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Prepare Now for AI Use in Financial Planning

Nick DiLisi May 7, 2024

Diverse Team in Data Strategy Session

With the introduction of such generative artificial intelligence (AI) tools as ChatGPT, Gemini (previously Bard), and others, speculation about future uses for AI and its impact is everywhere. But AI has been around for some time and is already being used in the financial industry, working quietly behind the scenes.

As AI technology progresses, its use in the financial services industry will only increase. While we don’t know exactly what the future of generative AI holds, there is potential for its use in personalizing the financial planning experience for advisors and clients.

Near-term Opportunities for Generative AI

Before examining how to prepare your internal data for AI applications, it’s important to understand how AI may initially be employed from a financial planning perspective. According to a recent white paper by Fidelity Investments, AI could be enlisted in several ways to support financial professionals in the near term.1

Content and Correspondence

Advisors can use a generative AI model to enhance their skills and save time with the creation of content and correspondence. Similar to chatbots we see responding to generic questions from website visitors, generative AI could tap into the client’s proprietary data to personalize the response. These tools could provide virtual assistance in answering clients’ financial questions by drafting initial responses for the advisor’s review and approval. Similar applications could include crafting social media posts and answering email correspondence.

Financial Education

Advisors must provide a steady stream of financial education to clients to ensure they get the most out of their financial planning experience. The industry is complicated—helping clients understand basic terms and concepts will help them achieve their goals. AI could be used to curate and deliver general educational programs personalized for each user based on the progress of their financial plan. The same goes for advisors and staff—AI could provide ongoing professional development resources based on career stage and job responsibilities.

Meeting Transcription and Follow-up

While transcription capabilities are already built into many meeting platforms, AI could take this to another level. Beyond transcribing and summarizing key points, other helpful tasks could include determining next steps and implementing prompts for assigned staff members to follow up.

Whether you are researching ways to employ generative AI today or want to prepare to do so in the future, steps can be taken now to ensure your firm and your data are ready.

Preparing Your Firm’s Data for AI Applications

Because generative AI creates new content, such as text or images, by learning from existing content, using it to personalize the financial planning experience would require access to a firm’s proprietary data. Methodical preparation for using proprietary data in this way is critical.

Data Accuracy

The accuracy of your firm’s client data could vary widely depending on the methods you use to collect and store it. For generative AI to correctly answer questions or create accurate outcomes based on client data, the data must be well-organized and precise. Technology is crucial to achieving this.

A customer relationship management system (CRM) facilitates the breakdown of client data by categories and criteria, simplifying the creation of focused lists. A digital onboarding tool streamlines data collection and increases the accuracy of client data. When these and other financial planning tools are integrated, they ensure client data is correct across an organization.

Ensuring the accuracy of client data will provide immediate benefits, long before advisors even think about using it in AI applications. This data can be used to personalize marketing, tailor products and services to client needs, and provide exceptional client experiences. Not only will accurate client data improve efficiency and productivity, but it will also help build trust, loyalty, and satisfaction among clients.

Data Security

The use of AI can create new cybersecurity challenges. Advisors and their compliance teams must work closely with their IT partners to implement robust security measures. Sensitive client information must be anonymized to protect the privacy of any personally identifying information present in AI training data to prevent breaches.

On the plus side, AI will also play a significant role in enhancing defenses against cybercriminals. It can be used in tools that spot suspicious activity and do a better job than humans in safeguarding information and protecting clients.

Data Bias

Just as financial professionals need to be aware of their personal money biases, generative AI systems must be protected from being trained using biased data. Firms must have a process in place to ensure any generative AI it uses will provide fair and equitable outcomes when used for advice and financial decision-making.

Regulatory Compliance

As the uses for generative AI evolve relative to the financial planning industry, so too will the regulations governing how it can be used and the ways client data must be protected. Regular audits and staying on top of all new regulations are essential to guaranteeing ongoing compliance, whether AI-related or not.

AI and the Human Element

As the debate continues about the ways AI could impact humans and the work they do, I believe financial planning will always require human interaction. Advisors can embrace the value AI provides to the financial planning process, confident that it can never replace the unique human interaction that clients want from a trusted financial professional.

Humans must play a role in ensuring that AI can provide that value. Taking steps now can ensure your client data is ready for generative AI applications, but its use will require ongoing human checks and balances. It will be important to continually validate that AI models are getting it right. Only you and your staff can understand and speak to the business context and accuracy of the results.

AI in Financial Planning Is Here to Stay

No matter the approach you take to incorporating more AI into your financial planning process in the future, there are steps you can take today to ensure you’re ready. Start small by focusing on one specific area of improvement at a time until you are seeing consistent results on what you’re trying to achieve.

Look at how your business and its processes are organized. Examine the way you’re collecting and storing your data. Implement a digital onboarding process or investigate how to ensure your data is integrated across your tech stack. Make sure you understand the implications of having all this client data and the risk that it poses for client security.

Finally, stay up to date on how AI is shaping the financial planning industry. Be curious and keep exploring what’s coming. AI will likely play a major role in simplifying the act of producing a financial plan, but it will never replace the empathy, connection, and guidance your clients need to achieve successful financial outcomes.

To learn more about how you can start using client data today to build stronger client relationships, read our eBook Using the Data You Have to Evolve Your Business and Client Relationships.


1 “The Incredible Potential of Artificial Intelligence in Wealth Management.” Fidelity Investments, 2023. August 7.

DISCLAIMER: The eMoney Advisor Blog is meant as an educational and informative resource for financial professionals and individuals alike. It is not meant to be, and should not be taken as financial, legal, tax or other professional advice. Those seeking professional advice may do so by consulting with a professional advisor. eMoney Advisor will not be liable for any actions you may take based on the content of this blog.

Image of Nick DiLisi
About the Author

As Head of Technology, Nick oversees software development and IT operations for the company. As one of the pioneering employees who co-founded eMoney in 2000, he also served as Chief Information Officer. You can say Nick’s contributions to eMoney’s core products give them the “X” factor not found in other financial platforms.

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