Sanford Schmidt and the Economics of Trust in an Automated Wealth Management Era

Economic Principle: Transaction Cost Economics (Ronald Coase) 

In a perfect world, artificial intelligence should have already pushed human financial advisors to the side. AI-driven robo-advisors can analyze massive datasets, adjust portfolios in real time, and work for a fraction of the cost of a human. In theory, this kind of efficiency should squeeze profit margins for traditional advisors until only the cheapest providers survive.

But in reality, it’s different. Advisors like Sanford Schmidt—a veteran in wealth management—keep bringing in new clients while keeping old ones, even as automation grows. In fact, the global financial advisory market is projected to grow from $79 billion in 2023 to $118 billion by 2030 according to Grand View Research.

The success of these human advisors, and the premium fees they still command, can be explained using Transaction Cost Economics (TCE)—a theory first introduced by Nobel Prize winner Ronald Coase. 

Transaction Costs Beyond Price

Transaction Cost Economics (TCE) starts with a simple truth: the cost of doing business isn’t just the price tag you see. There are search costs (finding the right provider), negotiation costs (agreeing on the deal), and enforcement costs (making sure the deal is honored).

In wealth management, those “hidden” costs include finding a good advisor, checking if they’re trustworthy, watching their performance, and making sure they have your back.

With AI, search cost goes down significantly as an investor can compare robo-advisors, sign up, and start investing in minutes. But in markets for credence goods—services whose quality can’t be fully judged even after you’ve used them—trust becomes the deciding factor. Wealth management is what economists call a credence good—you can never be certain whether a different strategy would have done better, because you can’t see the “what if” scenario.

When it’s impossible to measure results with complete certainty, clients fall back on reputation and trust to guide their choices. That’s why human advisors still have an edge over algorithms.

Trust as an Economic Asset

From a TCE perspective, trust is not just a warm fuzzy feeling—it is a valuable economic resource that decreases transaction costs by reducing the constant need for monitoring and verification.

In finance, where asymmetries of information are high and the consequences of a mistake are long-lasting, trust is an important efficiency mechanism. For example, through its 2019 Advisor’s Alpha study, Vanguard found that human financial advisors can provide an incremental value in net portfolio returns of up to 3% annually—not just through investment selection, but through behavioral coaching, adhering to the investment plan through disciplined rebalancing, and financial planning tailored to the client.

These costs occur as a result of the advisor establishing credibility and emotional intelligence. A robo-advisor may have the operational ability to rebalance a portfolio at will but it cannot provide personal empathy to a client emotionally experiencing a market freefall. The economic consequences of saving just one client panicking and selling at the bottom would proportionally outweigh any efficiency related to using an automated service.

This is partly why human wealth management firms, like Sanford Schmidt, continue to thrive. They are not necessarily providing more value than AI on the data-crunching front. Rather, what is important to them is lowering clients' perceived enforcement costs made possible by creating certainty and accountability through their presence as humans. 

Why AI Can’t Fully Replace Human Advisors

AI's inability to supplant human advisors is not a function of computation: algorithms can create extremely complex strategies. The limitation then lies with transaction costs as it pertains to credence goods markets which injects multi-layer transaction costs.

There are three persistent gaps that sustain demand from advisors:

Credibility Gap - Algorithmic-based advice, without any personal relationship and without any history, will seem generic (even if it is correct). Financial plans are about life goals and personal context, not just numbers.

Accountability Gap - Algorithms cannot be held liable, in the social, reputation or legal sense, whereas human advisors can be. For many clients, the mere fact that “someone’s name is on the line” may matter to them.

Signaling Value - In high-net-worth contexts, hiring a well-respected human advisor signals diligence and seriousness to one's peers, family members and business associates. These types of signals sometimes have spillover effects beyond mere investment outcomes. 

All of this indicates that perceived transaction costs are higher when considering fully automated solutions than with a trusted human advisor - especially in a complex portfolio that is characterized by higher stakes.

Economic and Behavioral Forces Sustaining the Balance

A number of macroeconomic and behavioral forces help to reinforce the equilibrium:

• Information asymmetry: As financial products become increasingly complex (e.g. structured notes, ESG strategies, private equity funds), clients are searching for interpreters to help contextualize their options.

• Market volatility: As markets become more volatile, the "trust dividend" increases. Clients get value from the comfort of knowing an experienced advisor is present, especially at times of volatility when the long-term investing plan seems threatened. 

• Demographic Preferences: At the higher age brackets in developed economies, individuals usually prefer face-to-face advice, especially for estate planning, tax optimization and intergenerational wealth transfer. 

This results in our market segmentation: while AI-based services dominate the low-cost, do-it-yourself marketplace, human advisors dominate the trust-sensitive, high-net-worth parts of the market.

Real-World Market Evidence

The market segmentation is also evident in published industry data; robo-advisory firms such as Wealthfront and Betterment manage more than $65 billion of assets in total, primarily due to their low fees, convenience, and automation. 

Yet at the margin, traditional services still control the top end of the market: Merrill Lynch Wealth Management - entirely based upon human advisor services - manages over $2.8 trillion in assets (Bank of America, 2023). This gap is affirming the notion that while automation may execute with efficiency, the largest pools of wealth are still under human supervision.

This pattern is reflected in other industries in which automation co-exists alongside high-touch services: the education software industry has grown significantly, but in-person teaching, tutoring or mentoring remains highly valued for the relationships and trust they build. In both industries, human advisors still have value, not because machines cannot disseminate information, but because there is still a requirement for a human agent to reduce perceived uncertainty. See education software development for more on where technology fits in this discourse.

Ramifications and the Future Model

Under the TCE framework, the evolution of wealth management is unlikely to be a zero-sum contest between humans and AI, but rather the industry will be heading towards a hybrid model:

• AI will handle: data processing, algorithmic issues, portfolio optimization, tax-loss-harvest, and routine reporting - thereby reducing search and basic processing costs.

• Humans will handle: relationship development tasks, behavioral coaching, multi-generational planning and trust - thereby reducing perceived enforcement and coordination costs.

In this model, AI takes care of the simple, repetitive tasks—fast, accurate, and cost-efficient—while human advisors step in where the stakes are high and the emotions are complex.

What makes a human wealth advisor truly valuable—whether it’s Sanford Schmidt with decades of experience or a newly certified CFP—is the ability to turn trust into an economic advantage. Even when computing is cheap and automation is everywhere, that trust is worth paying for.