How Farther is building a wealth management platform in the age of AI
- Farther is a technology-centric wealth management firm, with AI playing a pivotal role in differentiating the company from traditional wealth management firms and Registered Investment Advisors (RIAs).
- However, in Farther’s framework, AI is the dependable supporting actor, essential to the storyline but never the protagonist.
The 1962 sitcom The Jetsons anticipated life in 2062, showing people in space communities, zooming around in flying cars, and having robots handle household chores — concepts that were hard to envision in real life back then.
Jumping ahead to 2024, a few of these concepts are moving from theory to practical application, with some of the most visible advancements occurring in Artificial Intelligence. The idea of AI fully replacing humans in managing complex and delicate financial matters remains a distant prospect, but it is increasingly becoming a key component of how newer firms operate their business models.
Farther is one such technology-centric wealth management firm, with AI playing a pivotal role in differentiating the company from traditional wealth management firms and Registered Investment Advisors (RIAs).
By automating administrative tasks such as account setup, money transfers, and routine portfolio rebalancing, Farther reduces the time advisors spend on repetitive processes. This approach helps to minimize operational costs and free advisors to focus on higher-value activities like financial strategy, advising clients, and fostering deeper client connections. The platform is, however, integrated with key partner institutions, including custodians and brokerages.
Farther’s AI approach: Complement instead of replacement
Established in 2019 by CEO Taylor Matthews and CTO Brad Genser, the firm was born out of the founders’ realization that fragmented third-party technology in the wealth management industry was hindering advisors from effectively serving clients and growing their businesses.
In Farther’s framework, AI is the dependable supporting actor, essential to the storyline but never the protagonist – something the founders were clear about from the very beginning.
“We view AI as a powerful tool that supports wealth advisors, rather than replaces them,” said Brad.
Humans are in the driver’s seat, with AI in the passenger seat: In Farther’s model, AI is not responsible for making investment decisions but assists advisors by reducing their administrative workload.
“Advisors have been integral to Farther’s growth and technology has been a key enabler in this model,” noted Brad.
With AI as an enabler, the firm leverages technology to streamline advisor workflows, enhancing time management. This shift, according to Brad, enables advisors to spend 90% of their time engaging with clients and prospecting, allowing them to scale their practices more effectively and focus on identifying wealth-building opportunities for their clients.
The platform charges advisors 50% of their advisory fee on the first $500,000 and 25% on any amount above that threshold – in addition to offering equity in the company. According to Brad, this approach ensures advisors’ success directly contributes to Farther’s growth.
Thanks to tech-driven tools and attractive incentives, Farther has quickly grown its Assets Under Management (AUM), surpassing $5 billion, and is positioning itself for further market expansion as its advisor network continues to grow.
“With a by advisors, for advisors approach, we empower advisors by automating back-office tasks and providing flexibility with no arbitrary minimums or restrictive non-competes,” said Brad “Advisors have the freedom to choose the clients they wish to serve and manage their time as they see fit.”
Product development: Advanced AI supports the firm’s engineering team by optimizing coding processes, which accelerates the development and refinement of the platform. This, according to Brad, enables the firm to provide more personalized experiences for both advisors and their clients.
Product enhancements in the next five years: “Following our $72 million Series C funding round [last month], we are committed to continuous investment in our technology platform,” said Brad.
Farther’s plans for the future include launching improved features centered on both advisors and clients, aiming for an all-in-one platform. The firm is also working on expanding its investment solutions, including tax-efficient portfolios and alternative investments. In addition, the wealth-tech platform is focused on enhancing its lead generation capabilities to widen its reach and continue building on the key drivers of its growth.
AI is important, but so is far-sightedness: While automated investment tools have gained significant attention in recent years, current trends suggest that clients continue to place a high value on human advisors who can navigate the intricacies of their financial situations.
The usage of US digital advisors declined from 27.7% in 2021 to 20.9% in 2022, with high-net-worth investors moving away from robo-advisors at the highest rates.
“We recognized this growing demand [earlier] for expert guidance as a cornerstone of our mission,” Brad said. This is mirrored in the decision to have humans guide the decision-making process at Farther.
Brad believes that top-tier advice should be both accessible and personalized, without relying solely on automation. The future of wealth management will likely combine user-centric technology with the expertise and empathy that only human advisors can provide.
The challenge in creating AI-driven solutions today
AI solutions have been employed in the financial sector for years but their evolution has brought about new and increasingly complex challenges.
Having led Goldman Sachs’ inaugural AI engineering team in wealth management, Brad discusses how the development of Farther’s full-stack product approach today differs from that experience.
According to him, successful use and deployment of AI requires command of 4 main areas:
- Software domain knowledge
- AI mathematical knowledge
- Software engineering knowledge
- User empathy
“While the areas of emphasis have remained consistent, the required emphasis across these areas has shifted significantly in the last decade,” Brad noted.
In the 2010s, Brad trained software engineers in mathematics and quants in software development, dedicating significant time to building infrastructure for model deployment. At the time, the domain knowledge required was relatively simple, as the AI tools available could only handle basic tasks. User empathy wasn’t as critical, as the stakes were lower, and AI was seen more as a luxury — something people were aware of but didn’t feel the need to engage with.
Fast-forward to today: Brad explains that they now have sophisticated tools that encode the math and AI software, enabling engineers to focus more on the domain while rapidly deploying solutions. AI has evolved to handle complex tasks that were once the exclusive domain of humans.
Brad believes that as AI becomes increasingly essential for remaining competitive across industries, the real challenge for knowledge workers is adapting to the evolving nature of their roles and redefining their responsibilities.
“The challenge for AI professionals over the next 5 years is to build user trust and provide pathways and guidance to their highest value-added work, which will require a great deal of empathy to get to the right path,” shared Brad.