AI has recently been thrust into global headlines with the rapid growth of OpenAI’sChatGPT software, which has now prompted companies like Google and Tencent to begin developing their own versions in-house.

AI is a buzzword that is thrown around a lot and has wide applications outside of NLPs (natural language processors). We’ve seen it being used to write content, create videos, edit images and a recent McKinsey article has effectively visualized how this broad stack of technology can be used specifically by wealth managers in servicing clients:

We’ve looked into some of the different ways these technologies are already affecting the broader wealth and asset management space, and will increasingly do so as it improves:

1. Improved investment decision-making:  AI can analyze large volumes of data and identify patterns and trends that     would be difficult for humans to spot. It can also help remove narratives that exist from decision making, as the AI will produce digestible data without harbouring certain biases that can be seen in people. This can help wealth and asset managers make better investment decisions by identifying opportunities that they might have missed otherwise, or at the minimum give them a broader view of all relevant factors before moving ahead with their decisions.

2. Enhanced risk management: AI can help wealth and asset managers better understand and manage risks by analyzing data from multiple sources and identifying potential threats to investments. Again, AI’s ability to sift through the weeds and give people the data they need around risk management can help them make more informed decisions about which investments to make and how to manage their portfolios.

3. Servicing Clients: as referenced in the McKinsey graphic above, AI-powered tools delivered via mobile platforms, can     make digital channels far more engaging. Apps can also make analytics-driven investment recommendations, show asset allocations for various portfolios, help clients optimize portfolio risk, offer client-specific portfolio rebalancing, and identify the next best product for clients to consider.

4. Automation of routine tasks and improved efficiency: AI can automate many routine tasks, such as data entry and     analysis, freeing up time to focus on more strategic tasks, for example identifying new investment opportunities or developing long-term investment strategies.

5. Increased competition: AI is enabling new entrants to the asset and wealth management industry such as robo-advisors (e.g. Wealthfront), which are offering low-cost investment advice and portfolio     management services using sophisticated algorithms. This is increasing competition in the industry and forcing traditional asset managers to     adapt and innovate to remain competitive.

6. Expense management: AI-powered analytics can curate historical spending with recommendations for how to optimize spending, savings, and budget allocation.

AI is expected to have a significant impact on the investment industry, enabling people to make better investment decisions, manage risks more effectively, operate more efficiently, and compete in an increasingly crowded marketplace. Innovation in this space will see it have an increasingly significant impact on how people manage their own and their clients’ money. Watch this space for more investment AI based content.

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