It’s a familiar story: a client has a question on a particular product feature, tax quirk with a specific account, a special requirement regarding a particular asset class or which form to use for a transaction. You’re not sure of the right answer so you call your firm’s help line. The friendly support person on the other line isn’t immediately able to provide a definitive answer. You call again. This time you reach someone who gives one answer. Again, you call a third time, and receive another answer.
A day or two later, you’re no better positioned to address your client’s question than before you started. The user-support merry-go-round commonly frustrates financial advisors as they strive to serve their clients.
Artificial intelligence can offer a better way.
AI may seem like the far-off stuff of science-fiction stories, but nothing could be farther from the truth. AI for the wealth management industry can address the limitations that plague the current model—typically consisting of teams of support staff sitting in a call center, answering calls and emails as they come.
Greater Efficiency
Onboarding of a new advisor is a routine task for wealth management firms, yet it’s crucial to get it right, for the firm, the advisor and their clients. The process of transmitting client information over to a new firm, opening new accounts and moving assets to new custodial and clearing platforms traditionally requires a number of support staff. Support teams in our experience deploy three staff members, on average, to shepherd the advisor through the process.
Setting aside whether this approach leads to good transition experiences for advisors and their clients, the obvious question is whether the work of three employees—each of which entails outlays for salary, benefits and other costs—can be done by two or even one staff member.
AI algorithms can fill the gap by providing support staff, and advisors, with answers and guidance to common and uncommon questions. It can also mitigate the problem of repeated calls to answer the same question by providing accurate, appropriate responses that are consistent, no matter how many times an advisor asks for help or how many support staff members they consult.
This frees support staff to handle more complex inquiries that would challenge an algorithm’s abilities. In the long run, using AI to handle these more routine questions can reduce the need for firms to have the support headcount they typically have employed. AI can trim down that 3-to-1 ratio to something closer to 1-to-1 and, perhaps in a more distant future, eliminate the need for support staff altogether.
More Streamlined User Experience
Younger advisors and clients today are much more comfortable independently hunting online for answers to their questions than previous generations. If they call for help from human user support at all, they’ll only do so as a last resort, after they’ve run into a roadblock in their own search.
For better or worse, digital natives believe that they can get better answers faster if they use Google or some similar algorithmic system. They’re right. Google, Facebook, Netflix, Apple and Amazon have built empires on their ability to use data to understand user desires and return information that suits their needs.
AI-powered user-support systems in the form of digital assistants, chat bots, phone avatars or otherwise, fit more seamlessly into these users’ experience than the traditional call center-centric model. If these systems’ algorithms have been trained well, they can provide advisors and clients the right answers in the way they want to receive it, with minimal human interaction. If they aren’t able to fully address more complex requests, algorithms can be trained to route users to the most appropriate human expert. Such “smart routing” enables firms to prioritize the attention of their human support staff members where it’s truly needed.
It all adds up to a faster, more streamlined experience for all involved, as well as higher user satisfaction, reflected in higher customer satisfaction measures.
Greater Productivity
For advisors there’s an opportunity cost for each hour they spend addressing questions. Instead of creating new value for clients or performing tasks to generate revenue for themselves, they’re ferrying questions and responses between support staff and clients.
For example, if an advisor is performing due diligence for a particular investment vehicle, each hour they spend in limbo is a delay in making a recommendation for a client or, particularly for commission-based reps, executing a transaction.
AI can streamline the due diligence process by reducing the time advisors spend learning about products, enabling them to be more productive. Form automation is a prime example of users receiving help from an AI algorithm to discover, pre-fill, e-sign and submit forms, with near-zero error rates. By connecting process automation systems to conversational digital assistants, financial firms can take their efficiencies to even greater levels.
On a more basic level, AI-driven support systems have an advantage that traditional call centers lack: they are always available and not limited by the work schedules of human support staff.
The Time Is Now
Repeated calls for support waste time and resources, create unnecessary headaches for advisors and their clients and sap advisors’ productivity. One solution is better training for call center staff and advisors on the intricacies of the operations they need to know to serve their clients well. AI can be leveraged to reduce the time and resources firms must devote to the training process.
Yet in the long run, better training may only have incremental benefits for the quality of advisor support and its efficiency. Changing the entire system to take advantage of AI-enabled technology gives advisors more time to build relationships and increase sales and asset levels, enabling growth for the financial firm in the longer term.
At a moment when AI is already changing the way consumers shop or how employees do their jobs and leaders plan the future of their organizations, the time to apply this technology to advisor support within the wealth management industry has arrived.
Dr. Sindhu Joseph is the founder and CEO of CogniCor, an AI-powered digital assistant platform for financial firms. She earned a Ph.D. in AI, holds six patents and is an author and speaker on topics around enterprise AI and the need for diversity across the tech industry.