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Goldman Sachs launches AI assistant as the tech sweeps banking

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Goldman Sachs GS AI Assistant

Courtesy: Goldman Sachs

Goldman Sachs is rolling out a generative AI assistant to its bankers, traders and asset managers, the first stage in the evolution of a program that will eventually take on the traits of a seasoned Goldman employee, according to Chief Information Officer Marco Argenti.

The bank has released a program called GS AI assistant to about 10,000 employees so far, with the goal that all the company’s knowledge workers will have it this year, Argenti told CNBC in an exclusive interview. It will initially help with tasks including summarizing or proofreading emails or translating code from one language to another.

“Think about all the tasks that you might want to complete with regards to a variety of use cases for all those professions that can be now at your fingertips,” Argenti said. The Goldman assistant is a “very simple interface that allows you to have access to the latest and greatest models.”

Goldman’s move means that, along with JPMorgan Chase and Morgan Stanley, the world’s top three investment banks have aggressively released generative AI tools to their workforce, a remarkable development since ChatGPT went viral about two years ago.

Wall Street has embraced generative artificial intelligence faster than any other disruptive technology in recent years, experts say, because of how adept large language models are in replicating aspects of human cognition.

Today it can respond to queries, write emails and summarize lengthy documents, but expectations are high that future versions will exhibit so-called “agentic” abilities, meaning they can perform multi-step tasks with little human intervention.

In speaking with CNBC about his vision for artificial intelligence at the firm, Argenti — who joined from Amazon in 2019 — repeatedly likened the AI program to a new employee that will absorb Goldman culture over the coming years.

Initially, the tool will mostly produce answers based on Goldman data that has been fed into AI models from OpenAI’s ChatGPT, Google’s Gemini and Meta’s Llama, depending on the task, said Argenti. The bank is also looking at models from companies including Anthropic, Mistral and Cohere, he added.

“The AI assistant becomes really like talking to another GS employee,” Argenti said.

Learning the Goldman Way

“As we progress, the second step is when you’re starting to have this agentic behavior, that is, ‘I’m completing a task on behalf of a Goldman employee, and I need to take a set of steps’,” he said. “That’s where the model is going to start to do things like a Goldman employee, not only say things like a Goldman employee.”

This helps explain why companies have forbid employees from using ChatGPT for work, instead moving to create their own platforms to tap the technology. It allows firms to not only keep their information secure, but to also craft AI platforms that increasingly resemble the best examples of their own workforce.

“For the AI to have a very specific identity that reflects the tenets, the values, the knowledge and the way of thinking of the firm is extremely important,” Argenti said.

In practice, that means that just as an experienced Goldman employee would know to double check their work with multiple data sources or use a specific algorithm for a calculation, the AI will absorb those lessons, he said.

Marco Argenti, chief information officer for Goldman Sachs, joined the bank from Amazon in 2019.

Courtesy: Goldman Sachs

But Argenti says he is most excited by the prospect of what comes later, in perhaps three to five years, as AI models increasingly blur the lines between human and machine thinking.

This stage of AI at Goldman would have the model “actually reason more and become more like the way a Goldman employee would think,” he said.

So instead of being handed a run book, which is tech industry parlance for a set of step-by-step instructions for completing tasks or responding to incidents, the AI would be able to generate detailed plans “in the way that an experienced Goldman employee would do,” Argenti said.

Disruption risk

The prospects of that future — and the fact that Wall Street’s workers are helping train a technology that may make some roles obsolete, while augmenting other jobs and creating new roles altogether — may send a fresh wave of anxiety through employee ranks.

Like at Goldman, other major investment banks are on target to give generative AI tools to their entire workforces in the coming months.

More than 200,000 JPMorgan employees currently have access to in-house generative AI tools, according to a person with knowledge of that bank who declined to be identified speaking about internal matters. Roughly 40,000 Morgan Stanley employees had access to it as of late last year, the bank said in October.

Finance and technology are seen as among the industries where employees are most prone to upheaval because of generative AI, allowing companies to potentially generate billions of dollars in additional profits. Meta CEO Mark Zuckerberg told podcaster Joe Rogan earlier this month that its AI will be capable of writing code as well as mid-level software engineers this year.

Global investment banks may shed as many as 200,000 jobs in the next three to five years as the companies implement AI, according to a report from Bloomberg’s research arm. The report, based on a survey of tech executives at major banks, said that support and operations roles known as the back and middle office were most at risk.

At Goldman, however, the official stance is that AI will empower employees to do more, not necessarily result in the need for fewer humans.

“The importance of having a phenomenal human workforce is actually going to be amplified,” Argenti said.

“In my opinion, it always boils down to people,” he said. “People are going to make a difference, because people are going to be the ones that actually evolve the AI, educate the AI, empower the AI, and then take action.”

Morgan Stanley expands OpenAI-powered chatbot tools to Wall Street division

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Treasury Bond Volatility Forces Bessent to Double Debt Buyback Size as Yields Swing

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Bessent

A turbulent week in the U.S. Treasury market prompted the Treasury Department to sharply increase the size of its long-term debt buyback program, as bond prices fell even while equity markets pushed toward record highs. The divergence has drawn attention from fixed-income strategists who see it as a signal of underlying investor unease about federal borrowing levels.

What Happened This Week

U.S. Treasury Secretary Scott Bessent told CNBC on Thursday, August 20, 2026, that the Treasury had doubled the size of its long-term debt buyback operations, moving from roughly $2 billion to at least $4 billion per operation. Bessent indicated the figure could climb further, saying “we’re going to increase the size of the buyback,” and noted the accelerated pace could exceed the announced $4 billion threshold per issue.

Buybacks allow the Treasury to repurchase outstanding government bonds directly from the market, which can help support prices and dampen yield volatility during periods of stress. The expanded program came as stocks staged a late-week recovery: the S&P 500 and Russell 2000 both advanced on Friday, August 21, even as Treasuries logged mild losses, according to Bloomberg market data.

Why Bond and Equity Markets Are Diverging

Capital.com senior market analyst Daniela Hathorn described the week’s dynamic as markets “ending the week on a softer tone after the relative calm of early August was disrupted by renewed pressure in global bond markets, another rise in oil prices, and growing uncertainty around the Federal Reserve’s next move.” She noted that higher long-term borrowing costs are increasingly challenging elevated equity valuations, even as U.S. equities pull back modestly from record highs.

This divergence — equities near record levels while bonds sell off  is unusual and reflects two different sets of investor concerns. Equity investors have remained focused on corporate earnings strength, particularly from large technology companies ahead of Nvidia’s closely watched August 26 earnings report. Bond investors, by contrast, are more directly exposed to concerns about the scale of federal borrowing, highlighted this week by the national debt crossing the $40 trillion threshold for the first time.

The Fed and Treasury “Working in Opposite Directions”

Wilmington Trust senior bond portfolio manager Wil Stith told Yahoo Finance that current conditions reflect “the Fed and the Treasury basically working in sort of opposite directions,” adding that the imbalance will likely require the Federal Reserve  which he described as having “the larger sandbox”  to adjust the federal funds rate rather than relying on Treasury market interventions alone to manage yields.

Notably, the bond market’s reaction to the Treasury’s buyback expansion was relatively muted; strategists described the move as being largely absorbed without a major rally, suggesting the underlying pressure on yields stems from factors, such as inflation persistence and debt sustainability concerns, that a buyback program alone cannot resolve.

What Comes Next

Markets are now looking to two major events in the days ahead: Nvidia’s earnings report on Wednesday, August 26, and the Federal Reserve’s Jackson Hole Economic Symposium, running August 27-29. This will be the first Jackson Hole gathering under new Fed Chair Kevin Warsh, whose public communication style and policy signals remain less established than his predecessors’, according to market commentary from Regards of Wall Street.

For investors, the key metrics to watch are the size and frequency of future Treasury buyback operations, movements in the 10-year Treasury yield, and any policy signals from Warsh’s keynote address. Continued yield volatility alongside record equity valuations would suggest the market imbalance identified this week has not yet been resolved.

 

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Cross-Border Settlement Innovation and Real-Time Payment Architecture

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The global banking system is undergoing a comprehensive modernization of cross-border payment infrastructure. Driven by real-time settlement networks, open banking APIs, and interoperable messaging standards, financial institutions and multinational corporations are eliminating multi-day delays and reducing transaction costs associated with legacy international wire transfers.

Transition to Real-Time Gross Settlement Networks
Historically, international business-to-business (B2B) payments relied on complex correspondent banking relationships involving intermediary fees and processing delays. In 2026, the widespread adoption of ISO 20022 messaging protocols alongside interconnected Real-Time Gross Settlement (RTGS) systems allows direct, end-to-end processing of cross-border transfers.

Commercial banks are providing corporate clients with continuous, 24/7 payment clearing capabilities. Real-time transaction confirmation and automated FX rate locking allow international businesses to settle cross-border trade obligations within minutes, significantly reducing counterparty risk.

Central Bank Digital Currency (CBDC) Interoperability
Wholesale Central Bank Digital Currency (CBDC) pilot initiatives are reaching operational maturity across several key financial centers. Collaborative multi-CBDC platforms enable participating central banks and commercial institutions to settle foreign exchange and international trade transactions directly on shared distributed ledgers.

These wholesale digital currency networks eliminate traditional clearinghouse delays and minimize foreign exchange slippage. Enterprise treasury departments benefit from enhanced liquidity management, as cross-border cash balances can be deployed and repatriated instantaneously.

Corporate Treasury Transformation
For enterprise treasurers, instant cross-border settlement transforms cash management strategies:
– Working Capital Optimization: Reduced transaction float allows companies to lower precautionary cash reserves and optimize short-term liquidity investments.
– Automated Reconciliation: Enriched data formats embedded in ISO 20022 payment messages streamline automated general ledger posting and invoice matching.
– Reduced Processing Overhead: Account-to-account (A2A) real-time clearing bypasses costly intermediary correspondent banking fees.

Strategic Financial Priorities
1. Upgrade Treasury Systems: Ensure internal core enterprise software supports real-time ISO 20022 payment messaging standards.
2. Leverage Instant Clearing Rails: Utilize direct payment networks to lower cross-border transaction fees and eliminate settlement delays.
3. Evaluate Multi-Currency Liquidity: Modernize liquidity management frameworks to capitalize on 24/7 real-time settlement capabilities.

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Private Credit Expansion and Regulatory Oversight in 2026 Capital Markets

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The global private credit market has solidified its role as a fundamental pillar of enterprise finance, expanding rapidly across middle-market lending, asset-backed finance, and infrastructure financing. As non-bank financial institutions capture a larger share of corporate debt origination, global regulatory bodies are increasing oversight to evaluate market transparency and systemic risk interconnections.

Growth Drivers in Direct Lending
Direct lending platforms have continued to attract substantial institutional allocations from pension funds, sovereign wealth entities, and insurance companies seeking attractive risk-adjusted yields. Private debt funds offer corporate borrowers customized financing structures, faster execution timelines, and confidentiality compared to syndicated loan markets.

In 2026, private credit managers are increasingly financing larger corporate transactions, providing multi-billion-dollar credit facilities for buyout deals and corporate restructurings. The flexibility of private debt contracts—featuring unitranche pricing and tailored covenant packages—has made direct lending the preferred capital source for middle-market enterprise sponsors.

Regulatory Scrutiny and Systemic Risk Assessment
The rapid growth of non-bank intermediation has drawn heightened scrutiny from financial regulators in North America and Europe. Because private debt agreements are negotiated privately without public exchange disclosures, central banks are evaluating potential vulnerabilities related to asset valuation consistency and fund liquidity profiles.

Regulatory agencies are introducing guidelines aimed at improving reporting standards for private investment vehicles managing institutional assets. Key focus areas include monitoring leverage ratios within private credit funds and evaluating indirect credit exposures between commercial banking institutions and private debt funds.

Navigating Elevated Refinancing Costs
With benchmark interest rates remaining elevated, private debt borrowers face higher debt service obligations on floating-rate credit facilities. Financial advisory firms report an increase in proactive liability management strategies, including payment-in-kind (PIK) interest options, equity infusions from sponsors, and covenant modifications.

Private credit managers with deep operational capabilities are actively working alongside portfolio companies to optimize working capital and maintain cash flow coverage ratios during periods of higher borrowing costs.

Key Financial Takeaways
1. Mainstream Asset Class: Private credit has expanded beyond niche alternative asset status into a core corporate finance solution.
2. Enhanced Transparency Standards: Regulatory frameworks are evolving toward greater disclosure requirements for private debt managers.
3. Proactive Risk Management: Lenders and sponsors must prioritize debt sustainability and active portfolio monitoring amid high benchmark rates.

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