Artificial Intelligence (AI) can increase speed to market, firm’s profitability, improve service offerings and wealth advisor-client relationships and lastly business outcomes. Since AI can provide recommendations to advisors and directly to the clients in setting goals and in investing there is a vast realm of possibilities to speed up processes that can take a human advisor far longer. In financing sector financial institutions are already harnessing the potential of AI to solve challenges related to investment advisory, risk management, regulatory compliance, and prediction of markets.
With cognitive technologies, wealth management and advisory business have transformed vastly. AI can build the classification models in such a way that it can classify each investor to a particular investment strategy class, highly customized for investors with similar profiles and goals. This omits the need for a human advisor. AI models do this in an efficient and scalable way enabling firms to attract new investors, retain the existing investors, reduce operational costs, and stay ahead of the competition. Rebalancing portfolios with changing global markets and financial goals are also possible using these models.
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A part of natural language processing, sentiment analysis can have a multitude of applications in the investment domain. By scanning and analyzing various written and verbal client communication medium, firms can better understand customer sentiments. As a useful tool, more profound insights can be generated by highlighting the sentences and keywords behind strong emotions.
Robo advisors can help automate essential advisory functions assisting investors’ various needs. Soon, robo advisors would be built on self-learning algorithms. Robo advisors allied with a virtual assistant can make investment journey of the client a satisfactory one. They would offer sophisticated services like automatic portfolio rebalancing, asset class switching based on global macroeconomics, portfolio risk management and harmonizing other aspects of investment strategies in real time basis.
AI models in wealth management are used for enforcing regulatory compliance and manage risk more efficiently. These models can flag an order if it belongs to a class of bad trades or belongs to a high-risk category for pre-trade compliance checks.
While allowing firms to unleash insights and bring efficiencies, investment in AI and cognitive technologies in wealth management is inevitable and will grow exponentially in the coming years.
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