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How BILL is becoming the financial backbone of the SMB economy

For most small and midsize businesses, financial operations remain a tangle of disconnected systems: A payroll platform over here, an ERP over there, and a manual AP process stitching them together with spreadsheets. 

BILL has spent the past year making a systematic argument that this doesn’t have to be the case. Through a rapid series of embedded partnerships and a suite of AI Agents, the San Jose-based fintech is positioning itself as the infrastructure layer that powers intelligent finance across the platforms SMBs already trust.

Proving the model: Building where businesses already work

Embedded finance partnerships between payroll, ERP, and AP platforms are still nascent, and the playbook for doing them well is still being written. BILL’s approach offers an early view of what that playbook might look like.

In the span of just a few months in late 2025, BILL announced embedded partnerships with three of the most consequential platforms in the SMB stack – two ERP platforms and a payroll provider – demonstrating how a single payments infrastructure layer can be woven into the platforms SMBs already rely on daily.

ERP platforms: BILL’s AP automation embeds directly into ERP platforms, giving customers a payment experience, capturing bills, paying vendors, and reconciling payments in real time, all without leaving their system of record.

Payroll and HR platforms: Integrating AP into payroll platforms alongside HR functions brings people management and vendor payments together for the first time — a combination that reflects the converging expectations of SMB operators.

Russell Kornman, Director of Product, Developer and Partner Platform at BILL, describes the approach as deliberately choosing depth over reach. “When a partner chooses BILL, they’re not just outsourcing payments plumbing,” he says. “They’re choosing to not rebuild something that already exists and is hard to get right. AP and payments aren’t just features – it’s rails, KYC/KYB, vendor onboarding, risk, and compliance. That’s years of work and ongoing cost.”

The beginning of a broader industry trend

These partnerships are still early-stage, proof points in what BILL views as a long-term infrastructure play. The embedded finance category is young, and the integrations being built today may look markedly different in three to five years. What matters now is who is developing the conceptual framework for how this should work.

BILL’s early moves suggest it is competing to define that framework. By embedding payments rails, compliance infrastructure, and an eight-million-business network into partner platforms — rather than building a standalone destination product — BILL is making a deliberate bet on where SMB financial operations are heading: away from point solutions and toward unified, intelligent workflows that work inside the tools people already use.

From system of record to system of execution

What makes the ERP integration model technically significant is how it reframes what an ERP is actually for. Traditional ERP implementations treat the system as a ledger, a place to record what happened. BILL’s embedded model pushes that further.

“Embedding BILL into an ERP turns AP from a multi-system process into a single flow,” says Kornman. “Users can select bills, pay them, and see status and reconciliation come back in near real time, all without leaving the ERP. That removes things where breaks occur for customers today: exports, file uploads, duplicate entry,” he added.

For cloud ERP customers, a complementary integration adds an AP layer alongside existing receivables capabilities.  Together, they create a complete pay-in and pay-out experience inside one platform. “BILL’s role is bringing a best-in-class AP engine and payments network into these systems  so customers get a stronger AP experience without the platform having to build and maintain it themselves,” Kornman said.

Converging people and payments

There is a convergence of workforce management and financial operations unfolding in the SMB space. For SMBs that have historically juggled HR, payroll, and vendor payments across separate systems, the direction of travel is toward a genuinely unified back office.

Kornman frames it as both a product opportunity and a strategic one. “Payroll, HR, and vendor payments are converging, and customers increasingly want that in one place. By embedding BILL inside a leading payroll platform, we become the financial operations layer within the HR tools SMBs already rely on.”

According to BILL’s research, 62% of SMBs cannot immediately view their current cash position across all accounts, and nearly 40% of businesses that haven’t yet automated their financial operations plan to do so within six months. Integrations like this meet that demand by delivering clarity, speed, and control inside a platform hundreds of thousands of SMBs already use daily.

The network effect at scale

Underlying all three partnerships is an asset that competitors would find difficult to replicate quickly: BILL’s network. With more than eight million businesses connected across its platform, BILL processes roughly 1% of U.S. GDP annually. When any partner embeds BILL, they gain instant access to a vendor network that reduces onboarding friction, accelerates electronic payments, and raises the floor on payment security.

“Customers can increasingly find and pay vendors already on the network, which reduces onboarding friction, cuts down on checks, and drives more secure electronic payments,” Kornman notes. “As more customers join the network, the experience only improves.”

This network advantage compounds over time, and it provides the foundation for BILL’s most ambitious move yet.

Agentic AI and the Fortune 5 million

In late October 2025, BILL launched BILL AI: A suite of AI agents specifically designed for what CEO René Lacerte calls the “Fortune 5 Million”: the small and midsize businesses that power the U.S. economy but have historically been underserved by enterprise-grade automation.

The initial agents are focused on eliminating the most painful manual workflows in SMB finance: BILL’s W-9 agent autonomously requests, collects, and pre-validates tax forms from vendors, eliminating over 80% of the manual steps in a process that over 90% of business leaders describe as the most painful part of tax season. 

Other agents like the reconciliation agent automatically codes card transactions so receipts reconcile themselves, with early rollouts showing a 533% increase in transactions coded entirely by AI. An agentic onboarding feature for Spend & Expense automatically creates virtual cards and permissions so new employees can begin spending compliantly from day one.

These agents are trained on more than $1 trillion in transactions and 1.3 billion documents – proprietary data that gives BILL’s AI a head start no synthetic dataset can replicate. And critically, they are woven directly into the embedded partner ecosystem. “Instead of building their own AI stack, partners will be able to offer capabilities like automated invoice capture and coding, anomaly detection, and approval recommendations,” says Kornman. “That raises the bar for what their platforms can deliver without adding complexity on their side.”

The embedded finance model is still early. The partnerships being built today are first-generation integrations, and the industry is still working out what “done” looks like. But BILL’s approach – leading with infrastructure, network effects, and proprietary AI, reflects a considered view of where SMB financial operations are heading. In a fragmented market, the company that builds the rails often ends up running the trains.

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Forget the earnings. Watch where these fintechs are placing their bets.

    Weekly 10-Q

    The weekly 10-Q newsletter is part of the Tearsheet Pro subscription, where I unpack the recent moves and strategies of leading banks and fintechs in the public space, coupled with stock market analysis. In your inbox every Friday!

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    Forget the earnings. Watch where these fintechs are placing their bets.

    Chime, Block, and Circle each used the quarter to explain where fintech’s next moat will come from.

    This week, Chime, Block, and Circle all delivered solid 2026 second quarters. Each firm used the moment to explain a much bigger strategic shift: Chime is turning direct deposits into a lending advantage, Block is rebuilding its operating model around AI, and Circle is racing to become infrastructure before stablecoins become commoditized.

    For Chime, direct deposit becomes a lending moat

    Direct deposit has been fintech’s favorite engagement metric. Convince customers to route their paycheck into your account, and they’ll likely stick around longer and use more products.

    Chime’s latest quarter suggests the company now sees direct deposit as its underwriting infrastructure.

    Instant Loan originations climbed nearly 70% sequentially to $300 million, while MyPay, Chime’s earned wage access product, generated $4.5 billion in originations. Those businesses are expanding because recurring payroll deposits give the company continuous visibility into a member’s income, cash flow, and repayment behavior.

    CEO Chris Britt described it as the company’s “success in developing primary account relationships,” adding that “these recurring direct deposits drive more precise underwriting and an advantaged loan repayment position.”

    That philosophy runs through Chime Prime, the company’s premium banking tier for members who receive at least $3,000 in monthly direct deposits. Those members unlock higher MyPay limits, automatic Instant Loan qualification, and additional benefits. The objective is to encourage members to consolidate more of their financial lives inside Chime.

    The strategy appears to be working. CFO Matt Newcomb said Chime added more members making at least $3,000 in monthly direct deposits than in any previous quarter, while late-stage paycheck conversions reached a record. The company subsequently raised its full-year member growth target.

    As AI makes underwriting models increasingly accessible, differentiation is likely to come less from the model itself and more from the quality of the data behind it – something a lot of financial leaders are now emphasizing. Chime’s advantage is that recurring paycheck data gives it a proprietary, real-time view of a member’s financial life that’s harder to replicate.

    For Block, AI becomes the company’s operating model

    Block announced widespread layoffs earlier this year, and much of the conversation centered on those workforce reductions. Six months later, CEO Jack Dorsey pointed investors somewhere else. “The biggest proof point is our shipping velocity,” he told analysts.

    Rather than treating AI primarily as a customer feature, Block is first using AI to rethink how the company builds software.

    …

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    How banks have stopped thinking in products and started thinking in customer journeys

    One of the largest U.S. consumer financial services companies, Synchrony, with more than $120 billion in assets, faced a problem that had little to do with the amount of customer data it had and everything to do with what it could do with it.

    The company had spent decades building relationships through private-label credit cards, co-branded cards, installment financing, healthcare financing, and savings products. Every application, purchase, and payment added another data point to a customer profile. Yet when customers arrived on Synchrony’s digital channels, much of that knowledge remained disconnected from the experience they were having.

    A prospective customer exploring healthcare financing wasn’t necessarily looking for another credit product. The challenge wasn’t understanding who Synchrony’s customers were. It was recognizing what they needed in that moment and translating years of customer data into an experience that reflected their immediate goals.

    Since 2020, Synchrony has worked with Dynamic Yield to tackle the problem. At the time, Dynamic Yield was an independent personalization and decisioning platform owned by McDonald’s that helped banks, merchants, and brands use customer data and behavioral signals to personalize digital journeys and optimize customer decisions.

    Mastercard acquired Dynamic Yield in 2022 after announcing the acquisition in late 2021. The company saw that the future of payments wasn’t just about processing transactions, but about helping institutions understand customer intent before a payment, delivering the right experience during it, and building a more relevant relationship long after the transaction is complete. Dynamic Yield gave Mastercard a way to advance that broader vision as industry priorities evolved.

    Together with Dynamic Yield, Synchrony began combining its customer data with real-time behavioral signals and continuous experimentation to tailor experiences around customer intent.

    Six years later, the tech matters less than the problem it was built to solve. As banks layer AI into their customer experiences, many are grappling with the same challenge Synchrony set out to solve: how to turn years of customer data into a deeper understanding of each customer’s context.

    …

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    Why banks can’t policy their way out of shadow AI

    Employees at financial institutions are using AI tools their employers never approved for tasks that touch sensitive customer data.  This unsanctioned use of AI, often called shadow AI, is not a toothless problem. In May 2026, an employee at Pennsylvania-based CB Financial Services, parent company of Community Bank, uploaded a file containing customer names, Social Security numbers, and dates of birth into an unauthorized AI application while preparing a presentation. The employee bypassed the bank’s approved AI tool for a personal account on a personal device.  The bank caught the exposure quickly enough to get the data deleted before it could be used to train the vendor’s model. Notably, the bank already offered a sanctioned AI tool. The employee simply chose not to use it.  The instinct inside most banks and credit unions is to treat this as a policy failure and respond with tighter restrictions, more monitoring, and firmer language in the acceptable-use policy. But that response gets the diagnosis wrong, according to Corey Gross, VP and Head of Data & AI at Q2 Holdings. “When employees bypass a sanctioned tool, they’re telling leadership teams that the approved option isn’t getting the job done.” In his view, the root cause sits upstream of governance entirely: institutions are buying AI tools without first understanding the workflows those tools are meant to support. Instead of writing stricter acceptable-use policies, Gross suggests the more useful question is why employees felt they needed to go around the tool they were given in the first place. “It’s rarely a governance or compliance issue,” he said.

    The distinction sounds subtle, but it points to a different set of priorities for any bank trying to scale AI responsibly. It suggests that starting with the design of the work itself is more critical than the framing of the rules that surround it.

    Workflow redesign has to come before the AI rollout

    …

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    Regions Bank chose a modern core. Here’s what that journey looks like.

    Paul Weiss has spent decades running large-scale technology transformations. He knows what the complexity curve looks like, how it stops growing arithmetically at a certain scale and starts growing geometrically. When he joined Regions Bank as Chief Transformation Officer and inherited a core modernization already underway with Temenos, he knew what he was walking into.

    What surprised him was the partnership.

    “Very rarely have I had a partner that was as transparent and willing to collaborate as Temenos has been,” Weiss said. “Everything they’ve committed to, they’ve delivered. They’ve delivered on time.”

    That kind of endorsement carries weight at this particular moment. Regions, with assets north of $155 billion, selected Temenos SaaS in 2023 to modernize its legacy systems for customer records and deposits, and is now roughly two years into an implementation that positions it to be one of the first large US banks to complete a move to a modern core.

    The decision to go SaaS was deliberate. “We want to be able to focus on our customers and apply the functionality of the platform, rather than spending our focus on operating the platform,” Weiss said. Continuous upgrades, outsourced resilience, and the ability to redirect engineering attention toward customer outcomes rather than infrastructure maintenance drove the choice.

    The goals were set before Weiss arrived. Regions is a customer-driven bank, and the legacy environment was working against that identity. Months-long product development cycles, extensive custom coding, friction at every point of the delivery chain. “The biggest thing we were looking for is end-to-end client responsiveness,” Weiss said, “with the flexibility that we can have with a new modern core.”

    What Weiss brought to an already strong team was an engineering background and a specific discipline around managing complexity at scale. A core replacement at a bank like Regions means hundreds of integration points, each carrying its own data, compliance, and risk considerations, all of which have to move in concert. “Once you reach a certain scale, the complexity starts to increase geometrically, not arithmetically,” he said. “Thinking very carefully about how to manage complexity within the cost and timeframe that you have is a learned skill over time.”

    The complexity is exactly what’s kept many banks on the sidelines. The appetite for multi-year, high-risk big bang replacements has largely evaporated, a change Temenos’s own executives are watching closely. “The large banks have now realized they can’t get on the AI train unless they really do modernize,” said Will Moroney, Temenos’s Chief Revenue Officer. The conversation has moved from wholesale replacement to progressive modernization, introducing new capabilities for deposits or lending while the legacy platform continues to run alongside, then migrating product by product.

    Weiss sees AI reshaping the economics of that journey in ways that weren’t available when Regions started. Had the tools existed at the outset, he estimates the project could have been completed with roughly 30% less time and cost, a significant reduction, and one he believes will lower the barrier for other institutions considering similar moves. The areas where AI would have made the biggest difference: data management, data migration, integration, and testing. “These are all areas where generative AI can play a very strong role,” he said.

    Regions has also been developing its own AI tools including Cash Flow IQ and Client IQ, but hasn’t fully deployed them yet. Governance, model validation, and the distance between demonstrated functionality and production readiness are all factors. “There’s a long way to go from demonstrated functionality to bringing it in house with model validation and everything else,” Weiss said. “It’s an exciting development and one that we’ll track through an appropriate governance process.”

    Temenos has been focused on embedding AI directly into the platform rather than layering it on top — building “less but better,” with a deliberate narrowing of focus to use cases with broad impact across the client base. The FCM AI Agent, already live at a Tier 1 bank for sanctions screening, started at 5% of traffic and has been gradually expanded as the institution built organizational confidence alongside technical confidence.

    Technical readiness first, organizational readiness alongside is a sequencing Weiss recognizes from the transformation playbook. The change management dimension of a core replacement is as demanding as the engineering dimension, and it extends well beyond the technology team. “One of the signatures of a core transformation is there’s a huge number of moving parts and pieces, none of which individually are particularly complex, but all those gears have to fit together in just the right way,” said a Temenos spokesperson.

    For Regions, the competitive logic is straightforward. Being among the first large US banks to complete a move to a modern core creates flexibility that legacy-bound competitors won’t have. “We have a customer-centric culture,” Weiss said, “and what we’re doing is empowering our bankers with technology to serve our clients.”

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    The market no longer takes earnings beats at face value

      Weekly 10-Q

      The weekly 10-Q newsletter is part of the Tearsheet Pro subscription, where I unpack the recent moves and strategies of leading banks and fintechs in the public space, coupled with stock market analysis. In your inbox every Friday!

      Message Sara

      The market no longer takes earnings beats at face value

      The quarter of “lower-quality growth”: Why good quarters aren’t good enough anymore

      What kind of growth is this? The question surfaced repeatedly across this week’s second-quarter 2026 earnings. Companies including SoFi and Robinhood reported solid headline results. But investors looked past the beats and spent more time evaluating the businesses generating them than the numbers themselves. 

      Even stronger guidance failed to excite investors. Investors are more keen to know if growth is broad-based or concentrated, recurring or transactional, and whether those same growth engines will still be delivering a year from now.

      Growth is becoming more about composition

      SoFi’s second quarter 2026 earnings looked like the kind of report that would typically send a stock higher. The company posted record adjusted net revenue of $1.2 billion, up 40% year over year, while adjusted EPS beat expectations. It added 1.1 million new members, bringing its total to 15.8 million, raised its full-year revenue guidance, and continued expanding across lending, financial services, and its technology platform. By almost every traditional measure, it was a strong quarter.

      CEO Anthony Noto struck a confident tone, pointing to the breadth of SoFi’s business as evidence that the firm’s long-running diversification strategy is beginning to pay off. He said the company’s broader business mix gives it the ability to sustain growth, adding that what excites him most is “the velocity of our growth.”

      Yet investors weren’t entirely convinced. The stock fell after earnings and the debate quickly shifted to what was driving those results. Analysts focused on questions the earnings beat didn’t immediately answer. 

      • Why did management raise its full-year revenue outlook but leave its profitability outlook unchanged?

      • How quickly can the Technology Platform business recover after losing a major client?

      • Is SoFi relying too heavily on balance-sheet growth rather than accelerating its higher-margin, fee-based businesses?

      Those questions produced different conclusions.

      …

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      The Week in Market Moves | July 23-30, 2026

      Company signals and market response

      This analysis tracks the top company developments and how markets absorbed them through Thursday’s close, focusing on where shifting narratives translate into price action.

      It is part of Tearsheet PRO’s weekly 10-Q Newsletter, where strategy meets market reaction. I track how leading banks and fintechs are evolving in public markets and how investors are pricing those moves.

      Subscribe to PRO and get the full 10-Q story in your inbox every Friday!

      1. Upstart (UPST) – Close: $26.51

      • Upstart received conditional approval from the OCC to establish Upstart Bank, N.A., marking a major step toward becoming a nationally chartered bank.
      • FDIC deposit insurance and Federal Reserve approval to become a bank holding company are still pending before the bank can launch.

      Why it matters: For years, Upstart has positioned itself as the AI layer powering banks. A banking charter shifts that role. Rather than solely supplying underwriting technology, the company would gain greater control over funding, lending economics, and nationwide product distribution. It also reflects a broader shift in fintech: some firms are deciding that partnering with banks is no longer enough – they want to become one themselves.

      2. Visa (V) – Close: $364.11

      • Visa is cutting 2,600 roles (around 7% of its workforce), primarily across technology and product teams, to redirect investment toward higher-growth businesses.
      • The company plans to reinvest in stablecoins, cross-border money movement, B2B payments and value-added services, while AI increasingly automates routine work.

      Why it matters: Visa is reallocating resources toward where it believes the next decade of payments growth will come from. Stablecoins, commercial payments and AI are becoming core strategic priorities. The layoffs also signal that AI is beginning to reshape not just products, but how large financial institutions organize their workforce and allocate capital.

      3. Citi (C) – Close: $131.42

      • Citi partnered with Infor to launch Citi Consolidate, a platform that digitizes invoice approvals, purchase orders and accounts payable workflows.
      • The solution aims to reduce manual reconciliation, speed invoice approvals and improve access to working capital for buyers and suppliers.

      Why it matters: Payments have become faster. The workflows surrounding them often haven’t. As supply chains become more fragmented and global trade grows more complex, banks are finding that the bigger opportunity lies in orchestrating financial operations rather than simply processing transactions. Citi is betting that managing invoice data, approvals, and working capital will become as valuable as moving the money itself.

      4. SoFi (SOFI) – Close: $16.02

      • Existing members generated 51% of all new products during the quarter, up from 35% a year earlier, highlighting the growing role of cross-selling across SoFi’s ecosystem.
      • The company is embedding AI more deeply into its platform, with SoFi Coach evolving from providing financial guidance to eventually taking actions such as subscription management and cancellations.

      Why it matters: SoFi is shifting its focus from acquiring customers to increasing the value of each relationship. Every additional product deepens engagement while lowering customer acquisition costs across lending, banking, investing, and wealth. AI is becoming an enabler of that strategy by eventually taking actions on customers’ behalf, making the ecosystem more integrated and harder to leave.

      5. Robinhood (HOOD) – Close: $87.34

      • Robinhood reported record revenue of $1.3 billion while continuing to expand across banking, credit cards, retirement accounts, Gold memberships and prediction markets.
      • CEO Vlad Tenev said the company’s next challenge is “the orchestration of all of these things into one story,” as it connects its expanding portfolio into a unified financial platform.

      Why it matters: Robinhood is evolving beyond a brokerage into a broader financial platform. Banking, payments, investing, and credit are increasingly designed to reinforce one another rather than operate as standalone products. The real differentiator will be whether the firm can smoothly connect them into a single customer experience that captures a larger share of users’ financial lives.

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      The Week in Market Moves | July 16-23, 2026

      Company signals and market response

      This analysis tracks the top company developments and how markets absorbed them through Thursday’s close, focusing on where shifting narratives translate into price action.

      It is part of Tearsheet PRO’s weekly 10-Q Newsletter, where strategy meets market reaction. I track how leading banks and fintechs are evolving in public markets and how investors are pricing those moves.

      Subscribe to PRO and get the full 10-Q story every Friday!

      1. Intuit (INTU) – Close: $281.53

      • Intuit introduced a World Elite Business Mastercard that is deeply integrated into QuickBooks, combining spending, credit, and accounting in one workflow.
      • The company is positioning the card as another capital product in its growing financial services ecosystem, rather than a standalone payments offering.

      Why it matters: The move is about turning QuickBooks into the financial operating system for small businesses. By embedding credit directly into accounting workflows, Intuit gains continuous visibility into how businesses earn, spend and borrow. That creates richer data, stronger customer lock-in, and opens the door for increasingly personalised lending and financial recommendations over time.

      2. Nubank (NU) – Close: $14.19

      • Nubank is acquiring Banco Porto Real de Investimentos to obtain a full banking licence in Brazil, pending regulatory approval.
      • The move comes as Brazil tightens rules around the use of the word “bank” while Nubank continues expanding its banking footprint across Latin America.

      Why it matters: On the surface, this looks like a regulatory compliance exercise. In reality, it’s another step in Nubank’s evolution from fintech disruptor to full-scale banking institution. As digital banks mature, the competitive advantage is shifting from avoiding banking licences to embracing them, unlocking broader product capabilities, deeper customer relationships and greater regulatory legitimacy without sacrificing the digital experience that fuelled their growth.

      3. Block (XYZ) – Close: $76.49

      • Block unveiled Buzz, an open-source collaboration platform where AI agents receive their own identities, permissions and workspaces alongside human employees.
      • The platform is model-agnostic, supports multiple AI providers and records every action an AI agent takes under its own identity.

      Why it matters: Block is designing for a world where AI becomes part of the workforce itself. Giving agents identities, permissions and accountability signals that enterprise software is beginning to evolve around human-AI collaboration rather than human-only collaboration. The bigger question is no longer how employees use AI, but how organisations manage, govern and supervise an entirely new class of digital workers.

      4. Capital One (COF) – Close: $199.96

      • Capital One released VulnHunter, an open-source AI security tool that proactively searches source code for vulnerabilities.
      • The system includes a “falsification engine” that attempts to disprove its own findings before surfacing security risks to developers.

      Why it matters: As AI makes cyberattacks faster and cheaper to execute, security can no longer depend on humans reviewing every alert. Capital One is building AI that questions its own conclusions before developers ever see them. In an era where AI-generated false positives can overwhelm security teams, competitive advantage increasingly comes from judgement, not just detection. The companies that build AI capable of filtering, challenging, and validating its own reasoning will likely produce more trusted security systems than those simply generating more alerts.

      5. WISE (WSE) – Close: $12.08

      • Wise plans to reapply for a US national trust bank charter after the OCC rejected its initial application over AML and compliance shortcomings.
      • The company argues that regulatory developments, including the GENIUS Act and evolving payments infrastructure, strengthen the case for its revised application.

      Why it matters: The story is that obtaining a banking charter has become increasingly strategic for infrastructure providers. As payments become more programmable and stablecoins move closer to regulated financial systems, companies want direct access to payment rails instead of relying on banking partners. But Wise’s experience is also a reminder that no amount of technology or product innovation substitutes for strong compliance. The future of financial infrastructure will be shaped as much by regulatory credibility as technical capability.

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      Everyone’s using AI. So where does the advantage come from?

        Weekly 10-Q

        The weekly 10-Q newsletter is part of the Tearsheet Pro subscription, where I unpack the recent moves and strategies of leading banks and fintechs in the public space, coupled with stock market analysis. In your inbox every Friday!

        Message Sara

        Everyone’s using AI. So where does the advantage come from?

        Why every AI strategy is becoming a data strategy.

        Two years ago, the AI race was about models. Now large language models (LLMs) are increasingly capable and widely accessible. The performance gap between them continues to narrow. As that happens, financial firms are realizing that the harder challenge now is actually giving those models something meaningful to reason over.

        Across recent conversations with executives from Intuit Credit Karma, J.P. Morgan Payments, Deloitte, and others, it’s becoming clear that AI is only as valuable as the data, context, and systems surrounding it.

        Derek White, former CEO of Galileo Financial Technologies, distills that thinking into a key takeaway: “AI applications are only as good as the data that goes into them, and the human oversight and strategy used to guide and deploy them.”

        Data is THE product

        AI is taking different forms across the financial services landscape.

        Credit Karma is using AI-powered assistants to recommend what consumers should do with their debt, tax refunds, and paychecks. J.P. Morgan Payments is preparing for AI agents capable of shopping and transacting autonomously. Smaller banks are experimenting with Gen AI to improve fraud detection and customer service.

        …

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        The Week in Market Moves | July 30-Aug 06, 2026

        Company signals and market response

        This analysis tracks the top company developments and how markets absorbed them through Thursday’s close, focusing on where shifting narratives translate into price action.

        It is part of Tearsheet PRO’s weekly 10-Q Newsletter, where strategy meets market reaction. I track how leading banks and fintechs are evolving in public markets and how investors are pricing those moves.

        Subscribe to PRO and get the full 10-Q story in your inbox every Friday!

        1. Mastercard (MA) – Close: $575.95

        • Mastercard completed its $1.8 billion acquisition of stablecoin infrastructure provider BVNK, adding on-chain payment and stablecoin capabilities to its global network.
        • The combination is aimed at cross-border B2B payments, remittances, payouts, settlement and treasury flows across fiat and digital currencies.

        Why it matters: Mastercard is betting on becoming the connective tissue between different forms of money. BVNK gives it infrastructure for moving between fiat and on-chain value, while Mastercard brings distribution, institutional relationships and trust. The bigger play is interoperability: as stablecoins, tokenized deposits and traditional money co-exist, Mastercard wants its network to remain relevant regardless of which rail carries the transaction.

        2. Wells Fargo (WFC) – Close: $87.59

        • Wells Fargo plans to launch tokenized deposits for corporate and commercial clients this fall, initially supporting U.S. dollars and British pounds.
        • The deposits will allow clients to transfer, program, and settle funds around the clock, with integration planned for both private networks and a broader bank-led tokenized deposit network.

        Why it matters: The interesting part is where Wells Fargo is placing the technology in the financial stack. Tokenized deposits could give corporate treasurers programmable, 24/7 movement of money while keeping funds within the banking system. Starting with cross-border payments also points to one of the clearest use cases for tokenized money: making settlement faster without forcing businesses to move entirely outside traditional banking infrastructure.

        3. Chime (CHYM) – Close: $31.25

        • Chime’s Instant Loan originations jumped nearly 70% sequentially to $300 million, while MyPay generated $4.5 billion in quarterly originations.
        • Chime raised its 2026 member-growth target to 1.8 million after record direct-deposit conversions, with Chime Prime encouraging members to route more of their paychecks through the platform.

        Why it matters: Chime is increasingly treating the paycheck as more than an engagement metric. Recurring direct deposits give it a continuous view of income and cash flow while creating a natural mechanism for repayment. That creates a feedback loop: more paycheck data can support better underwriting, which supports more lending, which gives Chime another reason for members to make the platform their primary financial account.

        4. J.P. Morgan Chase (JPM) – Close: $356.30

        • J.P. Morgan CEO Jamie Dimon is recruiting more than 40 companies across banking, technology and critical infrastructure for an AI threat-prevention effort.
        • The initiative would expand the work of the Alliance for Critical Infrastructure as frontier AI makes cyberattacks faster, more scalable and potentially harder to defend against.
        • On the payments side: Merchants using J.P. Morgan Payments’ U.S. Commerce Platform can now offer Klarna’s pay-in-full, interest-free installments and longer-term financing without a separate integration.
        • The move removes a technical barrier to offering flexible payments as demand for installment options grows.

        Why it matters: Dimon’s move is a recognition that AI security is becoming a collective infrastructure problem, not something individual companies can solve inside their own walls. Banks, utilities, telecoms, transportation companies and other critical systems share many of the same vulnerabilities. Dimon’s push suggests the next phase of AI adoption may require companies to build defenses collectively, especially as attackers gain access to the same increasingly capable models as defenders.

        On the payments side, the strategic value there is less about adding another BNPL option and more about distribution. By putting Klarna directly into J.P. Morgan Payments’ Commerce Platform, the bank makes flexible payments easier for merchants to activate at scale. It also shows how payments infrastructure is increasingly becoming a distribution layer: the winning product is the one that gets embedded where merchants already operate.

        5. Block (XYZ) – Close: $79.02

        • Block says code changes per engineer have increased 150% since the start of 2026, while Square shipped 130 features in the first half of the year – more than three times the prior-year pace.
        • Product development expenses fell 17% year over year following February’s restructuring, while adjusted operating income reached a record $864 million in Q2 2026.

        Why it matters: Block’s AI bet is unusually direct: use AI to change how the company itself operates before worrying about how many AI features it can sell. Buzz, its platform for employees and AI agents to collaborate on software development and other work, is becoming a test case for whether smaller teams can actually produce more. The results are beginning to give investors something more concrete than an AI narrative: faster product output alongside lower development costs.