HSBC Private Bank launches Wealth Intelligence generative AI platform to deliver personalized investment insights at scale

Private banking clients increasingly expect their advisors to deliver timely, personalized investment guidance. HSBC Private Bank's client-facing bankers, investment counsellors, and product specialists work in rapidly evolving markets while managing deep client relationships. The bank's Chief Investment Office produces a comprehensive range of research reports.

HSBC Private Bank developed Wealth Intelligence, a proprietary generative AI ecosystem built by its in-house developers and powered by OpenAI's Large Language Model (LLM). The system analyzes and summarizes content from more than 10,000 data sources and offers fast, simple access to the reports published by the bank's award-winning Chief Investment Office. Third-party product information will be progressively integrated. Deployed initially across Hong Kong and Singapore for client-facing roles, the platform is to be scaled to more markets. In the next stage, it will be capable of screening and identifying suitable products so that wealth management teams can discuss investment options and asset allocation recommendations with clients.

Wealth Intelligence launched in September 2025 across Hong Kong and Singapore, with a planned global rollout to follow. Wealth management teams can now access synthesized market intelligence across 10,000+ data sources, freeing time for client interactions.

• Research synthesis automated across the full CIO report library and third-party feeds
• Staff augmentation across client-facing bankers, investment counsellors, and product specialists
• Geographic rollout planned from the Hong Kong and Singapore launch markets to more markets globally
• Positions HSBC wealth teams to deliver more personalized, data-driven investment conversations at scale

Qualitative outcomes include talent upskilling and transformation of client journey workflows, as cited by Lavanya Chari, Head of Wealth and Premier Solutions.

• Build proprietary on top of leading LLMs rather than deploying off-the-shelf tools.
• Phase deployments by capability, not geography alone: starting with research summarization before advancing to product screening.
• Position AI as a talent multiplier, not a replacement — the bank frames the platform around upskilling its wealth management talent and transforming workflows.