The promise of sexy new technologies such as artificial intelligence for the wealth management industry has been covered extensively — so much so that we are still wondering when the hype stops and reality starts so that it will actually help advisors do a better job with their clients and their businesses.
The theory goes that by harnessing Big Data, AI applications will provide predictive analytics to help advisors be more proactive at the advice and service levels.
For example, an AI bot can monitor the activity of a client's usage of a client portal to detect any patterns that would indicate they are at risk of leaving, such as logins at weird hours of the night, frequent checking of performance reports, subsequent money movements and other actions.
By comparing this activity with that of other clients who have left, the AI bot can identify a list of potential defectors and send an alert to the advisor to check in with the client and see if there's anything they can do to hopefully alleviate the situation, save the account and keep the client.
Other much-hyped applications that AI can deliver are through the mining of Big Brother databases to anticipate client life changes such as sales of businesses, marriages, divorces, deaths, births of children, etc., to predict future financial planning and investing needs.
Through this type of application, advisors will receive alerts from the AI bot to identify which of their clients and prospects will soon need their expert planning and investing advice to capture the "money in motion" caused by the life event to gather incremental assets and generate new revenue, all while enhancing service levels.
This all sounds cool and sexy in theory, and as a result has captured the imagination of C-suite executives, analysts and technologists industrywide. The reality, however, is that this type of AI works only when it can harvest massive amounts of data from millions of accounts, making it still out of reach to the average advisory firm that is serving just a few hundred households.
But Wait …
The good news, however, is that AI and its corollary technologies, such as machine learning (ML), natural language processing (NLP) and robotic process automation (RPA), are ready for prime time in wealth management with much more immediate results. These benefits, however, reside in the back office of advisory firms, not necessarily in the front, and can dramatically affect an advisory firms' operations, compliance and administrative workflows — all of which are essential to improving service in a highly competitive service profession.
This is critical because while back-office employees typically do not interact with clients directly, 60% of client dissatisfaction originates from back-office service interactions and not necessarily from their advisor. Because workflows in wealth management operations are repetitive, data-based and labor-intensive, the back-office is a great candidate for AI and its cousins RPA, ML and NLP to drive workflow automation.
For example, according to CapGemini, RPA in the back office can reduce 70% of the cost of a full-time employee, providing a quick and tangible ROI to advisory firms.
Some of the applications of these workflow automation technologies may seem simple, yet they can dramatically increase capacity in advisory firms. Consider client meetings as an example. Advisors often have hundreds of client meetings in a year, and just scheduling, confirming and preparing for those meetings can bog down advisors and their staff on a daily basis.
By combining AI and NLP, virtual assistants (e.g., your own Siri or Alexa) can be programmed to automatically check the firm's CRM for upcoming meetings, send an advance digital communication out to the client (either email or text) to coordinate, confirm and get the meeting scheduled on the advisor's calendar without any staff involved.
