Connect with us

Finance

Goldman Sachs launches AI assistant as the tech sweeps banking

Published

on

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

Continue Reading

Finance

Treasury Yields Rise as Fed Cut Expectations Shift

Published

on

Treasury Yields Rise as Fed Cut Expectations Shift

Fixed-income markets recorded significant re-pricing during the week ending July 25, 2026, as a convergence of strong labor market metrics and surging energy costs drove U.S. Treasury yields higher across all maturities. The benchmark 10-year Treasury yield climbed toward 4.70%, reaching its highest point in several months. Institutional bond investors rapidly adjusted portfolio durations as expectations for near-term interest rate cuts by the Federal Reserve faded in response to inflation concerns.

The upward shift in sovereign yields reflects a broader fundamental reassessment of global monetary policy. Earlier in the quarter, money markets had priced in a series of rate reductions designed to support economic activity. However, with initial jobless claims falling to 187,000 and crude oil breaching $100 per barrel, fixed-income traders are pricing in a ‘higher-for-longer’ interest rate environment. The inversion between short-term Treasury bills and long-term bonds narrowed, indicating a shift toward term premium expansion.

Rising Treasury yields present both challenges and opportunities for institutional wealth managers. While commercial lenders and mortgage origination volumes face headwinds from elevated borrowing costs, fixed-income investors are locking in attractive real yields on high-quality sovereign and investment-grade corporate bonds. Institutional debt issuers, conversely, are recalibrating their capital structures, opting for shorter-term refinancing instruments or private credit facilities to avoid committing to elevated long-term coupon rates.

Navigating the current bond market landscape demands strict duration management and credit selection. Wealth advisors recommend maintaining flexible fixed-income allocations, combining short-duration Treasuries with inflation-protected securities (TIPS) to shield capital against potential energy-driven inflation spikes while earning dependable nominal income.

Continue Reading

Finance

Private Credit Expansion Transforms Corporate Loans

Published

on

Private Credit Expansion Transforms Corporate Loans

Private credit markets reached a pivotal milestone during the week ending July 25, 2026, as non-bank direct lending consortiums captured a record share of middle-market corporate debt originations. With commercial banks maintaining conservative credit standards and public bond yields remaining elevated, corporate borrowers are increasingly turning to private fund managers for customized capital solutions. This expansion marks a permanent structural shift in enterprise finance, establishing private credit as a primary pillar of institutional corporate liquidity.

The acceleration of private credit deals is driven by speed, deal certainty, and flexible terms. Unlike traditional syndicated bank loans that require lengthy underwriting, credit rating approvals, and public roadshows, private direct lenders can structure tailored financing packages within days. Middle-market firms facing upcoming debt maturities are utilizing private debt facilities to execute recapitalizations, strategic acquisitions, and growth capital deployments without risking execution delay in public markets.

However, financial regulators and central bank supervisors are scrutinizing the sector’s rapid growth. Supervisory agencies are evaluating potential systemic risks associated with non-bank leverage, valuation transparency, and liquidity mismatches during economic downturns. Despite regulatory interest, major pension funds, insurance firms, and sovereign wealth entities continue to expand capital allocations to private credit funds, attracted by reliable floating-rate yields that outperform public fixed-income benchmarks.

As private credit matures into a dominant asset class, corporate chief financial officers must evaluate non-bank lenders alongside traditional banking relationships. Direct lending partnerships provide valuable balance sheet resilience, enabling companies to secure flexible financing terms even during periods of public market turbulence.

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

Trending