adoption and the “how” of implementation.

Robust governance frameworks are essential for responsible usage of GenAI – that is, in alignment with ethical business objectives, company values and compliance with regulatory requirements. Given the interconnected nature of GenAI applications, the complex ecosystems in which they will be deployed, and the need to scale, insurers will need ever more sophisticated controls. Such a controlled approach to adoption won’t be easy, but it’s the right way to democratise high-impact technologies, such as GenAI.

Anita Sun-Young Bong is EY Asia-Pacific insurance sector leader

Ed Majkowski is EY Americas insurance sector and consulting leader

Phil Vermeulen is EY EMEIA insurance leader