AI techniques are increasingly being used in retail investor analysis and advisory tools. By capturing complex non-linear relationships and incorporating unstructured data such as text and images, they can better reflect the multiple factors that drive investor behaviour.
Key takeaways
- AI is transforming retail investor analysis and engagement, enabling deeper behavioural insights, more accurate segmentation and personalised advice.
- Behavioural analysis and clustering of individual investors, together with Large Language Model (LLM)-based synthetic surveys, offer new ways to understand investor preferences and test communication strategies, supporting more tailored and responsible communication.
- Robo advisors and recommender systems, LLM-powered chatbots and mailbots enhance investor communication and decision making, while improving efficiency for asset managers.
You can now read the full whitepaper at the link below
