Three ways AI is shaping wealth management
The perception of artificial intelligence (AI) and machine learning (ML) in wealth management is changing. Both those who thought AI had no place in wealth management and those who thought AI would completely take it over were wrong. AI and ML have become essential tools for wealth managers to add value to their business. From selecting and managing the investments themselves to operating a more efficient company and enhancing customer experience, AI is now impacting all facets of wealth management. It provides insights on investments and potential investments, enables the automation of previously tedious tasks and allows for personalized and targeted customer experiences.
Augmenting and automating investment insights
AI enables data-based decision making for selecting and managing investments. As more and more data are collected from every facet of life, ML models can improve the use of current data sources and also integrate novel and unique data sources not previously used to inform investment decisions. A ML algorithm could use pattern recognition to make market forecasts and find trends not perceptible to humans. ML models could also use natural language processing to automatically summarize financial reports. These automatically produced results can be easily displayed through dashboards and reports, providing timely and actionable insights to decision makers.
Enhancing recommendations for clients
In addition to allowing for more data-based decision making, wealth managers can also use AI and ML to strategize which products would be the best fit for a client. Clients have different personal preferences, risk appetites and goals. Well-built AI and ML algorithms can create a client profile and use their persona to recommend wealth management products and strategies, creating a more personalized experience.
Increasing office efficiency and security
ML and AI products can automate manual, time-consuming processes, which frees wealth managers and analysts to focus on higher-level investment decisions. For example, AI and ML algorithms can be trained to automatically generate client reports, monitor and report suspicious activities or answer questions from analysts that might have previously required human interaction.
AI is changing all aspects of how wealth managers conduct business but not in a way that replaces humans or takes advantage of clients. Rather, AI takes on the behind-the-scenes work, providing automation, efficiency and insights for decision makers. As a result, companies that do not adopt AI and ML technologies may fall behind. AI takes data, expertise and effort to build and train effective models and algorithms, but when this technology is properly deployed, it can increase returns for everyone.