The AI Advantage in Wealth Management

As organic growth rates stagnate across the wealth management industry, firms are increasingly turning to artificial intelligence to retain a competitive edge. The AI advantage will transform how firms enhance advisor efficiency while maximizing net new asset growth. 

To understand the opportunities and applications of AI to spur organic growth, we reached out to Jeannette Kuda, Chief Operating Officer of TIFIN AG - a financial technology firm that employs advanced algorithms to help wealth enterprises answer specific questions to drive net new asset growth. During our conversation, we covered the advantages of being an early AI adopter, leveraging AI to catalyze organic growth, and how TIFIN AG partners with wealth enterprises to address challenges across acquisition, expansion, and retention segments.

Hortz: How is the wealth management landscape evolving and why are traditional methods no longer sufficient for growth?

Kuda: The wealth management landscape is currently experiencing a significant transformation. Firms are grappling with mounting challenges as they seek to expand their businesses. Since inorganic growth avenues are reaching their limits, firms are turning their attention to bolstering their organic growth strategies. However, the tried-and-true traditional methods—such as mass marketing, seminars, in-person networking events, and generic client segmentation—are no longer sufficient.

The shift toward a new imperative is clear: efficiency, scalability, and hyper-personalization. Advancements in technology have intensified competition while simultaneously putting pressure on profit margins. Consequently, wealth management firms must deftly balance scaling their organic growth strategies with maintaining operational efficiency and delivering personalized client experiences.

Survival and competitive advantage now hinge on embracing innovation, particularly in the realms of Artificial Intelligence (AI) and Machine Learning (ML). Business leaders who proactively adopt these disruptive technologies will likely win, while those who hesitate will be left behind.

Hortz: How quickly do you foresee AI technology gaining widespread adoption in the industry?

Kuda: We are still in the early innings of adopting AI in wealth management, but the pace of innovation and the ensuing adoption and integration will be like nothing we have seen before.

While the wealth management industry has been somewhat deliberate in embracing AI for operational efficiency —particularly in middle and back-office functions — its adoption for organic growth has been more measured. Although firms recognize the advantages AI offers, many remain on the sidelines, cautiously observing. However, those who approach AI with a pioneering spirit stand to gain a significant first-mover advantage.

In the next 12 to 24 months, I anticipate AI becoming foundational to the success of every growth-oriented wealth enterprise. Early adopters are already experiencing remarkable growth rates and this success story is likely to propel broader industry adoption.

Hortz: How would you describe a use case for deploying AI to a financial advisor?

Kuda: Wealth enterprises that embrace AI for organic growth optimization should have a clear objective: to enhance advisor efficiency while maximizing net new assets. Imagine an advisor with a call list of 100 clients, lacking clear direction on whom to call or why. Without AI assistance, this task often results in mediocre outcomes and consumes excessive time.

However, an AI model will identify the top 10 clients to focus on each week while surfacing potential asset consolidation opportunities. Armed with this information, the advisor gains direction, focus, and intent — leading to realistic goals and tangible outcomes.

In essence, AI empowers advisors by pinpointing high-return opportunities within their book of business. By knowing precisely whom to engage and when, firms gain a competitive edge over their peers.

Hortz: Why do you feel being an early adopter of AI will help firms grow faster?

Kuda: Machine learning represents a critical facet of artificial intelligence that drives organic growth signals for businesses. Specifically, supervised AI algorithms analyze client demographics, financial data, and asset flows to discern patterns and predict future opportunities. These models are then integrated into customer relationship management (CRM) systems or advisor desktops, where they continuously learn from new data generated through outcomes, behaviors, meetings, and other advisor-driven activities. This iterative process, facilitated by feedback loops, tailors the model to the unique context of the firm.

When business leaders strategically embrace and deploy AI/ML models across their advisor base, early adopters gain a competitive edge. By continually feeding the model with more data, they enhance its accuracy and predictive capabilities, leading to better-informed decisions and more effective growth strategies. Being at the forefront of AI adoption positions firms to capitalize on emerging opportunities and stay ahead in a dynamic business landscape.

Hortz: What are the different ways wealth firms can grow using AI?

Kuda: Most firms are experiencing organic growth challenges that span one, two, or all three growth segments:

The first is identifying and prioritizing prospects who align with an advisor’s ideal client profile. Think of this as an acquisition strategy that assists wealth firms struggling to convert new clients. By leveraging AI, firms reduce the noise by ensuring advisors or business development teams focus their prospecting efforts on the most promising leads.

The second centers around studying and evaluating consolidation opportunities within an advisor’s existing client base. Selling to existing customers is highly effective (with a probability of 60%-70%). AI-driven insights, such as signals derived from money-in-motion events, enable advisors to increase wallet share within their book of business.

Third is the use of AI to study asset flow behaviors of current or previous clients. Detecting signals that indicate a client may consider moving assets elsewhere or closing their account allows advisors to take proactive steps. Through strategic outreach, advisors can enhance retention rates and transform at-risk clients into success stories.

Hortz: Data analytics and intelligence have been around for a while – how does AI differ?

Kuda: While data analytics provides valuable insights, there is a fundamental distinction between merely knowing information and strategically acting upon it. The true differentiator of AI lies in its learning component. Unlike traditional data analytics, AI models actively learn from both an advisor’s successes and failures. This continuous learning process allows the technology to adapt and refine predictions specifically tailored to each advisor’s unique context. As a result, AI-driven insights lead to better outcomes over time, enabling more precise targeting efforts.

Hortz: How has TIFIN AG tested and validated its approach in the marketplace?

Kuda: We partnered with a large North American wealth management firm for a 6-month pilot study. During this collaboration, we deployed our Asset Consolidation solution — an innovative model designed to identify held-away assets and pinpoint clients most likely to consolidate those assets.

The results were compelling: Advisors who acted on TIFIN AG-identified leads experienced a remarkable increase in net assets under management (AUM) compared to a control group. In practical terms, these proactive advisors successfully guided clients to consolidate assets from other institutions into the wealth firm. Meanwhile, the control group, following conventional practices, witnessed asset distributions out of the wealth firm. This real-world impact underscores the effectiveness of AI solutions in driving growth and enhancing client retention. 

Hortz: How does TIFIN AG enhance its AI models to meet the evolving needs of the wealth management sector?

Kuda: We are committed to staying at the forefront of industry trends through continuous innovation. We actively seek feedback from our clients, allowing us to develop new AI models that address emerging needs effectively. Recently we worked with one of our current clients to develop a capability that identifies cross-sell opportunities — such as transitioning mortgage clients or self-directed brokerage accounts into wealth management clients. By connecting these dots, our client was able to find a new avenue to drive organic growth.

To maintain cutting-edge solutions, we are also investing in algorithm performance improvements through expanded partnerships. Our goal is to continuously evolve our capabilities, meeting the dynamic challenges of the wealth management sector and supporting sustainable growth for our clients.

Hortz: What advice do you have for firms looking to adopt an AI growth strategy?

Kuda: When considering AI adoption, recognize that it is not a standalone solution. AI complements existing processes to drive scale, efficiency, and personalization.

Start with Clarity: Understand precisely how AI enhances your firm’s efforts and empowers your people. What specific challenges will it address? What opportunities will it unlock? Clear objectives are key.

Top-Down Commitment: Leadership sets the tone. Ensure that management fully supports the AI initiative. Allocate resources, both in terms of funding and internal capacity, to drive success.

Practice Management and Enablement: Proficient practice management and enablement teams play a pivotal role. They create awareness, provide education, and deliver the necessary training to drive advisor adoption, ultimately leading to desired organic growth outcomes.

AI is not a magic wand—it is a strategic tool. By aligning it with your firm’s goals and investing in the right support structures, you will be on the path to sustainable growth.

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