What Your Friends Can Teach You About Money
Millennials and Gen Z are turning to peers instead of professionals for financial advice. They don’t trust banks, and they are tired of information overload.
Millennials and Gen Z are turning to peers instead of professionals for financial advice. They don’t trust banks, and they are tired of information overload.
Colin Saint-Vil got his money education at the dim sum cart, over a steamy plate of pork buns and turnip cake.
A friend offered to pick up the whole tab on her credit card, “for the points.” At the time, six years ago, “for the points” meant nothing to Saint-Vil, now a 30-year-old planning manager in Brooklyn, so he pressed for more details. They lingered over the dim sum meal as a larger conversation unfolded about annual percentage rates, credit-card debt, payment schedules and more.
Millennials and members of Gen Z prefer to seek financial advice from each other than from parents or from financial professionals. They don’t like overwhelming spreadsheets and marketing material written in seemingly foreign languages. They don’t trust big banks and institutions trying to sell them on investment strategies—as many were raised around the late 2000s financial-crisis. And, they are not wrong: There is a lot to be learned from comparing numbers with peers—from sharing salaries to talking out big decisions like home or car purchases.
Saint-Vil said when his father was his age, he had already begun investing in real estate, but with property prices now so high and mortgage rates only just beginning to fall, he said he couldn’t imagine being able to follow in his father’s footsteps. He, like many millennials and Gen Z-ers, describe their finances as “fairly good” these days, though they hold a negative picture of the greater economy, according to a new poll of 18 to 29-year-olds from the Institute of Politics at Harvard Kennedy School.
Millennials are still reeling from the impact of back-to-back recessions, all while large bank closures and investing scams dominate the headlines. Younger people report a feeling of “financial avoidance” exacerbated by high inflation and the pandemic-era budgeting.
As of June 2023, Gallup polling revealed a historically low faith in U.S. institutions, with younger generations voicing high skepticism. According to Gallup, only 9% of respondents aged 18 to 34 expressed “a great deal” of confidence in banks; meanwhile, 47% and 28% said they have “some” or “very little,” respectively.
But when it comes to winning back young consumers, these same financial institutions haven’t quite given up, and are rolling out new outreach programs and robo advisors, some of which have helped bridge a connection with Gen Z and millennials, said Keith Niedermeier, clinical professor of marketing at Indiana University. But many young people still say they prefer do-it-yourself investing platforms like Robinhood and Acorns over traditional advisers at more established wealth-management firms.
Andrew Ragusa, a real-estate broker based on Long Island, blamed the twin problems of low housing inventory and high home prices for postponing younger buyers’ ownership. The median age of a first-time home buyer in the U.S. is 35-years old as of 2023, according to data from the National Association of Realtors. That is slightly down from an record high of 36 in 2022, but still two years older than the median age in 2021, which is representative of an ageing first-time buyer trend.
When he talks with younger clients now, he detects a gloomy sentiment. “They try to be optimistic, but the overall sentiment is ‘This is supposed to be the American dream: we get a house and we get some financial security and I just have to have faith it will all work out in the end.’ But they don’t have faith it will.”
Fear and shame around being able to buy or accomplish as much as one’s parents might have financially can crop up when millennials talk to elders about their financial frustrations, said Jodi Kaus, director of Kansas State University’s student financial planning centre, Powercat Financial. She’s found that lessons and advice from friends are often more constructive.
Kaus leads a peer-to-peer financial planning centre that pairs up students to work through financial issues. She works to pair people with similar backgrounds: graduate students with graduate students or international students with international students. Talking with someone only a few years removed from your current situation means you’re better able to internalize the messages and execute on their advice, Kaus said.
“Early on, parents even say ‘Are you sure students can help my child?’” she said. “And I say ‘I am more than confident that they can help each other.’
Sharing money tips and financial know-how with your friends doesn’t only benefit the asker, Kaus said. In the Kansas State University peer-to-peer group, the advice giver also learns a lot from their own position, because sharing their story and bonding with a peer helps them to build their own confidence and belief in their financial acumen.
Lindsay Clark, a 34-year-old director of external affairs in Washington, D.C., recalls one lesson she shared with a friend carrying student loans from pharmacy school. Clark works at Savi, a student loan platform, and she offered to cook her friend dinner while they sorted through his loan repayment options. Long after they’d cleaned their dinner plates, they sat together at Clark’s kitchen island, lingering over a plate of homemade hummus and chatting about everything from financial goals to Costco card benefits.
“Those conversations blossom from the transparency, and the visibility makes both people feel really good,” she said. “That creates better relationships overall.”
When you’re talking about money issues with friends, Clark said, you’re not artificially inflating your salary or pretending to know more than you do. And most important, you’re not worried about their ulterior motives.
“You feel safe in that conversation, knowing their intentions are good and they’re not trying to make money off of you,” she said. “And that’s going to lead to better results, because we’re working with the reality here.”
Skepticism of pronounced experts and criticism of established financial institutions is especially common among millennials and Gen Z, Neidermeier said. Studies show people across generations are much likelier to take a friend or colleague’s recommendation to heart over that of a faceless institution, he said; people who spend time on social media just have a greater opportunity to source those answers and field questions.
“What people say to each other over the picket fence is what is the most influential,” he said.
At a certain point, however, talking solely to friends and peers for your financial lessons can be very limiting, said Sarah Behr, founder of Simplify Financial Planning in San Francisco. Relying on your social circle can also put a strain on those relationships; no one wants to be responsible for your disappointment when a financial decision that worked out well for them doesn’t fit as well in your own life.
Behr recommends tuning into your own emotional reactions when assessing peer advice: does the road map they followed align with your own financial values? Does it put pressure on you to live outside your means or challenge your personal risk tolerance? If the answer doesn’t feel clear, that could be a time to outsource to a financial professional who has no emotional connection to you or your financial status.
“‘People have been telling me do this, but I just don’t know if it’s the right thing for me’—I get a lot of calls like that,” said Behr.
Saint-Vil said he and his friends share tips on what high-yield savings accounts offer the best rates, and when he did his credit card research, he chose a card recommended by a friend. When it comes time to work with a financial adviser or even one day a wealth manager, he’ll likely work with someone recommended through a peer. Behr said close to 90% of her business comes by way of client referrals.
Since that first conversation over dim sum, Saint-Vil has thrown his own card onto the table at meals and shared his knowledge with other pals who look confused.
“I have a real wide range of friends who are in many different financial places, but I would say a rising tide lifts all ships,” he said.
Julia Carpenter is the co-author, with Bourree Lam, of The Wall Street Journal’s “The New Rules of Money: A Playbook for Planning Your Financial Future,” a personal-finance workbook published this week by Clarkson Potter, an imprint of the Crown Publishing Group.
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Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
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.
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.
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.
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.
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.
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
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