Goldman Builds What It Used to Buy
CIO Marco Argenti says AI cut build times enough to terminate vendor contracts.
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NEWS
Goldman CIO on AI Inside the Bank
Goldman Sachs CIO Marco Argenti said AI has made it cheap enough to build smaller applications in-house, with the firm already terminating some third-party software contracts.
Marco Argenti, speaking on Bloomberg’s Odd Lots podcast, said the buy-versus-build calculation has shifted. Engineers can now build working applications in days rather than months, he said.
Other notes from the podcast:
Goldman’s internal AI assistant is deployed to 47,000 employees logging more than a million prompts a month.
On token costs, Argenti expects per-unit prices to fall but total consumption to rise faster. Goldman built a model gateway that routes queries to the cheapest model that can handle them. “Total token cost is going to be a major item of cost in any organization,” he said. “It’s to be compared to the cost of people.”
Agents as a Service
Citi Ventures says AI-native startups are beginning to convert work historically done by humans in functions like IT, sales, legal, and HR into software-driven workflows, charging for completed tasks rather than software licenses and putting pressure on traditional per-seat SaaS pricing.
The note points to the growing importance of specialized models, particularly large tabular models designed for structured financial data like fraud detection and credit risk, where traditional language models are less effective.
Related
Retail Broker Rolls Out AI agents that Place Trades
Public, a retail brokerage, is rolling out AI agents that can execute trades on behalf of customers, automating tactics like protective hedging, cash sweeps into higher-yield assets, and stop-loss orders based on predefined rules.
Users write out a strategy, refine it through follow-up prompts, and review a step-by-step workflow before the agent goes live. The system logs every action and operates within fixed instructions. “It can only do what you tell it to do,” co-CEO Jannick Malling told the WSJ.
Public joins Robinhood and eToro in pushing AI beyond research and into execution. Brokerages are now starting to let those systems convert user-defined strategies into live trades.
FDIC Moves to Ease AI Model Risk Rules for Banks
The FDIC is revisiting its model risk management guidance, with an agency official telling Congress it has been applied too broadly and imposed unnecessary burdens, particularly on smaller banks, without a meaningful reduction in risk. The agency is working with the Fed and OCC on a more tailored, risk-based approach that accounts for a bank’s size, complexity, and the materiality of each model.
The shift does not change safety expectations but could reduce supervisory friction for lower-risk AI applications such as internal copilots and summarization tools, while models used in credit and risk management remain tightly governed. The official also said the FDIC expects to roll out GenAI tools to its own staff by mid-year.
Top Bridgewater Scientist to Join Google DeepMind
Jasjeet Sekhon, former head of AI at Bridgewater Associates, is set to join Google DeepMind as chief strategy officer, a move that reflects how quantitative investing and AI research are converging: both train models on large datasets to identify patterns and make predictions.
Perplexity Runs AI Agent Stock Pitch Contest
Perplexity is running a stock pitch competition for college students, offering $17,500 in prizes for investment theses built using its Computer product, a general-purpose AI agent that it says executes multi-step workflows autonomously.
The judges are Philippe Laffont of Coatue, Dan Loeb of Third Point, and Ken Hao of Silver Lake. Submissions are due April 3.
What Else I’m Reading
AI Companies Shatter Fund-Raising Records, as Boom Accelerates NYTimes
Bank of America’s wealth management firms roll out AI tool Banking Dive
Starling Bank Launches UK’s First Agentic AI Money Manager Fintech Times
QuantumStreet AI launches long-short global equity strategy Hedgeweek
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