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Paper still defines payments’ last mile. J.P. Morgan Payments thinks AI and robotics can tackle that.

The dominant narrative in payments is real-time payments, stablecoins, instant payment rails, always-on cash flow, and near-seamless cross-border movement. But speed at the point of settlement doesn’t solve what happens before and after money moves.

One of the world’s largest payments businesses processed more than 130 million checks in 2025. Behind every check was a chain of envelopes, remittance slips, invoices, inconsistent formats, and manual reconciliation.

That’s the gap J.P. Morgan Payments is targeting with its multi-year effort, using AI, robotics, computer vision, and large language models to digitize and automate its lockbox operations. The project is about modernizing one of the most manual information-processing systems still embedded inside corporate payments.

“Checks are still a meaningful part of the U.S. payments landscape,” says Michelle Conklin, Head of Receivables and Public Sector at J.P. Morgan Payments. “The challenge is often not the check payment itself, but all of the manual work that comes with it: opening mail, extracting checks and remittance documents, capturing data, validating information, and handling exceptions.”

Michelle Conklin, Head of Receivables and Public Sector at J.P. Morgan Payments

“That is where we see a real opportunity to drive value,” she notes. “When we automate those steps with AI and robotics, we can scale more easily and make the process faster and more accurate. This is a reminder that innovation in payments is not only about faster settlement. It is also about removing friction from the end-to-end process, such as what we’re advancing in the lockbox space.”

When AI finally became good enough for the messy middle

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What Fifth Third’s invitation to Project Glasswing says about the bank’s role in the financial system

Banking scale has been measured in assets, deposits, and branches. In 2026, another metric may be emerging: how much of the country’s financial activity would be disrupted if your systems stopped working.

That helps explain why Fifth Third’s recent invitation to Anthropic’s Project Glasswing holds importance. The bank has been invited into an invite-only cybersecurity program that grants a small group of vetted partners early access to the Claude Mythos Preview model.

Project Glasswing is a controlled-access initiative, bringing together a limited set of trusted organizations to test advanced AI systems in real-world security environments. The focus is on detecting and helping remediate critical software vulnerabilities at scale. Anthropic has said its Mythos models have already identified more than 10,000 vulnerabilities in widely used, systemically important software, and Glasswing extends that capability to selected partners before wider deployment.

That signals the direction Fifth Third is moving in. The same week, it rolled out a refreshed small-business platform to over 240,000 customers.

From banking customers to orchestrating flows

Fifth Third’s new small-business offering is a digital banking upgrade built around speed and access – Early Pay brings forward incoming funds, digital lending speeds up capital access, Zelle shortens payment cycles, and tap-to-pay streamlines merchant acceptance. The unifying theme is flow.

After its merger with Comerica, Fifth Third now ranks as the 9th-largest U.S. bank with about $294 billion in assets, strengthening its footprint across several fast-growing commercial markets.

Scale matters, but operational density matters more. The more businesses, payrolls, government programs, and payment streams flowing through a bank, the more consequential its systems become.

Why Anthropic cares

Bryan Preston, Fifth Third’s Chief Financial Officer, attributed the bank’s inclusion in Project Glasswing to its role in administering Direct Express, processing payments for U.S. Customs, and handling large volumes of payroll activity across the country. 

These are not ordinary banking products. They are payment flows tied to government programs, public-sector operations, and employer payroll systems that millions of people depend on.

Basically, Fifth Third was selected because disruptions to its systems could ripple far beyond the bank itself.

The emerging hierarchy of banks

Size used to define banks – now their function does. The key distinction is between customer-facing banks and those that operate financial infrastructure.

Fifth Third’s recent announcements suggest it is moving toward the latter category.

The broader shift is that regional banks are increasingly being discussed alongside infrastructure providers, payment operators, government disbursement systems, and national cybersecurity efforts. Increasingly, a bank’s importance may be measured by systemic dependence on how critical an institution is to keeping the financial system smoothly functioning.

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The 3-Min Read: Why Anthropic is becoming AI’s reference point

In the span of just twelve months, Anthropic has shifted from being one of several frontier AI labs to a gravitational center of the industry. The change is driven by a compounding sequence of capital inflows, enterprise adoption, and infrastructure-scale positioning that increasingly resembles platform formation rather than startup growth.

The clearest signal came on May 28, 2026, when the company closed a $65 billion Series H round at a $965 billion post-money valuation, briefly making it the world’s most valuable AI startup ahead of OpenAI. Its valuation has climbed rapidly from $183 billion in Series F to $380 billion in Series G, and nearly doubled again in the latest round.

This momentum is being driven by strong enterprise demand. Anthropic now reports an annualized revenue run-rate above $47 billion, largely fueled by adoption of its Claude models in coding and agent-based workflows. Increasingly, Claude is being embedded into production systems where productivity gains translate directly into cost reduction.

Coding has become the primary growth engine, marking the second signal. Software development is now the operating layer of modern enterprises. As Claude moves deeper into these workflows, Anthropic’s identity shifts from product builder to infrastructure provider.

But rapid growth comes with pressure. The company is close to its first operating profit, yet compute costs remain heavy. In Q1 2026, it spent 71 cents for every dollar of revenue on compute, expected to improve to 56 cents in the next quarter. Efficiency is improving, but only because demand is rising fast enough to absorb training and inference costs. Yet Anthropic has also cautioned that planned infrastructure investments could make profitability difficult to sustain over the full year. This tension between scaling demand and managing compute costs is now a pressing challenge for frontier AI companies. Bankers and investors are increasingly focused on Anthropic’s token economics and compute costs, worried that rising AI usage costs could pressure margins and make it harder to justify its valuation after an IPO.

Which leads to the third signal: capital structure alignment. On June 1, Anthropic confidentially filed for an IPO, working with Morgan Stanley and Goldman Sachs, alongside J.P. Morgan Chase. Anthropic leadership notes that frontier model training requires sustained access to large-scale capital, and public markets are structurally better suited to that need. 

Alongside expansion, Anthropic is also moving carefully on safety and control. Through Project Glasswing, the company has scaled access to its Mythos cybersecurity model from roughly 50 organizations to 150 across more than 15 countries. The system has already helped identify more than 10,000 high- or critical-severity vulnerabilities in widely used software.

The same capabilities used to detect vulnerabilities could also be used to exploit them, so the model distribution is limited to vetted partners. Expansion happens through controlled channels rather than open release.

Anthropic is also exploring broader deployment of the model through discussions with the EU cybersecurity agency ENISA, which could extend access beyond the US and UK for the first time – widening its user base through institutional gatekeepers.

What Anthropic is becoming

These shifts show Anthropic evolving into three roles:

  1. A capital-scale company moving toward public-market size with trillion-dollar ambitions.
  2. An embedded intelligence layer inside enterprise systems, especially in software development.
  3. A controlled provider of high-risk AI systems, distributed through strict governance frameworks.

Anthropic is trying to scale and contain at the same time. The broader question is whether the economic and governance structures around frontier AI can scale at the same pace as the systems they are now trying to contain.

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What Citi Sky says about the reinvention of client relationship models in wealth management

Wealth management follows a familiar rhythm where advisors book meetings in advance, send market notes after the fact, and make decisions that move at the speed of inboxes and calendars.

Citi Wealth is aiming to break that cadence with Citi Sky, built in partnership with Google Cloud and Google DeepMind. The bank describes it as an always-on AI-powered member of the Citi Wealth team that can talk, respond, and surface insights in real time.

Citi’s Head of Wealth, Andy Sieg, says the intent is to move away from the fragmented experience clients have lived with for years. “For decades, managing your financial life meant navigating apps, calls, and meetings,” he said in a press release. “With Citi Sky, you simply ask – and act. This is the shift from interface to intelligence, from transactions to outcomes.”

The Citi-Google Cloud relationship extends beyond a typical vendor arrangement. While Google provides the underlying infrastructure and AI stack, the collaboration evolved into a deeper co-development effort. Teams from Google Cloud and Google DeepMind worked alongside Citi engineers to shape Citi Sky’s architecture, conversational experience, and guardrails, while Citi retains ownership of the client experience, data, and decisioning layer.

From infrastructure modernization to client-facing intelligence

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