Money Angst? You Might Consider a Financial Therapist

Do you worry a lot about higher food and gas bills? Fight with your spouse over spending splurges? Fear you’ll outlive your savings?

Some people seek to ease such money anxieties by hiring a financial therapist.

The goal of financial therapists ultimately is to help people make good financial decisions, typically by raising their clients’ awareness of how their emotions and unconscious beliefs have affected their sometimes messy experiences with money.

Needs for such help often arise following a job loss, bankruptcy or marital partner’s financial infidelity—when one spouse hides or misrepresents financial information from the other. Even something seemingly positive, such as getting a big inheritance or winning a lottery, can cause financial anxiety.

“Folks are craving help with financial well-being,’’ says Ashley Agnew , president of the Financial Therapy Association, a professional group launched in 2009.

Financial therapists tend to come from mental-health and financial-planning disciplines, and there are signs that their ranks are rising: The Financial Therapy Association has 430 members, up from 225 in 2015. Still, according to the group, fewer than 100 financial therapists have completed its certification process, introduced in 2019. You can be an association member without being certified by it.

The reason for the increased interest is clear: Many Americans are worried about their personal finances. In a survey of about 3,000 U.S. adults conducted last October by Fidelity Investments, more than one-third of respondents said they were in “worse financial shape” than in the previous year. Some 55% of those respondents blamed inflation and cost-of-living increases.

Similarly, 52% of 2,365 Americans polled for Bankrate.com said money negatively affected their mental health in 2023. That is 10 percentage points higher than in 2022. Financially anxious and stressed individuals are less likely to plan for retirement, prior research has concluded.

Messy divorce

New York advisory firm Francis Financial hired financial therapist Allen Sakon last November to aid individual clients. Many are divorced or widowed women with complicated money problems.

Certain clients “don’t believe they have enough resources, even though objectively they do,” says Sakon, who is a certified financial therapist, financial planner and accountant. Meanwhile, others with limited means mistakenly believe “they can live as extravagantly as they want,’’ she says.

Sakon currently counsels a recently divorced woman who is struggling with her dramatically lower income and the imminent sale of the family’s suburban New York home. “Her world has been turned upside down” by a financially messy divorce, Sakon says.

Though the woman has stressful new money responsibilities, she long avoided financial decisions, according to Sakon. “A money-avoidant grown-up is typically someone who was excluded from money discussions as a child,” she says.

Sakon says she hopes to eventually help this client feel capable of making financial decisions based on her resources and the financial plan that Sakon created for her.

Nate Astle , a certified financial therapist in Kansas City, Mo., met nine times from May 2023 to February 2024 with Andrea and Gianluca Presti , a 30-something Texas couple who were having persistent spats over money. Andrea Presti , an email marketer, says she believed that “if we didn’t go to financial therapy, I was going to question our entire relationship and whether we could continue.”

The wife cites an argument over the possible purchase of an expensive new car to replace their decade-old vehicle as an example of the couple’s financial conflicts. They disagreed over whether to give up a car that still worked well.

The husband, Gianluca Presti, a music producer, says financial therapy taught him and his wife to communicate better through active listening. He says he stopped being the couple’s money gatekeeper, became more open-minded about spending—and agreed to pay up to $45,000 cash for a new car. “We have to be a team if we want to solve financial issues,” he now realises.

Astle helped the Prestis revamp their household budget as well. It now reflects each spouse’s interests by including expenditures, investments and savings.

Astle, who is also a marriage and family therapist, says he has seen his financial-therapy clients more than double to 43 since 2022.

Possible pitfalls

Still, there are possible pitfalls when hiring a financial therapist. One major drawback: Anyone can claim they are qualified to practice financial therapy.

No government agency regulates the young profession. Candidates for certification by the Financial Therapy Association must take online courses designed by the association covering financial and therapeutic techniques, counsel clients for 250 hours and pass a 100-question test. But you can call yourself a financial therapist and not be certified by the association.

Meanwhile, the cost of financial therapy varies widely—from $125 to $350 an hour, Agnew estimates. Insurance rarely covers the tab.

In addition, there is no broad evidence that financial therapy works well. No large-scale studies demonstrating the field’s effectiveness have been conducted.

Another potential downside is that financial therapists with mental-health backgrounds typically lack extensive financial-planning experience—and vice versa. It is wise to interview at least three financial therapists, experts suggest. Then, pick someone who admits the limits of their expertise.

“I am very upfront about my boundaries,” says practitioner Aja Evans , a licensed mental-health counsellor who isn’t certified in financial therapy. Evans adds that she failed the certification test but plans to take it again during 2024—and before she becomes Financial Therapy Association president in January.

She says she feels well-qualified to help clients recognise how their upbringing affects their money beliefs today. “But I am in no shape or form going to be advising you about your investments, money moves or creating a financial plan,” Evans says. For clients who want that assistance, she says, she refers them to certified financial planners and accountants she knows well.

A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.

The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.

The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.

The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.

This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.

The debt behind the AI build-out

Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.

Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.

JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.

The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.

That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.

A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.

When interest rates rise, those assumptions become less forgiving.

Inflation changes the calculation

September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.

The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.

CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.

Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.

Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.

The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.

China adds another source of pressure

Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.

Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.

The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.

That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.

A reset rather than the end of the boom

The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.

What has changed is the market’s willingness to overlook the price and financing structure of that growth.

The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.

More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.

For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.

Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.

The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.

Fact box

Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026

Philadelphia Semiconductor Index: Down approximately 11.4 per cent

Micron Technology: Down approximately 14.6 per cent

Samsung Electronics: Down approximately 18 per cent

SK Hynix: Down approximately 24 per cent

US September inflation: 3.7 per cent annually

Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion