According to Shopify’s announcement, Tinker consolidates more than 100 specialized AI tools, drawing on models from OpenAI, Google and Anthropic, organized not by model name or capability but by output: merchants browse by what they want to create, not by which tool produces it. The app covers images, videos, logos, product visuals and 360-degree product views. Each tool surfaces curated examples so a merchant knows exactly what it generates before committing any input.

The core mechanic Shopify built around is prompt abstraction. Rousseau Kazi, director of product at Shopify, said in the announcement that the team writes “very long prompts that are optimized for quality” and then reduces them to a few simple fields for the merchant to fill out.

The merchant describes their need in plain language; Tinker handles the technical prompting in the background. A brand described in one sentence generates a logo. A product photo becomes a social media video. Multiple creations can run simultaneously, so a founder can queue a batch of assets during a commute and review the results on arrival.

Tinker also maintains continuity across sessions. Because all assets live in a single environment, the app applies context from prior creations to new ones, preserving visual and brand consistency without having the merchant manually carry references between disconnected tools. When a new AI model launches from any of its provider partners, Tinker updates automatically, removing the recurring cost and learning curve of separately adopting each new capability.

Less Friction

The specific merchant cases Shopify cited in the announcement illustrate the operational problem Tinker aims to address. Lena, founder of jewelry brand Loire, generated more than 150 brand images for her store in her first month using the app, assets that consistently matched her feedback on the first or second attempt. The alternative, professional photography in the U.S., runs approximately $50 per shot, meaning a single product photographed from two angles costs $100 before any editing or reshooting. For a brand still building its initial catalog, that unit cost forecloses iteration entirely.

Yukiko, founder of supplement brand Allie Beauty Protein, identified a different constraint: general-purpose generative AI tools produce visually compelling images but inaccurately render product label text, a significant commercial problem for supplement brands that are legally required to include nutritional information on packaging. Tinker’s specialized prompting layer, built for specific output types rather than general-purpose generation, resolved that gap for her use case.

Shopify’s Broader Agentic Bet

As reported by PYMNTS, Shopify’s AI Store Builder, introduced in May 2025, already lets merchants generate full store layouts from descriptive keywords without writing code. Tinker extends that capability into the creative layer above the storefront, handling the brand assets and marketing materials that fill a store once its structure is in place.

The strategic logic behind both tools connects to where Shopify sees commerce heading. As reported by PYMNTS, Shopify President Harley Finkelstein argued at the Upfront Summit in March 2026 that agentic AI will act as a personal shopper, surfacing products based on contextual fit rather than keyword bids or paid placement.

In that environment, the quality and consistency of a merchant’s brand presentation carry more commercial weight than they do in a search-optimized storefront. Tinker is a standalone app for anyone who wants to experiment with AI tools before agentic discovery becomes the primary commerce channel.

The broader market context reinforces the timing. According to Google Labs, the company introduced Photoshoot on its Pomelli platform in February 2026, a free tool that converts basic product images into studio and lifestyle imagery using its Nano Banana model, with brand context automatically applied from stored business information.

For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

The same week, lab testing company Function announced a connector that lets its members pipe lab results and clinician-reviewed summaries directly into Perplexity Health.

Those moves follow OpenAI’s ChatGPT Health and Microsoft’s Copilot Health on March 12, bringing the number of major AI platforms with dedicated consumer health products to five in under three months.

In the U.S., 3 in 5 adults used AI tools for health purposes in the past three months. About 70% of AI health conversations occur outside clinic hours, and roughly 1.6 million to 1.9 million messages per week on ChatGPT focus on health insurance questions, according to PYMNTS coverage. The platforms responding to that demand are not building the same product. They are building different layers of the same stack.

Vertical Stack: Amazon Owns the Full Care Workflow

Amazon builds vertically. Its Health AI agent does not hand users off to another system. It handles the question, the appointment, the prescription and the specialist referral inside one product, connected to one provider network.

Health AI answers health questions, explains lab results and medical records, manages prescription renewals and connects users to One Medical providers through message, video or face-to-face visits. The system runs on Amazon Bedrock as a multi-agent architecture: A core agent handles patient communication, sub-agents oversee specific tasks, auditor agents review conversations in real time, and sentinel agents escalate to human providers when needed.

Prescriptions are routed to Amazon Pharmacy or any pharmacy of the user’s choice. One Medical maintains clinical partnerships with Rush University System for Health and Cleveland Clinic for specialist referrals, with Health AI routing patients across those networks.

Horizontal Stack: Perplexity Aggregates Any Source

Perplexity builds horizontally. Perplexity Health does not tie users to a specific provider network. It pulls data from across fragmented health data and surfaces answers from it all at once.

Perplexity Health launches with connectors for Apple Health, electronic health records from more than 1.7 million care providers, and wearable platforms including Fitbit, Ultrahuman and Withings.

A question about resting heart rate draws on that user’s cardiac history, recent bloodwork, and activity logs. Answers draw from clinical guidelines and peer-reviewed journals, with each response connected directly to source material.

Health data is encrypted in transit and at rest, is not used to train AI models and is not sold to third parties. The product is available to Pro and Max subscribers in the U.S. on iOS and at perplexity.ai/health.

Function is a company that provides lab testing and clinician-reviewed biomarker insights. It announced a partnership with Perplexity Health to integrate this data into the AI system, with CEO Jonathan Swerdlin noting, “AI is most powerful when it’s personal,” as the collaboration helps turn fragmented health data into useful insights.

OpenAI and the Scale of the Shift

OpenAI established the category in January with ChatGPT Health as reported by PYMNTS. The usage numbers behind the launch explain the competitive urgency. More than 230 million people globally ask health and wellness questions on ChatGPT every week, according to TechCrunch.

Among U.S. adults who used AI for health in the past three months, 55% used it to check symptoms, 48% to understand medical terms and 44% to learn about treatment options, according to OpenAI.

As PYMNTS covered, AI agents in healthcare are moving from pilots to live deployments across patient engagement, care coordination, clinical documentation and chronic care management.

Amazon operates a vertically integrated model, combining its AI, provider network, pharmacy and billing into a single system. Perplexity takes a horizontal approach, offering one interface that sits across providers, wearables and labs. While OpenAI brings the largest distribution channel, with 230 million weekly health users and a multiyear lead in clinical model development. Each approach is distinct, but together they point to a consumer healthcare system where AI becomes the first point of interaction before any clinician is involved.

For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

For banks, the timing is not incidental. The industry has already embedded AI into core operations, a process that has been in the works for years. PYMNTS Intelligence data from 2024 shows that nearly three-quarters of finance leaders reported their departments were using AI, with applications spanning fraud detection, risk management and automation. These are the operational systems that influence how accounts are opened, how transactions are approved and how risk is priced.

The White House-directed push toward a national framework signals that policymakers are unlikely to regulate AI as a stand-alone distinct category. AI is being positioned as a capability that will be absorbed into existing financial rules, rather than governed through a standalone regime. That approach carries consequences for banks.

AI Within Existing Regulatory Boundaries

By extension, AI inherits the rules that already govern the activities it touches. A fraud model that declines a transaction is subject to the same expectations as any other payment decision. An onboarding model that flags a customer is bound by the same requirements that govern identity verification and fair access.

If a model contributes to an erroneous denial, a missed fraud event or a discriminatory outcome, the responsibility rests with the institution that deployed it. The technology becomes inseparable from the financial action it enables.

The 2025 State of Fraud and Financial Crime report illustrates how deeply AI is already embedded in that decision layer. Financial institutions are shifting toward intelligence-driven fraud defenses, combining machine learning and behavioral analytics to manage increasingly complex threats. At the same time, 68% of institutions have increased fraud detection spending, reflecting the central role these systems now play in operational risk management.

Fraud, Identity and the Weight of Decisions

The same report underscores why regulators are unlikely to treat AI outputs as abstract or experimental. Unauthorized-party fraud now accounts for 71% of incidents and losses, driven by credential theft and account takeovers. These are precisely the areas where AI is deployed to make real-time judgments about identity, authorization and intent.

In that context, AI-driven decisions are indistinguishable from the financial actions they trigger. When a model approves a payment or allows account access, it is participating in a regulated activity. When it fails, the consequences extend beyond losses to include reputational damage and erosion of customer trust, which half of institutions report experiencing.

From Outputs to Accountability

For banks, AI-driven identity checks, fraud decisions and payment approvals will not be assessed as technological outputs. They will be judged as financial decisions subject to established consumer protection, anti-fraud and compliance frameworks.

This distinction alters how institutions must approach model development and deployment. Performance metrics such as speed and accuracy remain important. But in addition, models must be explainable, auditable and consistent with regulatory expectations that were designed for human decision-making but now apply to automated systems.

The shift also exposes gaps between adoption and readiness. While AI usage is widespread, the PYMNTS Intelligence 2024 data points to persistent concerns around consumer trust, cybersecurity exposure and regulatory uncertainty. Those concerns now take on added weight as policy begins to formalize expectations.

The Read Across for Banks

The next phase of competition will hinge on which institutions can demonstrate that their models produce outcomes that withstand examination by regulators, auditors and, if necessary, courts.

This is a different kind of arms race. It places a premium on governance and model transparency. It also requires tighter integration between risk, compliance and technology teams, as decisions once made in isolation are now subject to broader institutional accountability.

New research by Anthropic shows that more people would say “yes” to the first part of that question than to the second.

The findings—released last week and flagged in a report Sunday (March 22) by the Financial Times (FT)—showed that just under 27% of respondents said they were most concerned about mistakes made by AI.

“I had to take photos to convince the AI it was wrong — it felt like talking to a person who wouldn’t admit their mistake,” said a user from Brazil quoted in the report.

“The hallucinations were a disaster. I lost so many hours of work,” said a German entrepreneur, one of 81,000 people interviewed for the study.

Meanwhile, 22% said they were worried about AI’s impact on jobs and the economy, while 16% mentioned “cognitive atrophy” or a loss of critical thinking.

“The risk isn’t losing your ability to think — it’s losing your perspective: you start adopting the AI’s way of structuring things without even noticing,” a user from Germany said.

Deep Ganguli, who heads Anthropic’s societal impacts team and oversaw the research, told the FT the project was designed to “collect this rich human experience using Claude, so it could really inform our research agenda, change our research agenda, change the way we think about building our products, deploying our products.”

The findings come amid a wave of AI-related job losses, with several companies pointing to the technology when announcing layoffs recently.

But as PYMNTS has written, although job cuts tied back to AI invariably foster fears of a larger employment crisis, current labor research indicates that the situation is more complex.

That report cited findings from the World Economic Forum, which argued that while automation and AI will eliminate the need for certain tasks, they will also bring about new categories of work, especially in data, AI oversight, cybersecurity and human-centric services.

The report stressed that this will lead to a time of transition rather than permanent contraction. Many workers’ skills are expected to evolve in the next five years, which will mean retraining and adaptation.

“The pressure is real, but it is directional. Roles centered on routine information processing are most exposed. Roles combining domain expertise, judgment and technological fluency are expanding,” PYMNTS added.

For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

The framework aims to provide a consistent national policy, the White House said in a Friday press release.

“Importantly, this framework can succeed only if it is applied uniformly across the United States,” the White House said in the release. “A patchwork of conflicting state laws would undermine American innovation and our ability to lead in the global AI race.”

The framework’s objectives include protecting children and empowering parents by providing account controls, safeguarding and strengthening communities by making it easier to secure permits for on-site power generation at data centers, and supporting creators by respecting intellectual property rights while also allowing fair use by AI.

The framework also calls for protecting free speech by preventing AI systems from being used to silence political expression, enabling American dominance in AI by removing barriers to innovation, and developing an AI-ready workforce by expanding workforce development and skills training programs.

“The Administration looks forward to working with Congress in the coming months to turn this framework into legislation that the President can sign,” the White House said in the release.

President Donald Trump signed an executive order in December 2025 that directed the federal government to establish a new national approach to AI and to push back against state-by-state AI rules the administration said are slowing AI innovation.

It was reported Tuesday (March 17) that AI companies and investors have clamored for Congress to enact a single, federal standard that would override the growing patchwork of often conflicting state AI regulations.

Currently, around 20 states have passed comprehensive privacy laws covering AI and several others have passed more limited measures.

It was reported in February that Utah had become the latest flashpoint between states and the White House over AI regulations. As a bill regulating AI was being considered by the state’s legislature, the White House Office of Intergovernmental Affairs sent a letter to a state senator saying that the bill is “unfixable” and “goes against the Administration’s AI Agenda.”

Stablecoins, after all, have been able to basically make their name on just their promise alone to innovate and disrupt the cross-border settlement space. As recently as Tuesday (March 17), PayPal expanded the availability of its dollar-backed stablecoin PayPal USD (PYUSD) and now offers it in 70 markets worldwide.

But stablecoin flows represent an infinitesimally small portion of cross-border payment volume. Payments originating from Latin America and Africa, two supposed digital asset hot spots, each account for less than $1 billion. Stablecoin payment activity today is driven almost entirely by payments sent from Singapore, Hong Kong and Japan, per McKinsey.

Beneath the headline crypto noise, however, a more powerful, real-world transformation has been unfolding. Traditional payment rails, long criticized for being slow, opaque and expensive, are undergoing a structural upgrade.

Three main advances are driving change: real-time rails are expanding globally, FX costs are shrinking and APIs are turning payments into software and streamlining local and multicurrency collections.

And unlike many crypto-native experiments, these changes are already delivering measurable impact at scale. The news Wednesday (March 18) that J.P. Morgan Payments and Mastercard have launched a new virtual card in Europe, for example, is likely to drive far greater actual cross-border volume than any stablecoin expansion could.

Read more: Trade Disruptions Tie Up Cash and Test CFO Playbooks 

Why Stablecoins Aren’t the Main Story

The broader story is that many of the benefits associated with stablecoins, such as speed, lower costs and flexibility, are now being delivered within the existing financial system. They are being delivered in a way that is integrated with regulatory frameworks, banking relationships and enterprise workflows.

In other words, the transformation of cross-border payments is not waiting for a new system to replace the old one. It is happening within the system itself.

While cross-border payments have been constrained by the limitations of domestic systems, that divide is now closing. Real-time payment networks are proliferating rapidly across major economies, from Europe to Southeast Asia to Latin America.

More importantly, interoperability between these systems is improving. Bilateral and multilateral linkages are enabling funds to move directly between countries without defaulting to legacy correspondent banking chains.

And if speed has been the most visible pain point in cross-border payments, cost has been the most persistent. Foreign exchange spreads, intermediary fees and hidden markups have long made international transactions expensive and unpredictable.

But advances in treasury technology are enabling businesses to manage currency exposure more proactively, reducing the need for costly last-minute conversions. At the same time, a combination of increased competition, better pricing data and more efficient liquidity management is driving FX costs downward.

Perhaps most importantly, payment providers are rethinking how FX is integrated into the transaction flow. Instead of treating currency conversion as a separate, opaque step, it is increasingly embedded into the payment process itself, with real-time pricing and clear disclosures.

See also: B2B’s Biggest Innovation Isn’t Technology. It’s the Buying Experience 

Payments Are Becoming Software

The third, and perhaps most transformative driver of change, is the rise of API-driven payment infrastructure. In the past, integrating with cross-border payment systems required significant manual effort, custom integrations and ongoing operational overhead. Payments were something businesses executed, not something they could easily embed into their products or workflows.

With APIs, however, instead of building separate processes for each market, companies can create unified payment experiences that adapt dynamically to local requirements. Collecting funds in multiple currencies, reconciling transactions and routing payments through the most efficient corridors can all be automated.

“There are expectations both on buyer sides and supplier sides for things to become a little bit more digital and automated,” Rene Stynen, senior vice president, EMEA, B2B Payments at Boost Payment Solutions, told PYMNTS in an interview this month.

“Embedded payments, where the payment becomes invisible in the procure-to-pay process, is what everyone wants,” Stynen added. “You don’t want the payment as a separate step.”

A company can, for example, accept payments in local currencies from customers around the world, hold those funds in multi-currency accounts, and disburse them to suppliers or partners without unnecessary conversions. The result is a more efficient flow of funds and a better experience for all parties involved.

For global businesses, this shift opens up new possibilities. Entering new markets becomes less about navigating complex payment infrastructures and more about executing a coherent go-to-market strategy. Managing suppliers and partners across borders becomes more predictable and less resource-intensive. And delivering a consistent customer experience becomes achievable, even in highly fragmented markets.

For all PYMNTS B2B coverage, subscribe to the daily B2B Newsletter.

The latest Bureau of Economic Analysis (BEA) data, released Friday (March 13), shows that income growth picked up in January and inflation remained relatively contained. Spending continues to outpace income in real terms, while overall economic growth slowed sharply at the end of 2025. The result is an economy that is expanding, but with consumers carrying much of the momentum while managing rising costs and limited financial buffers.

January’s personal consumption expenditures (PCE) data shows a consumer economy still moving forward, but with signs of strain beneath the surface.

Personal income rose 0.4% for the month, continuing a steady trend after increases of 0.3% in December and 0.4% in November. Compensation growth accelerated to 0.5%, while asset income, particularly dividends, jumped 1.2%. Disposable income rose faster, climbing 0.9%, largely because personal taxes dropped 3.2%, a seasonal shift often tied to withholding changes.

Consumers spent that additional income quickly. Personal consumption expenditures rose 0.4% for the month, matching December’s increase. The composition of that spending reveals a familiar pattern in the post-pandemic economy: services continue to dominate, especially necessities like housing and healthcare. Spending on services rose 0.7% in January, while goods spending fell 0.4%. Durable goods purchases dropped 0.7%, suggesting households are pulling back on larger purchases.

Inflation remained moderate but persistent. The PCE price index increased 0.3% for the month and 2.8% year over year, while core PCE rose 3.1%. Services prices climbed 3.5% annually, outpacing goods prices, which increased 1.3%.

When adjusted for inflation, the imbalance becomes clearer. Real disposable income is up 1.8% year over year, while real consumer spending is up 2.4%. In other words, consumers are still spending faster than their incomes are growing.

At the broader economic level, growth slowed sharply. Friday’s data showed that GDP increased at an annualized rate of just 0.7% in the fourth quarter of 2025, well below the 4.4% pace recorded in the third quarter. Declines in government spending and exports drove much of the slowdown, while consumer spending and private investment continued to support the expansion.

The Affordability Gap Behind the Numbers

These data points highlight the widening gap between economic resilience and financial comfort.

The recently released PYMNTS Consumer Expectations Index (PCEI), which measures not just consumer sentiment but also their perceived ability to spend, found that how Americans feel has a lot to do with their financial lifestyle. Households not living paycheck to paycheck maintain relatively positive feelings, while consumers struggling to pay bills remain deeply negative about their financial position.

At the same time, Americans broadly report feeling confident about their ability to manage debt but less certain that their overall financial position is improving. That combination supports steady spending in the near term but leaves households with less cushion if conditions worsen.

Looking at affordability specifically can help explain why the macro data can look healthy while consumer sentiment remains uneasy. Rising prices for everyday necessities like groceries, housing, insurance and transportation have fundamentally changed how households think about spending decisions. Affordability conversations used to revolve around discretionary choices such as vacations or large purchases. Today, they increasingly center on managing cash flow and covering essentials.

The January income and spending data reinforces that reality. Paychecks are growing and inflation has cooled from its peaks, yet spending continues to run ahead of income in real terms. For businesses watching consumer demand, that dynamic suggests the same pattern PYMNTS research has been tracking for months: resilient spending, but with increasingly thin financial margins supporting it.

The bill, which was introduced Tuesday (March 10), would set the hourly minimum wage for employers with more than 500 employees at $30 by 2030 and for those with fewer than 500 employees at $29 by 2031, according to the website of the New York City Council.

New York City’s minimum wage is currently $17 per hour, according to the WSJ report.

Other cities whose minimum wages are among the country’s highest include Seattle, at $21.30 per hour, and Los Angeles, whose minimum wage for hotel and airport workers will rise from $20.32 to $30 by 2028, the report said.

If the New York City bill becomes law, the minimum wage would still fall short of what the Economic Policy Institute calculates to be a living wage in the city. While the organization says a single person needs an annual income of $83,262 for a living wage in the New York metro area, the bill’s minimum wage would provide $62,400, per the report.

One business owner interviewed by the WSJ said a wage increase would make it impossible for people to open new restaurants. Another, who owns five restaurants and a cocktail lounge, said he would have to cut a dozen jobs and require customers to place orders on their phones. A third business owner said the higher minimum wage would be fair and would help employers retain workers.

New York State Restaurant Association President Melissa Fleischut said in the article: “We feel like we’re at a tipping point with consumers. There’s only so much you can charge for a slice of pizza or a cheeseburger.”

City Council Member Carmen N. De La Rosa said in a post on X that the bill would ensure “the pockets of NYC’s workforce match the reality of today’s economy and rate of inflation.”

A separate New York City law requiring companies to offer grocery delivery workers the same minimum pay that restaurant delivery workers are eligible for, went into effect in January.

The U.S. Office of the Comptroller of the Currency (OCC) is receiving so many applications for digital asset-focused national trust charters that a lobbying group for the traditional financial sector, the Bank Policy Institute (BPI), is considering suing the banking regulator over its decisions to approve so many crypto, payment and FinTech companies for them.

Many crypto and crypto-interested financial firms are pursuing national trust bank charters because they allow custody and tokenization without the heavy regulatory burden of deposit-taking banks.

During 2025 alone, the OCC received 14 de novo charter applications, a number nearly equaling the total applications received by the agency in the previous four years combined.

Now, barely 2½ months into 2026, the OCC has already approved four new applications and received north of seven.

Digital lender Upstart on Tuesday (March 10) became the latest U.S. FinTech seeking a banking charter, applying to the OCC and the Federal Deposit Insurance Corporation (FDIC) to establish an insured national bank.

And while conditional approvals and actual operational status are two very different things, the direction of travel across banking implies that regulated infrastructure providers, not consumer interfaces, could be the most valuable layer of finance.

See also: Bank Charters Are Reshaping Who Can Compete for Consumer Deposits 

Making Sense of Banking Charters

A predominant feature of the current charter wave is that many applicants are not seeking to become traditional banks. Instead, they are pursuing licenses that allow them to perform specific financial functions.

The pace of activity may be easiest to understand when visually mapped across approvals and pending applications.

 

As highlighted in the chart, despite the rush of approvals and applications, conditional approval does not mean a bank is operational. To launch, firms must meet additional regulatory requirements, including capital thresholds, governance structures, and operational readiness standards.

Protego’s own case highlights how difficult that transition can be. The company initially received conditional OCC approval in 2021 but failed to meet the required conditions before the approval expired. It was conditionally approved by the Treasury agency for a second time in February.

A bank charter “is not a trophy, and it certainly isn’t a product label, but it’s a public trust,” Rodney E. Hood, former acting comptroller of the currency, said in an interview with Competition Policy International, a PYMNTS company, in January.

“A federal charter should never be construed as an end run around supervision, and it should certainly never be a pathway to scale without accountability,” Hood added.

See also: Can Crypto’s Open Network Dreams Survive Going Corporate? 

The FinTech Charter Strategy

Behind the charter race could lie a shift in how financial value is being created.

Historically, consumer banking has been dominated by institutions controlling deposits and lending. But digital assets are creating new layers of financial infrastructure across custody, settlement networks, tokenized securities, and blockchain-based payment rails. The companies controlling these layers may end up capturing the most value.

Research by PYMNTS Intelligence has found that 62% of Generation Z consumers would consider using a neobank as their primary bank account provider, “a striking level of openness that outpaces all other generations,” as covered here in October.

The implications, according to a paper published last month by economists Michael Junho Lee and Donny Tou at the Federal Reserve Bank of New York, could be systemic. The New York Fed report found that stablecoins do more than compete with bank deposits. They alter the liquidity demands placed on the banks that serve them. In doing so, they encourage a more reserve-heavy and potentially less loan-intensive banking model.

This model resembles what economists often call a “narrow bank.” Such institutions focus on safeguarding assets and facilitating payments while maintaining high levels of liquidity and minimal credit risk. In contrast, conventional commercial banks generate revenue primarily by transforming deposits into loans.

Regulation, as always, will have a key role to play in the future of the banking ecosystem. The PYMNTS Intelligence and Citi report “Chain Reaction: Regulatory Clarity as the Catalyst for Blockchain Adoption” found that blockchain’s next leap will be shaped by regulation. While evolving guidance is starting to create the foundations for safe, scalable blockchain adoption, “implementation challenges … continue to complicate progress.”

The Consumer Price Index rose 2.4% year over year in February, according to data released on Wednesday (March 11) and increased 0.3% month over month on a seasonally adjusted basis, according to the Bureau of Labor Statistics.

That annual pace matches the reading recorded in January, indicating that broad price pressures remain relatively stable across the economy.

 

The data arrives before what economists increasingly view as a possible inflationary jolt tied to geopolitical tensions and energy markets. Energy prices rose 0.6% in February and Brent crude prices were roughly 33% higher than a month earlier, a surge that could ripple through transportation, logistics and consumer prices if sustained.

For now, however, the inflation picture remains uneven. While headline inflation sits near the Federal Reserve’s long-run target, several everyday spending categories continue to climb at a faster rate.

Services and Essentials Continue to Apply Pressure

A closer look at the CPI components reveals that certain segments still exceed the overall index. Shelter costs rose 3% over the past year and food prices increased 3.1%. Within food spending, meals away from home climbed 3.9% during the same period, while food at home rose 2.4%.

Service categories also continue to account for a large portion of inflationary momentum. Services excluding energy increased 2.9% year over year, and medical care services rose 4.1% over the same period.

These categories matter because they dominate household budgets. Housing, groceries and healthcare represent recurring expenses that are difficult to postpone or substitute, which means even modest price changes affect household finances.

Consumers have responded to those pressures with adjustments that extend beyond simply buying less.

Research from PYMNTS Intelligence indicates that financial strain increasingly shapes how households shop and pay. Many consumers facing tighter budgets are shifting toward online retail and digital payment methods that offer greater visibility into spending or access to flexible financing.

The findings suggest that financial pressure does not necessarily suppress spending outright. Instead, it changes how consumers structure purchases and manage payments.

Food Costs and Financial Stress Shape Payment Choices

Food spending illustrates this shift particularly clearly. Grocery purchases often serve as a barometer for inflation, yet purchasing behavior suggests that households are adapting rather than withdrawing.

Consumers experiencing financial stress often spend more per grocery transaction than those with lower financial strain. In one example cited in PYMNTS Intelligence research, high-stress consumers spent an average of $109 on their most recent grocery purchase compared with $95 among low-stress consumers.

This pattern may reflect consolidation of purchases or efforts to stretch trips to the store. It also suggests that households increasingly rely on financial tools that allow them to smooth spending across pay cycles.

Digital wallets and installment features play a growing role in that process. Among consumers experiencing financial pressure, the share using digital wallets for retail transactions rose notably during 2025, and wallet usage is often linked to access to buy now, pay later options.

Karen Webster, CEO of PYMNTS, noted on Wednesday that consumers are not primarily focused on maximizing rewards or loyalty programs. Instead, they are trying to manage cash flow and maintain flexibility in the face of unpredictable expenses.

“Consumers are constantly managing the gap between paychecks, sometimes consciously, often on autopilot,” Webster wrote, noting that credit cards, installments and BNPL serve as tools for navigating that gap rather than competing products in the consumer’s mind.

Her observation reflects a broader shift in consumer finance behavior. Households increasingly view payment methods as interchangeable mechanisms for balancing income timing and expenses.

Installments Likely to Remain Central as Inflation Evolves

If energy markets push inflation higher in coming months, those flexible payment tools may become even more central to consumer spending behavior.

Many households already operate under tight financial constraints. Research shows that roughly two in three Americans live paycheck to paycheck, even if they do not always report outright shortfalls in meeting expenses.

That reality means that even moderate price increases can influence how purchases are financed. Installments and BNPL plans allow consumers to convert immediate expenses into predictable payments, which can help preserve liquidity during periods of uncertainty.

If inflation accelerates again due to higher energy prices or geopolitical disruptions, the trend toward installment-based spending is unlikely to reverse. Instead, consumers will continue doing what they have quietly done for years: assembling a stack of financial tools that allows them to manage cash flow one purchase at a time.