Couples Embrace the Least Romantic Date Ever: The Money Date
The case for making financial plans over candlelit dinners
4 min
To set the mood for poring over budgets and savings goals, Tierra Bates and her husband, Gregory, get dressed to the nines and head to dinner at a fancy steakhouse.
“We’re discussing things, but we’re celebrating at the same time,” said Bates, a school therapist and real-estate agent in Shelby, N.C. “Treating ourselves while still talking about the goals we have in mind.”
This mix of romance and finance has been dubbed a money date by financial advisers and others in the business of building wealth. The idea is to carve out time for the sort of conversations couples often dread by making it an event to look forward to.
Advisers and relationship counsellors say couples who go on regular money dates can better manage their spending, saving and investing. Since disagreements over money can strain marriages, having regular open discussions about financial decisions in a fun and intimate way can help address any troubles before they become a source of resentment.
“I have even suggested to clients, ‘Have the money date in your sexy clothes,’” said Christine Luken, a financial coach based in Cincinnati. “Just go ahead and have it naked—as long as you get the money stuff done.”
Bates and her husband plan money dates throughout the year. In January they set goals for the year, then they set up shorter quarterly follow-ups, as well as brief monthly check-ins for short-term concerns and week-to-week budgeting.
At their August check-in, Bates and her husband visited a local food hall and hired a babysitter to keep the focus on the big conversation: the Bates’s back-to-school budget.
Talking about something as stressful as the school year can bring up a lot of emotions, Bates said, but the money date gives them a specific time to work through everything together. Plus, doing it with good food and adults-only time makes it more enjoyable.
The art and science of the money date
Turning financial planning into a date might sound like a mismatch, but science backs up the premise. It is a form of temptation bundling, pairing a less exciting task with a more exciting reward, that research suggests can actually help people change their habits, said Scott Rick, associate professor of marketing at the University of Michigan.
“Pair the want with the should in order to entice you to do the should,” he said. “Get each other money date presents. Open the nice bottle of wine. Say, ‘This is the night we order in from the best restaurant in town.’”
You might have to spend money to make better money decisions, as counterintuitive as that might seem. As Adam Kol, a financial therapist based in Fort Lauderdale, Fla., likes to remind his clients: “You don’t get bonus points for having a money date if you’re sitting in a dark room and you’re in a miserable mood.”
Box-office receipts
When Megan and Bronson Allen got married in 2019, the Chicago-based couple pooled their finances. They also set up a regular recurring calendar invite that prompted them to sit down together to go over savings, investments and personal-account expenditures.
Megan will pop a big bowl of popcorn and project their laptop onto the TV screen so they can review the money-date agenda items almost “more like a game or a movie that’s playing,” Bronson said.
They have taken their laptops to a coffee shop and cozied up while reviewing coming travel and other big purchases. They also tried a double money date with Megan’s brother and his wife.
“It’s about finding ways to make them kind of lighthearted, like a date and not like a chore,” said Bronson, a 33-year-old software designer.
Their money dates can take several forms, Megan, a 28-year-old product designer, said. Sometimes they look at the calendar and plan travel spending for the month. Or they look back at the previous month’s budget and compare it to the bank statement.
Then there are pitch days, when one of them makes the case for an especially big purchase or financial goal. On a recent money date, Bronson made the case to take some money from their shared account to invest in a new road bike for his triathlon training, laying out his plans as he and Megan mixed drinks.
“I’ve been running the numbers, and this is what I’m thinking, and this is the account it would come from,’” he told her.
They landed on a compromise: Bronson would sell his old bike to invest in the newer one.
Making a first money date
For couples looking to set up their first-ever money date, Kol recommends reviewing the most recent credit-card statement as a duo. When both partners are looking at the transaction history, they are better able to get on the same page about what needs to be done about recurring subscriptions or spendthrift tendencies.
“It doesn’t have to be ‘I can’t believe you spent this, we need to cut this,’ but instead ‘Let’s make sure nothing weird is going on here. Let’s make sure our kid isn’t charging $700 to Candy Crush,’” he said.
From there, you can build onto your money dates and introduce different themes or topics to organise them. For example, maybe one month you and your partner review your respective student-loan payment plans, and the next you could price out travel options for a coming vacation.
“Having that monthly touchpoint allows you to feel like ‘OK, if I have a concern, it’s not going to go on indefinitely. I’ll have a chance to talk to them, I don’t have to confront them,’” Kol said.
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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.
4 minA 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
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