Financial advisors today have access to many technology tools, including a growing number of artificial intelligence applications. However, effectively integrating these tools can be challenging. This article examines three key use cases where AI can benefit financial advisors: practice management, client engagement and prospecting.
Use Case 1: Enhancing Practice Management
AI tools can be applied to many aspects of practice management to deliver a better customer experience and drive efficiencies. A prime example is the use of AI note-takers, such as those offered by Otter and Fathom, in client meetings. The traditional approach of physical notetaking often restrains financial advisors, detracting them from actively participating and being present during discussions. It is also easy for points to get missed in the notes. AI note-takers, however, have revolutionized this sphere. These digital assistants alleviate the pressure, facilitating a greater focus on the current conversation, thereby enhancing client interaction and comprehension.
Yet, the use of AI doesn’t just stop at notetaking. Client conversations often generate lengthy transcripts, so summarizing the contents is vital for client follow-up and providing a record of the conversation for compliance. AI assistants such as Claude come to the fore here, condensing extensive documentation to concise, shareable summaries and ensuring that pivotal insights and next steps are not lost amidst the heap of information.
This streamlined process is further augmented by integrating these summaries into customer relationship management systems. Such integration not only enriches customer data but also aids teamwork by providing a detailed picture of client interactions and demonstrating adherence to compliance protocols.
What to look for:
AI note-takers: Numerous options are available, both specialist solutions and those offered within video conferencing platforms. Key considerations include the ease of using the note-takers on calls, the accuracy of the transcription provided, the ability to access playbacks, and whether there is a limit on the number of minutes uploaded.
AI summary tools: Key aspects to consider include determining if it is possible to upload source documents versus copying information directly into the platform, whether there are restrictions on the length of text to be summarized and the standard of the summaries provided.
Use Case 2: Delivering Personalized Client Engagement
By leveraging AI, advisors can transform customer interactions. Advisors invest hours preparing for client meetings and reviewing data to find useful insights. However, relevant data is often fragmented across various technology platforms and reports, making it hard to uncover key details. This is where AI tools designed specifically for advisors can help. These systems sift through disconnected data sets to surface hidden insights that can shape pivotal client conversations and guide next steps. Advisors simply ask questions to help with meeting prep, such as customer interactions over the past year or changes in buying behavior. AI acts as an intelligent co-pilot, revealing crucial details from vast data troves.
As well as helping with individual client meetings, generative AI is also invaluable for mining the client book for clients at risk and untapped opportunities. They can aggregate insights, spotlighting gaps in outreach and client engagement. Moreover, they can also intuitively suggest the next best steps in strategic planning, ensuring advisors are equipped with questions like “How can I refine my client engagements?”
What to look for:
AI financial advisor co-pilots: For this use case, it is best to work with a specialist GPT provider designed for the wealth management space, as opposed to a generic GPT. Specialist GPTs are pre-trained in the relevant industry terminology, are designed to accept relevant industry inputs and adhere to industry security and privacy standards. Some GPTs also assist advisors by providing pre-set prompts or providing examples of key questions to ask.
Use Case 3: Enabling Personalized Prospecting
Finally, there are a variety of AI assistants to help advisors strategically engage with prospects. LinkedIn tools such as Taplio go beyond the social media scheduling tools of old and help users with content creation and personal brand building. They can also help with network building by automating responses and direct messages to those who respond to content.
Then, there are email coaching tools, such as Lavender, which help to craft more compelling outbound sales emails. Lavender’s AI-generated personality profile function is particularly noteworthy for how it pinpoints the optimal sales approach for each individual prospect. Beyond the obvious benefits of high-quality content creation, arguably the greatest benefit of these tools is how they facilitate meaningful interactions and catalyse genuine relationships in a digital age.
What to look for:
LinkedIn tools: in addition to scheduling and analytics, look for assistants that can assist with providing fresh ideas for content creation and actively facilitate interactions with connections.
Email sales tools: There are numerous AI writing coaches, but for prospecting purposes, focus on those that have been designed for sales engagement and that can bring additional capabilities, such as personality profiles.
Reaping the Benefits of AI
By thoughtfully implementing AI to handle routine tasks in these areas, financial advisors can boost productivity, enhance client service, and accelerate growth. The key is strategically leveraging these emerging technologies to complement, not replace, the advisor’s expertise.
There are many points in an advisor’s work where AI tools can bring efficiency gains and substantially better working practices. Yet, understanding where to start is not always easy. It is important, of course, to consider the wider company strategy and to determine the points at which AI assistants can help. There are some relatively quick, easy and cost-effective AI wins to be found, while investments in enterprise-grade, specialist financial advisor co-pilots will need greater consideration; getting the most out of each tool can also take some practice, but providing training, encouraging advisors to explore and test the technology and putting in place mechanisms for users to share how they interact with AI tools will encourage uptake. For those wealth managers who embrace the potential offered by AI, the upsides are enormous.
Nathan Stevenson is CEO and Browning Mank is the Chief Revenue Officer at ForwardLane