As insurers confront shifting demographics and rising expectations, AI is redefining how they manage complexity and deliver value. Liu Chun Yen, CIO at AIA, explained how artificial intelligence is helping her company scale personalization – enabling portfolios to evolve with customers’ life stages across millions of policyholders. As customers move through different stages of life, their investment needs evolve – from wealth accumulation to decumulation. Traditional models that fix asset allocations at inception can’t keep pace with clients’ evolving needs. For AIA – with products sometimes spanning three generations and liabilities extending over two centuries – static approaches simply don’t work.
AI has become essential to solving this. As Liu explained, her team could already tailor portfolios for one or two groups of customers – but doing so across AIA’s 23 million policyholders requires technology that can extend and scale human expertise. AI-driven models now enable dynamic allocation adjustments as clients move through life, aligning assets and liabilities across markets, currencies, and time horizons.
This same drive for intelligence at scale is also reshaping risk management. David Chua, CIO at Income Insurance, described using machine-learning models to test investment biases and ensure consistency in decision-making, while Allen Kuo, CIO at SingLife, shared how large-language models are improving credit watchlists and risk reporting by automating data checks and surfacing hidden patterns.
Together, their experiences show how insurers are using AI to extend human expertise – scaling personalization, judgement, and hedging.
Bloomberg’s integrated data and analytics bring true workflow efficiency to insurers – linking asset, liability, and data systems to enable seamless hedging, allocation, and reporting.
