Connect with us

Finance

JPMorgan Chase blueprint to become first fully AI-powered megabank

Published

on

JPMorgan launches AI tools: Here's what to know

Deep within the bowels of JPMorgan Chase’s data centers and cloud providers, an artificial intelligence program crucial to the bank’s aspirations grows more powerful by the week.

The program, called LLM Suite, is a portal created by the bank to harness large language models from the world’s leading AI startups. It currently uses models from OpenAI and Anthropic.

Every eight weeks, LLM Suite is updated as the bank feeds it more from the vast databases and software applications of its major businesses, giving the platform more abilities, Derek Waldron, JPMorgan chief data analytics officer, told CNBC in an exclusive interview.

“The broad vision that we’re working towards is one where the JPMorgan Chase of the future is going to be a fully AI-connected enterprise,” Waldron said.

JPMorgan, the world’s largest bank by market capitalization, is being “fundamentally rewired” for the coming AI era, according to Waldron. The bank, a heavyweight across Main Street and Wall Street finance, wants to provide every employee with AI agents, automate every behind-the-scenes process and have every client experience curated with AI concierges.

If the effort succeeds, the project could have profound implications for the bank’s employees, customers and shareholders — even the nature of corporate labor itself.

Waldron, who gave CNBC the first demonstration of its AI platform seen by any outsider, showed the program creating an investment banking deck in about 30 seconds, work that would’ve previously taken a team of junior bankers hours to complete.

Out of the box

Since the arrival of OpenAI’s ChatGPT in late 2022, optimism over generative AI has driven markets higher on gains from the tech giants and chip makers closest to the trade. Underpinning their growth is the expectation that corporate clients deploying AI will either boost worker productivity or lower expenses through layoffs — or both.

But similar to how the internet story played out in the 1990s, near-term expectations for AI may have outstripped reality. Most corporations had no tangible returns yet on their AI projects despite more than $30 billion in collective investments, according to an MIT report from July.

Jamie Dimon, Chairman and Chief Executive Officer of JPMorgan Chase & Co. speaks during an event honoring local construction workers who helped build the firm’s new headquarters at 270 Park Avenue, in the Midtown area of New York City, U.S., Sept. 9, 2025.

Shannon Stapleton | Reuters

In the case of JPMorgan, even with it $18 billion annual tech budget, it will take years for the company to realize AI’s potential by stitching the cognitive power of AI models together with the bank’s proprietary data and software programs, said Waldron.

“There is a value gap between what the technology is capable of and the ability to fully capture that within an enterprise,” Waldron said.

Companies “do work in thousands of different applications, there’s a lot of work to connect those applications into an AI ecosystem and make them consumable,” he said.

If JPMorgan can beat other banks to the punch on incorporating AI, it will enjoy a period of higher margins before the rest of the industry catches up. That first-mover advantage will allow it to grow revenues faster by going after a larger slice of the addressable market in global finance — enabling the bank to pitch more middle-market companies in investment banking, for instance.

Change on the horizon

AI was a major topic at a four-day executive retreat held in July by JPMorgan CEO Jamie Dimon, according to a person who attended but declined to be identified speaking about the private event.

Among concerns discussed at the off-site meeting, held at a resort outside Nashville, was how AI-driven changes will be adopted by the bank’s 317,000-person workforce and its possible impacts to the apprenticeship model on areas including investment banking.

If JPMorgan succeeds with its AI goals, it will mean that a bank that is already the largest and most profitable in American history is set for new heights. Dimon has led the bank since 2005, guiding it through periods of upheaval to notch record profits in 7 of the last 10 years.

The end state for JPMorgan, as envisioned by Waldron, is a future in which AI is woven into the fabric of the company:

“Every employee will have their own personalized AI assistant; every process is powered by AI agents, and every client experience has an AI concierge,” he said.

JPMorgan laid the groundwork for this starting in 2023, when it gave employees access to OpenAI’s models through LLM Suite; it was essentially a corporate ChatGPT tool used to draft emails and summarize documents.

About 250,000 JPMorgan employees have access to the platform today, which is the entire workforce except for branch and call center staff, said Waldron. Half of them use it roughly every day, he said.

JPMorgan is now early in the next phase of its AI blueprint: It has begun deploying agentic AI to handle complex multistep tasks for employees, according to an internal roadmap provided by the bank.

“As those agents become increasingly powerful in terms of their AI capabilities and increasingly connected into JPMorgan,” Waldron said, “they can take on more and more responsibilities.”

Nvidia deck

Waldron, a former McKinsey partner with a Ph.D. in computational physics, recently demonstrated LLM Suite’s capabilities to CNBC.

He gave the program a prompt: “You are a technology banker at JPMorgan Chase preparing for a meeting with the CEO and CFO of Nvidia. Prepare a five-page presentation that includes the latest news, earnings and a peer comparison.”

LLM Suite created a credible-looking PowerPoint deck in about 30 seconds.

“You can imagine in the past how that would have been done; we would’ve had teams of investment banking analysts working long hours at night to do this,” said Waldron.

The bank is also training AI to draft other key investment banking documents including the “inch thick” confidential memos that JPMorgan produces for prospective M&A clients, said the person who attended the July executive meeting.

Derek Waldron, JPMorgan’s chief analytics officer.

Courtesy: JP Morgan

The prospect of collapsing work loads means that fewer junior bankers may be needed even while AI-enabled teams handle more work and pitch more companies, according to senior Wall Street executives at several firms who spoke on the condition of anonymity to provide their candid thoughts.

But to extract the full value from this new, almost magical technology, it’s not just about the tools: Changes to how employees and departments are organized may be needed.

One proposal being discussed at a major investment bank is reducing the ratio of junior bankers to senior managers from the current 6-1 to 4-1. In the new regime, half of those junior bankers would be working from cities with cheaper labor, say Bengaluru, India, and Buenos Aires, Argentina, instead of being clustered in expensive New York.

The AI-powered junior bankers could then work on deals in shifts around-the-clock, passing the baton from one time zone to the next.

With fewer bankers on the payroll, the cost structure of investment banking would fall, boosting the bottom line, said the executives.

Structural shifts

AI FOMO

Goldman Sachs tests agentic AI to automate software engineering

Continue Reading

Finance

Tokenized Debt Shifts How Corporate Manage Short Term Liquidity

Published

on

Tokenized Debt Shifts Corporate Liquidity

The landscape of institutional debt markets is undergoing a profound structural shift on July 21, 2026, as major corporate issuers and commercial banks rapidly accelerate the deployment of tokenized debt instruments. Data published by leading capital market consortiums indicates that primary issuances of digital commercial paper and tokenized corporate bonds have reached record volumes this month. By moving legacy debt origination, underwriting, and secondary distribution onto permissioned distributed ledgers, corporate treasurers are unlocking unprecedented operational flexibility and instantaneous cross-border liquidity.

The adoption of tokenized debt is fundamentally altering how enterprise balance sheets manage short-term liquidity needs. Traditional corporate bond settlement cycles historically required multi-day clearing processes involving numerous intermediaries, custodial entities, and clearinghouses. Through programmable smart contracts on distributed ledgers, issuers can now execute atomic settlement—enabling continuous, 24/7 access to institutional capital pools. This instantaneous clearing mechanism drastically reduces counterparty risk, eliminates costly settlement friction, and allows treasury teams to dynamically optimize working capital in real time.

A major catalyst driving this institutional migration is the establishment of comprehensive digital asset regulatory frameworks across major financial hubs. Clear legal guidelines regarding ledger-based securities ownership have provided institutional compliance officers with the regulatory confidence necessary to transition multi-billion-dollar liquidity facilities onto digital platforms. Furthermore, the integration of automated regulatory reporting directly into token smart contracts simplifies ongoing compliance audits, ensuring that secondary market trades automatically enforce investor accreditation limits and tax withholding requirements.

For chief financial officers and institutional portfolio managers, tokenized debt represents a fundamental evolution in fixed-income strategy. Companies that embrace ledger-based debt structures gain direct access to a broader, global base of digital-native institutional investors while substantially reducing borrowing overhead. As ledger interoperability continues to improve across global exchanges, tokenized debt is poised to become the standard infrastructure for global corporate finance.

Continue Reading

Finance

Private Credit Expansion: How Alternative Lending Platforms Are Reshaping Corporate Liquidity

Published

on

How Alternative Lending Platforms Are Reshaping Corporate Liquidity

Private credit has firmly established itself as a foundational pillar of global financial markets in 2026, transitioning from an alternative asset class into a dominant mechanism for middle-market corporate financing. Reports published in mid-July 2026 show that direct lending assets under management have expanded significantly, as corporate borrowers increasingly bypass traditional syndication desks in favor of customized private debt solutions. This structural migration has fundamentally altered corporate liquidity dynamics, providing middle-market enterprises with reliable access to tailored capital packages even during periods of regulatory bank tightening.

The primary driver of this continued growth is the structural flexibility inherent in private debt agreements. Unlike public bond markets or conservative commercial bank loans—which often carry rigid covenants and slow underwriting timelines—private credit funds offer speed of execution, flexible payment-in-kind structures, and customized debt-service frameworks. For companies undertaking strategic acquisitions, capital expenditures, or complex balance sheet recapitalizations, the ability to negotiate directly with a unified syndicate of private lenders provides significant certainty and confidentiality.

However, the expansion of private credit is attracting heightened regulatory attention and risk scrutiny. Financial regulatory bodies are closely evaluating the lack of secondary market price discovery and the potential concentration of illiquidity risks within non-bank financial institutions. Because private debt instruments are held to maturity and marked to model rather than marked to market, evaluating real-time enterprise valuations during economic shifts requires robust internal credit assessment standards. Analysts note that as loan portfolios mature, performance variations between disciplined lenders and aggressive underwriters will become increasingly apparent.

For corporate financial officers and institutional portfolio managers, private credit represents both a powerful strategic tool and a vital diversification strategy. Borrowers must weigh the higher nominal coupon rates of private debt against the tangible value of operational flexibility and execution certainty. Meanwhile, investors must maintain rigorous credit due diligence, prioritizing funds with proven restructuring capabilities and deep operational expertise in underwriting resilient middle-market businesses.

Continue Reading

Finance

Tokenized Real-World Assets: Institutional Ledger Adoption Achieves Scale in July 2026

Published

on

Institutional Ledger Adoption Achieves Scale in July 2026

The integration of blockchain technology with legacy financial markets has reached a decisive tipping point in July 2026, driven by the rapid scaling of Real-World Asset (RWA) tokenization. Major global investment banks, custodial entities, and asset managers are actively shifting sovereign debt, commercial paper, and private fund shares onto permissioned distributed ledgers. Recent industry data confirms that the aggregate market capitalization of tokenized treasury products and private credit funds has surged past major milestones, illustrating that ledger-based settlement is no longer experimental, but core financial infrastructure.

The fundamental value proposition of asset tokenization rests on operational efficiency, continuous liquidity, and automated compliance execution. By embedding regulatory checks, investor accreditation limits, and automated coupon distributions directly into smart contract code, financial institutions eliminate vast amounts of manual back-office reconciliation. Furthermore, fractionalized ownership structures allow high-value asset classes—such as prime commercial real estate and private equity funds—to be split into accessible units, significantly expanding liquidity pools and enabling real-time collateral optimization.

A key catalyst behind this institutional momentum is the establishment of comprehensive regulatory clarity across major financial jurisdictions. The implementation of standardized digital asset frameworks in the United States and Europe has provided institutional compliance officers with the legal certainty required to deploy capital on-chain. As a result, premier custodian banks are now offering unified digital asset custody, seamlessly bridging traditional securities depositories with programmable ledger ecosystems.

Looking forward, the maturation of tokenized assets will continue to transform secondary market trading and treasury management. Corporate treasurers can now yield-optimize idle cash in real time by moving into tokenized money market instruments that settle instantaneously on a 24/7 basis. To remain competitive, financial leaders must ensure their institutional architectures are interoperable with modern digital ledger protocols, positioning their organizations at the forefront of modern capital market efficiency.

Continue Reading

Trending