The Asia InsurTech Podcast spoke with Tom Gerritsen, Head of Group Data Analytics at AIA, about the impact and implications of AI in the insurance industry. Tom highlights AI as the most significant emerging trend in insurance and insurtech with transformative capabilities for customer engagement and business operations.
Tom perceives the launch of OpenAI’s ChatGPT as an “iPhone moment” for AI, democratizing its usage, although he notes that many businesses are yet to fully integrate AI into their operations.
At AIA, Tom’s team uses AI to personalize customer interactions and assist in agent hiring. The team envisions AI supporting insurance agents in real-time, providing data-based insights during customer interactions. Tom also emphasizes the critical role of data quality in achieving accurate and useful AI outcomes, advocating for continued improvements in this area.
The discussion also extends to AI’s impact on business aspects like decision-making, fraud detection, and localization, underlining AI’s capability to optimize efficiency and streamline processes. Gerritsen shares how AIA has leveraged AI to expedite their claims process and improve fraud detection, with AI handling a majority of customer interactions.
The conversation concludes with a discussion on AI’s potential in personalized marketing, the significance of compute power accessibility in enabling comprehensive data analysis, and Sam Altman‘s statement about the decreasing marginal utility of adding more data to large language models, suggesting a shift towards identifying real use cases for AI.
Topics we discussed:
- Emerging trends in insurance and insurtech, focusing on the increasing application and impact of AI.
- AIA’s use of AI for enhancing customer interactions, agent recruitment, and claims processing, and the role of data quality in these processes.
- The influence of advancements in AI, such as OpenAI’s ChatGPT, on business operations and their acceptance.
- The potential and challenges of AI in creating hyper-personalized marketing and products, and its role in localization and error prevention.
- The implications of increasing computational power and bandwidth on data analysis and the broader use of AI.
- The future direction of AI technology, including a shift towards real use cases and hybrid customer service models, combining human agents and AI.