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In August 2023, the Securities and Exchange Commission (SEC) made headlines following the approval of the first AI-powered investment platform as a registered financial advisor.
Given the pace at which AI-centric financial service platforms are being developed and entering the market, the approval of a fully digital and AI-powered registered financial advisor is one of many that are expected to become a regular occurance in the financial sector in the coming years.
This is a prime example of how artificial intelligence is transforming the financial services industry, leading advisors and service agents into a new era of digital excellence, and helping bridge the divide between customers and financial accessibility.
With billions in public and private investments flowing into the AI industry, one critical question many financial advisors are asking is how they can leverage these applications to improve their customer’s experience while maintaining human connections, authenticity, compliance, and accuracy.
Deepening customer connections and predictability
For decades, financial advisors relied on antiquated methodologies to find new clients. Tactics such as cold calling, and strengthening their networks through referrals helped advisors build their client base, however, maintaining these relationships was often laborious and consumed a tremendous amount of time and resources.
These activities - finding new clients and deepening these relationships - become an automated process as AI technology enables advisors to discover lead information more accurately, and produce more high-quality interactions based on real-life connections.
Predictive AI tools can now help trace and find new leads and deliver them straight to an advisor's dashboard. From here on forward, the process becomes a streamlined process, as advisors can use generative AI prompts and algorithms to put together personalized messages and kick-start the conversation.
Taking it a step further, advisors can better understand new clients’ investment and financial priorities, as predictive AI provides accurate customer information retrieved through available data sources. These efforts help advisors to align their financial strategies according to customer’s needs, without having to push through a seemingly endless amount of client information.
Improving efficiency and accurate communication delivery
Timing plays an important role in strengthening customer relationships, while simultaneously delivering a robust experience that sees advisors addressing key customer demands across various digital touch points.
Artificial technology is helping advisors provide more high-impact deliverables, crafting personalized content that targets customer pain points, and improving client engagement efforts.
Already AI-powered platforms are being used to help generate content and fresh ideas in a matter of seconds, helping to save employees time, and providing them with generative tools for ideation, and building customer profiles more accurately.
When combining these efforts in the realm of financial services, there’s the opportunity for advisors to seek out generative AI applications that can help them improve their service delivery, through things such as automated responses, handling customer inquiries more efficiently, and drafting quicker responses.
These tools help to free up more time, and allow advisors to have an omni presence among their client base. Advisors can instead focus on building valuable insights from clients, through calls, virtual meetings, or in-person conversations.
These efforts begin to play an important role in the customer journey, and more importantly in how advisors can deepen the relationship between the client and the services rendered.
Predictive customer insights
Both client and market insights are key to unlocking wider potential, as data-driven decision-making can help provide advisors with more accurate recommendations and enable more seamless delivery of financial strategies.
AI ensures that advisors have access to accurate client and market information, but further ensures that they can better understand financial data, and how they can plan based on client needs and market trends.
With predictive AI, information regarding customer needs can help advisors, and other service agents identify client pain points more accurately, and proactively develop solutions that can address these problems more effectively.
These efforts are valuable in terms of how advisors routinely connect with their customers regarding specific matters.
For example, AI-powered systems will now be able to automatically detect when a client has missed a payment on their account, and notify both the client and advisor to ensure the necessary actions are taken on their account.
With artificial intelligence, advisors can now automatically communicate with clients when needed, which in return can help minimize the time and effort needed to participate in rigorous or mundane tasks.
Even more, AI can help garner the necessary information regarding a client’s portfolio, and align certain strategies in a way that can help them make more informed data-driven decisions.
Instead of having to rely on outdated data that might not consider the long-term outlook of a client’s needs, AI data analysis tools can better adjust algorithms, patterns, and preferences based on the available customer information and market trends.
Improve conversations regarding effective strategy planning
Constructive conversations regarding strategy planning, and long-term outlook are vital factors for advisors and their clients. This is especially important for advisors who are looking to strengthen their relationships with their existing clients, but further scale their activities.
Traditional modes of communication such as newsletters, webinars, and more recently, social media, can help advisors bring important conversations closer to the client while fostering more meaningful relationships.
Yet, these activities require physical input from advisors and other service providers. From researching market trends, creating predictive analyses, and compiling content, all of these actions can now be automated and further improved by using automated generative AI tools and software.
For example, advisors can now utilize AI-powered systems to help them track their monthly client engagement allowing them to visualize their outreach efforts. On top of this, advisors can automate their schedules to align with important events, while simultaneously informing clients of upcoming proceedings.
All of their digital marketing and content creation activities can be automated through the use of generative AI prompts. These prompts help to establish a schedule for publishing new content, sending out informative emails, or sending newsletters to clients each month.
Additionally, client metrics can be tracked and better understood, allowing service providers to understand their level of engagement, which topics are clients more interested in, and how they can align their marketing strategies to help boost their customer relationship management.
Once again, all of this becomes important for advisors that are looking to better understand their client's needs and interests, without removing the human relationship element that plays a critical role in the customer experience journey.
Transform the scope of financial planning
Throughout the client journey, customers want to see how advisors can achieve tangible goals, and deliver on their near and long-term strategies. However, up until recently, these activities required a tremendous amount of time for advisors to demonstrate the unique values that set them apart from industry competitors.
Now, however, things have become a lot more sophisticated, ensuring customers choose advisors over AI-based robo-advisors for their financial planning.
The combination of artificial technology used in parity with advisory planning can help professionals conduct better market analysis, build improved predictive insights, and make decisions based on data-driven outcomes that ensure clients can achieve their financial success.
For instance, advisors can transform the estate planning process, removing unnecessary ambiguity, and making it easier for clients to read and understand. Another example could be using certain data extraction tools as a way to locate key information within customer portfolios that can later be integrated into their financial planning.
From the basics, such as planning how much clients will need to save for retirement, to building a robust savings plan or acting as a basis of ideation, artificial intelligence is furthering the conversation regarding how advisors can achieve their goals more effortlessly while keeping clients engaged, informed, and satisfied.
Challenges Going Forward
Despite the versatility provided by artificial intelligence, these applications aren’t without seeing some possible challenges that could potentially tarnish the near-term experience for customers when not deployed or utilized appropriately.
Regulatory compliance
One of the biggest roadblocks with artificial intelligence is the amount of data collected about customers. The majority of the data collected by AI-powered systems tend to contain highly sensitive and confidential information, further putting into question regulatory considerations regarding the harvesting, handling, and storing of client details.
Security concerns
Second to this is the seriousness of security protocols, and data protection infrastructure. As more advisors begin to collect and store highly valuable client information, so will security concerns regarding the handling of data come under scrutiny. Deploying the necessary digital security infrastructure will be a crucial aspect for advisors, from now on and moving forward. These actions will need to closely follow and combine both industry-specific and region-specific regulatory compliance.
Customer transparency
Collecting more information about clients comes with an increased awareness regarding the amount of transparency advisors can provide them with. While it’s important to understand clients' needs and requirements, building a foundation of trust within the realm of artificial intelligence will require businesses to have the necessary policies in place that provide clients with secure protection over their information, but allow them to communicate how their data is being harvested and used for financial purposes. Again, this is simply one suggestion, and advisory firms will need to develop internal policies that align with industry-specific compliance.
Training and Education
While from the outside artificial intelligence can be an easy tool to use, the application thereof is often more sophisticated than initially imagined. This would mean that advisors and service providers will need to have the necessary skills, knowledge, and abilities to use certain tools as effectively as possible. This could increase the cost burden for advisors and firms, and potentially decrease their engagement over the near term.
Building trust
Making sure that clients understand the connection between their needs and the use of artificial intelligence requires advisors to undergo a nurturing process that could allow them to solidify the trust of their clients. However, not all clients may be on the same page considering the use of AI-powered systems for their financial needs, and this would require advisors to communicate their intentions, and how these applications can be used as a beneficial tool for empowering financial prosperity.
Bridging the gap and narrowing the divide
As artificial intelligence becomes a more integrated part of our work, understanding the complexities of these applications, and how they can benefit the workplace, and improve client engagement can help advisors build a more dynamic strategy towards narrowing the divide between their clients and the financial services industry.
Despite the obstacles that advisors may encounter along the way, viewing the longer-term success of artificial intelligence can deepen the connection with their customers, and ensure a more seamless flow of information.
The better we begin to understand how to work with artificial intelligence, the faster we can develop tools that help to improve our accuracy, and authority, and foster customer relationships that are not purely data-driven, but combine human capabilities and technological ingenuity.
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