Journal of Financial Planning: October 2024
Molly Weiss, group president, wealth management platform at Envestnet (www.envestnet.com), is a wealthtech veteran with more than 20 years of experience. Today, Molly drives the continuous innovation of Envestnet’s end-to-end technology and solutions, ranging from portfolio management, financial planning, performance reporting, and digital account management tools. Molly works to deliver the technology platform capabilities that financial professionals need to serve their clients. She holds an MBA from Santa Clara University.
Creating a financial plan used to be a somewhat cumbersome manual process that resulted in a static plan that had to be updated proactively to identify new scenarios or opportunities. Thankfully, financial planning technology has evolved significantly, enabling interactive, digital engagements between an adviser or planning professional and their client. This helps to make interactions more dynamic and more customizable, allowing clients and their advisers to plug in different variables and see how different scenarios impact financial outcomes.
As we look to the future and what will further enhance the value and experience of financial planning, machine learning offers endless possibilities for the planning and advice industry. This technology has the ability to transform mountains of raw data into clear, actionable insights, allowing advisers to make informed, data-driven decisions that help deliver better client outcomes, efficiently identify new opportunities, and ultimately grow their business.
Zooming out, artificial intelligence will be the linchpin that powers and will help scale the personalization of financial services, a crucial factor for client retention. According to Envestnet’s The Adviser’s Playbook for Leading Your Clients Forward study, 70 percent of wealth management clients consider highly personalized service as key when deciding whether to stay with their adviser. Similarly, a McKinsey report shows that 80 percent of consumers value personalization. AI will be a key driver in enabling advisers to bring personalization to their clients in a scalable way by allowing advisers to analyze vast amounts of data to deliver customized insights, aligning closely with client expectations for tailored communication and services.
Furthermore, Broadridge Financial Solutions’ 2020 survey reveals that clients prefer individualized information in their communications.1 By leveraging AI and machine learning applications, advisers can anticipate client needs, preferences, and behaviors, enabling them to provide highly relevant and personalized advice. This not only deepens client relationships but also positions advisers to meet the growing demand for personalization in financial planning, driving both client satisfaction and retention.
But leveraging artificial intelligence can allow advisers to go far beyond customization to offer client-specific strategies that address specific needs that can not only enhance client satisfaction but help advisers’ business as well.
Anticipating client behavior and market shifts can be crucial for an adviser’s ability to deliver optimal financial solutions.
Top Areas Where Advisers Can Leverage Machine Learning
With machine learning comes the ability to generate insights across an adviser’s entire book of business—providing real-time applications and opportunities for advisers to engage with clients on their financial plan and personalize their approach. Here are a few examples of machine learning insights that can prompt an adviser to take action within a client’s plan:
High-Value Held-Away Accounts
Research by Envestnet shows that nearly two-thirds of clients would prefer to or already use one single financial provider. Yet we also know that the average American holds 5.3 financial accounts. Machine learning can help identify high-value held-away accounts in an adviser’s book—accounts managed by external financial institutions that hold substantial assets—and clients with held-away accounts valued at $50,000 or more, excluding 401(k) accounts.
Clients who fit certain profiles, such as those over 50 with no retirement assets under management or those invested in less common asset styles, may be highlighted as potential candidates for asset consolidation.
For financial advisers, this information can reveal opportunities to have discussions with clients about the potential advantages of consolidating their assets under their management, to provide a more streamlined management of their portfolio, see all their assets in one place, and, overall, experience a more comprehensive and holistic financial planning experience.
Absence of Lifestyle Goals
Oftentimes, with some quick analysis, an adviser can see that a client doesn’t have any lifestyle goals in their financial plan. This is a real opportunity to engage because it means the client hasn’t defined specific personal aspirations or the quality of life they aim to maintain or achieve through their financial plan. Lifestyle goals typically include things like the desire to retire early, travel frequently, buy a second home, fund college for a child or children, or support certain hobbies or activities.
Adding an additional layer of analysis, planners could pull out clients who are nearing retirement age with substantial assets, who are arguably at a very critical stage in their planning journey, to assess the need to plan for healthcare, potential long-term care, travel, and legacy planning.
Without these goals, the financial plan may lack direction and a desired outcome, as it’s unclear what the client’s financial priorities are beyond basic needs or investment growth.
Life Insurance Gap
Today’s clients expect more than just investment management from their advisers. They’re increasingly looking for advisers to adopt a more holistic approach to their financial well-being. For example, life insurance advice is desired by 76 percent of clients surveyed, yet only 11 percent of those clients claim to receive that service from their adviser.2
Addressing life insurance needs is a critical component of comprehensive financial planning. Using technology, we can help advisers identify clients with significant life insurance gaps, defined as a shortfall greater than $100,000, with at least $100,000 tied to the financial plan.
This insight enables advisers to proactively address potential shortfalls in a client’s life insurance coverage, ensuring that they have adequate protection for their families and dependents. With this information, advisers can have informed conversations with clients about potential life insurance needs, suggest appropriate coverage options, and integrate life insurance planning into the client’s overall financial strategy. This can be crucial for everything from managing estate taxes and ensuring heirs receive the intended inheritance without having to sell assets to business continuity for business owners, as life insurance can fund buy–sell agreements or cover key person insurance needs, ensuring the business continues to run smoothly.
Tax Loss Harvesting
Among high-net-worth investors—and across millennials, Gen X and boomers—minimizing their tax burden has emerged in the top three of their primary financial concerns.3 With this, advisers are looking for ways to help clients minimize tax liabilities and maximize after-tax returns. Technology has offered advisers the ability to identify taxable accounts with losses of at least $1,000, where the position constitutes a significant part of the total account market value. This insight is particularly useful for clients in higher tax brackets, as it allows for strategic planning that can lead to substantial tax savings.
For example, many HNW clients understand that the taxes they pay on gains from investments, or capital gains taxes, could be their portfolio’s largest expense. For some investors, the taxes they pay on these gains could approach 50 percent or higher.
With ever-changing tax laws and regulations, investors may need to rely on the professionals they work with to manage the intricacies of tax planning and optimization. Advisers with tax management seamlessly built into their practice have an opportunity to deepen their client relationships while increasing efficiency and adding to the success of their overall financial plans.
Money-in-Motion Client Engagement Opportunities
Anticipating client behavior and market shifts can be crucial for an adviser’s ability to deliver optimal financial solutions. For instance, some models can analyze cash flow patterns over an 18-month period using machine learning to forecast cash inflows and outflows with high accuracy.
This can prompt alerts for various scenarios, such as unexpected withdrawals, missing contributions, or anticipated cash flows. For example, the system can alert advisers if a client misses a regular contribution after several months of consistency or if there is an unexpected withdrawal.
These alerts allow advisers to engage proactively with clients, providing timely counsel that can help prevent disruptions to their financial plans. Predicting cash flows with high confidence also enables advisers to optimize asset allocation strategies, ensuring that cash is used effectively to meet both short-term and long-term financial goals.
Looking Ahead
As the financial advice and planning industry continues to embrace advanced analytics and data-driven solutions, predictive capabilities will become increasingly essential for advisers seeking to deliver superior value and achieve exceptional client outcomes.
By harnessing these insights, advisers can not only meet but exceed client expectations, ultimately driving growth and success in their advisory practices. Advisers will need to stay ahead of these advancements to remain relevant and competitive.
Embracing AI and machine learning is already enabling advisers to offer more comprehensive, holistic advice that includes tax optimization, estate planning, and retirement savings. Providing this integrated advice is becoming the new norm, as clients seek a single point of contact for all their financial needs.
AI-generated insights can significantly enhance client engagement and business growth.
In today’s fast-paced financial environment, technology offers opportunities for advisers to enhance their services and expand their client base. By leveraging data-driven insights, advisers can deliver more personalized, efficient, and high-value services to a broader range of clients. And importantly, this convergence of human and digital interaction and optimization provides a glimpse into the future of financial advice and planning.
There are risks inherent in AI technology and its application in the financial sector, including embedded bias, privacy concerns, outcome opaqueness, performance robustness, unique cyberthreats, and the potential for creating new sources and transmission channels of systemic risks. Trends or potential transactions identified by AI are for informational purposes only and are not to be construed as an instruction to take any specific action.
Endnotes
- Broadridge. 2020, July 27. “Investor Preferences Undergo Lasting Transformation from COVID-19 Pandemic, Reveals Broadridge Survey.” www.broadridge.com/press-release/2020/investor-preferences-undergo-lasting-transformation-from-covid-19-pandemic.
- Envestnet. 2024. Envestnet 2023-2024 Trends Report, Accelerating Toward the Future of Financial Advice.
- Envestnet. 2023. Rethinking Expectations for HNW Investors.
Sidebar
Steps to Get Started with Data Driven Insights in Your Practice
Integrate technology gradually: As always, walk before you run in terms of beginning to take advantage of this type of approach in your practice. The benefit of machine learning is its fluidity and ability to adapt to your specific practice needs.
Get your data in order. Identify the sources of data within your practice, and begin to process it for use in modeling and insights planning—including collection, cleansing, organization, integration, and selection. This is the first step for beginning to generate insights that can help power your practice.
Modeling and analysis. Once you have your data set in order, you can begin to use algorithms to analyze the data, e.g., predictive modeling, classification, clustering, or regression to detect patterns, trends, or anomalies. In-house data scientists can help you with this step, but so can outsourced vendors or software providers.
Insight generation, visualization, and recommendations. After the model is set up, you can begin to identify trends, predict outcomes, and highlight opportunities in an easy-to-understand dashboard. An ideal end state would be to start off your day with insights to act on, to establish a habit and cadence of leveraging these models.
Focus on personalization. Use data-driven insights to tailor your advice and services. Develop strategies for tax optimization and holistic financial planning to meet diverse client needs.
Invest in client education. Create valuable educational resources, such as blogs or curated information hubs, to help clients make informed decisions when presented with opportunities to make changes in their planning process. This builds trust and positions you as a reliable source of financial information.