In a volatile industry, to meet the challenges in portfolio monitoring and reporting, asset and wealth management firms need to innovate via the adoption of AI-based digital tools and data analytics.
While some investors prefer expert financial advisors to help rebalance their portfolios, others are seeking self-guided methods. That creates opportunities, and at the same time, challenges for wealth managers to develop novel services that can serve the needs of both segments, requiring a shift to remote/hybrid ways of consultation provision. As a result, apart from improving expertise, asset and wealth management firms should prepare digital portfolio management and data analytics tools to boost productivity. By investing in AI adoption, managers can perform portfolio monitoring and reporting more efficiently.
In this blog, we discuss how AI involvement in portfolio monitoring and reporting can assist asset managers.
AI bolsters goals-based asset allocation
Research by Cerulli Associates shows that investors appreciate an understanding of their needs and goals, a holistic overview and a willingness to explain analysis above all else when seeking an advisor. Wealth managers are facing challenges in interpreting clients’ philosophical goals, creating strategies to achieve them, then break those down into a tactical approach to ensure investment portfolios remain as appropriate for clients’ needs as possible.
An intelligent engine can track courses of action, gather all the information and documents that are required to understand both the markets and the clients. By establishing AI-powered portfolio monitoring and reporting tools enabling automatic risk reviews, suitability evaluation, pre-trade checks and investment opportunities analysis, firms can refine goals-based advisory solutions customized to every client’s needs.
“Mentally processing all the existing and new client information to arrive at the right recommendation for them can be incredibly complicated with many moving parts,” said Greg Davies, Head of Behavioural Science at Oxford Risk. “AI can dynamically process that information in real-time and do all the data juggling to present the advisor with the most accurate, holistic portrait the firm has of the client at that moment.”
AI strengthens informed decision-making
The value of AI in portfolio monitoring and reporting is less in the computer ‘giving the answer’ and more in it acting as a support tool helping in decision-making. Whether it is a decision made by clients or wealth managers, AI integration in portfolio monitoring and reporting tools can equip them with timely, accurate and relevant information. A myriad of internal and external sources, structured and unstructured data will need advanced data analytics relying on machine learning processing power for finding proper insights.
In portfolio management, AI-based tools are being utilized to find useful trading patterns and movements, detect volatile markets and better market research than with conventional methods, allowing examination of both potential risks and returns.
For example, during portfolio monitoring, the data collection and analysis of public filings augmented by natural language processing can increase efficiency in research and would be a step toward well-informed investment decisions. AI is also particularly helpful in pulling a lot of information and doing analysis fast to support decision-making of investors who increasingly consider the environmental, social and governance-related impact of their investment.
AI reinforces the ability to react quickly
Instead of being done periodically, with help from AI, portfolio monitoring can be performed frequently to continuously, and real-time reports can be provided shortly after investors’ queries. Useful insights derived early from AI and machine learning-powered tools may become valuable for clients to gain an edge over other investors.
Moreover, although in portfolio planning, asset allocation has been decided, it is usually impossible to implement the predefined strategy exactly. Market changes and price fluctuations can lead to deviations from the strategic asset allocation. Since it is important for investors to stay as close to the planned allocation as possible, they need timely reports to respond fast. AI-based portfolio monitoring can notify wealth managers and investors via digital channels whenever the asset allocation needs rebalancing.
Recently, while the number of self-directed investors is expanding, we should be aware that investors, especially those in the ultra-high net worth segment, will be best served by their trusted wealth managers augmented with more powerful portfolio monitoring and reporting tools. To achieve that, firms should explore equipping their portfolio managers with AI solutions so they can effectively monitor portfolios.
If you’re interested in learning more about how AI adoption drives efficiency in Asset & Wealth Management, download our whitepaper, “Driving Middle and Back-Office Efficiency in Asset and Wealth Management”, or visit our website to explore our AI solutions that firms can apply.