The Latest on Goldman Sachs's Open-Source Trading Floor

Summary

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WSJ Your Money Briefing

Episode: The Latest on Goldman Sachs's Open-Source Trading Floor
Date: April 4, 2019
Host: J.R. Whalen
Guest: Liz Hoffman (Wall Street Journal Reporter)

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Episode Overview

This episode explores Goldman Sachs’s unprecedented move to open up access to parts of its proprietary trading software and data, traditionally locked behind closed doors. Wall Street Journal reporter Liz Hoffman joins host J.R. Whalen to break down what this means for the finance industry, how the landscape has shifted since the 1990s, and what’s at stake for Goldman and its competitors. The conversation features comparisons to Silicon Valley’s tech model and discusses potential outcomes for this bold new strategy.

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Key Discussion Points & Insights

1. Background on Goldman Sachs’s Trading Engine (SECDB)

• Origin & Function: Goldman Sachs developed the Securities Database (SECDB) in the 1990s, which became “the brains of the trading operation” ([02:26], Liz Hoffman).

• Historical Importance: SECDB aggregated firm-wide data on prices, activity, and events—a groundbreaking tool at the time, allowing Goldman to earn enormous profits and weather the 2008 financial crisis better than many peers.

  “It was a really big deal then. And so that made Goldman just a ton of money in the 90s and the 2000s and helped them…stay out of as much trouble as others got into in 2007 and 2008.”
  — Liz Hoffman ([02:43])

2. Shifts in Regulation and Bank Strategy Post-2008

• Changing Laws: After the crisis, proprietary trading by big banks has largely been outlawed.

• Response: With in-house trading profits off the table, Goldman is pivoting to monetize its technology as a service for clients.

  “You cannot proprietary trade anymore after the financial crisis...There’s two ways to make money off something: you can use it and try to make money on yourself, or you can sell it to clients. And they’re effectively trying to sell this to clients as a service.”
  — Liz Hoffman ([03:07])

3. Modernizing Client Access: From Phone Calls to APIs

• Old Process: Hedge funds would call a Goldman salesperson, requesting custom data runs—a slow, labor-intensive method.

  “That’s a really time intensive and expensive process for Goldman. And it’s also just increasingly not how hedge funds want to get that data.”
  — Liz Hoffman ([03:46])

• New Approach: Developers and quantitative analysts at client firms can now directly access certain data and code, submit queries, and receive results nearly instantaneously through new digital interfaces.

  “Those guys want to be able to knock on the door on their own…and it’s going to do it instantaneously and I’m going to get that right back in a form that I understand…”
  — Liz Hoffman ([04:13])

4. Streamlining and Cost Efficiency

• Benefits: The shift reduces errors, costs, and delays compared to legacy manual processes, making data interactions smoother and more agile.

  “When you do this digitally, it’s… much, much smoother.”
  — Liz Hoffman ([04:38])

5. Monetization—Inspired by Silicon Valley

• Rationale: Goldman’s move echoes Amazon’s strategy of selling excess computing capacity (Amazon Web Services), turning internal capabilities into major revenue streams.

  “About 15 years ago, Amazon… realized that it had something valuable…Now Amazon Web Services is the largest provider of cloud computing and it accounts for like 3/4 of Amazon’s profits…”
  — Liz Hoffman ([05:06])

6. Access and Scope; Not an Entire Free-for-All

• Mechanics: Access is via GitHub; some data and analysis is open, but deeper access requires being a Goldman client and additional permissions.

• Competitors: Other banks are moving in the same direction; JP Morgan is particularly advanced in commercial payments technology, while Goldman leads on the trading side.

  “There’ll be certain types of data and certain types of analysis that you’ll have to be a Goldman client, that you’ll have to ask them for permission and they’ll share it with you. So, you know, they’re not throwing the doors totally wide open. This is a crack.”
  — Liz Hoffman ([05:52])

7. Risks and Uncertainties

• Market Expectations: Advanced quantitative clients have high standards; the offering must be robust to compete.

• Industry Implications: The move signals a broader tech-driven transformation in financial services but is not guaranteed success.

  “There’s so much, the expectations are so high at these really quantitative shops…If this isn’t good, it isn’t gonna work.”
  — Liz Hoffman ([06:37])

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Notable Quotes & Memorable Moments

• On Motivation:
  • “Goldman’s not doing this out of the goodness of their heart.”
    — J.R. Whalen ([04:49])
  • “Goodness, no.”
    — Liz Hoffman ([04:51])
• On “Opening the Doors”:
  • “Anybody can open that [GitHub] account...They’re not throwing the doors totally wide open. This is a crack.”
    — Liz Hoffman ([05:52])
• On Tech-Banking Convergence:
  • “Wall Street in general…I think in the last couple years has taken a look at Silicon Valley, where huge amounts of value have been created…banks are looking at this and thinking, well, what do we have that’s like that?”
    — Liz Hoffman ([05:04])

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Key Segment Timestamps

• [02:26] – History and development of SECDB
• [03:22] – Changing client delivery methods; shift to digital
• [04:38] – Discussion of smoothness and efficiency of digital access
• [05:06] – Amazon Web Services analogy and tech-banking convergence
• [05:52] – Access details, GitHub, and permission controls
• [06:09] – Industry landscape and competitive positioning

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Summary

This episode succinctly outlines how a giant of Wall Street is embracing the ethos of Silicon Valley by ‘cracking open’ its secretive trading tools. With regulations barring proprietary trading, Goldman Sachs aims to transform its internal tech into a new revenue stream for the digital age, setting a precedent competitors are closely watching. As banks and tech continue to converge, the experiment will test whether Wall Street’s unique data can be as lucrative and transformational as cloud computing has been for Amazon.

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Transcript

[A]

This episode is brought to you by Charles Schwab. Decisions made in Washington can affect your portfolio every day. Washington Wise from Charles Schwab is an original podcast that unpacks the stories making news in Washington. [e-mail] Washingtonwise.

[B]

Here's your Money briefing. I'm J.R. whalen at the Wall Street Journal in New York. Goldman Sachs is about to throw open the doors and let developers have access to to coding it uses to set the prices of things like derivatives and assess risk. We'll explain in a moment. First, these money and market stories. You should know average mortgage rates have come down to near 4%, and that has sparked a boom of sorts, refinancing. In fact, the Mortgage Bankers association says the mortgage application volume jumped 18% last week from a week earlier. But many in the industry feel if you're looking to refinance, you should strike while the iron is hot. The current low mortgage rates were just as low but back in January of last year and could cycle upward all over again. And check out Wall Street Journal Middle C columnist Scott McCartney's newest piece that focuses on whether you should buy travel insurance before taking a trip. McCartney says that while signing up for travel insurance might provide peace of mind for passengers, it turns out travel insurers write a lot of gotchas in most policies, especially, as he says, the inexpensive insurance sold through airlines and online travel agencies. Scott says many travelers find the coverage they thought they had really doesn't cover them at all. Or the coverage is redundant, as airlines will reimburse costs in some situations and credit cards offer some forms of travel insurance themselves. See Scott's full [e-mail] or the WSJ app, A big bank's trading engine. And proprietary data that would determine how much a derivative derivative should cost used to be coveted information that could make traders a lot of money. Well, now in the case of Goldman Sachs, that information is going to be available to people outside the bank. And Wall Street Journal reporter Liz Hoffman is here with some details. So, Liz, now, Goldman's proprietary trading engine was a real asset at one time. It helped it and traders get through the 2008 financial crisis, as you point out in your story. But the laws have changed.

[C]

Yeah. So to really understand the story, you have to go all the way back to the 1990s. And Goldman built something they called securities database called SECDB. And it was the brains of the trading operation. So would take in data from across the firm about what things were priced at where there was a lot of activity what was happening and that sounds like table stakes now. It was a really big deal then. And so that made Goldman just a ton of money in the 90s and the 2000s and helped them. Yes, you're right. Stay out of as much trouble as others got into in 2007 and 2008. The world is very different now. So you cannot proprietary trade anymore after the financial crisis. So what that means is that Goldman can't take information that it sees from clients and sort of, and use that to make money itself. So they have this really valuable thing and you know, there's two ways to make money off something. You can use it and try to make money on yourself, or you can sell it to clients. And they're effectively trying to sell this to clients as a service.

[B]

So like a lot of other banks, Goldman has been serving portfolio managers and traders and now they're serving developers by letting them more or less enter this database and providing them with some code to allow them to have access to some of the data.

[C]

So if you're at a hedge fund, you used to have to pick up the phone, you call your salesperson at Goldman and say, hey, can you give me a spreadsheet with all of the healthcare companies where some factor, where stock's been going up quickly or where they've had a change of management, I want to bet on those companies. And the trader would call over one of his, one of his nerds and he would say, can you run this data for me and send it back? And then they would send it back to the client. And that's a really time intensive and expensive process for Goldman. And it's also just increasingly not how hedge funds want to get that data. So hedge funds and other big asset managers have been hiring coders for themselves and those guys want to be able to knock on the door on their own and to send what queries to the database and say, all right, I'm going to send this line of code and it's going to ask for that same spreadsheet, but it's going to do it instantaneously and I'm going to get that right back in a form that I understand that I can monkey around with to get the sort of training results that I want.

[B]

Okay. So it takes some legwork into the process.

[C]

Absolutely. And some costs and you know, that's a very error prone process that involves a lot of people and you know, if you want to make a change to it, the whole thing has to start all over. When you do this digitally, it's Just, it's much, much smoother.

[B]

Goldman's not doing this out of the goodness of their heart.

[C]

Goodness, no.

[B]

They will still own the data and they'll make money off of it.

[C]

They will. Wall street in general, I think in the last couple years has taken a look at Silicon Valley where just huge amounts of value have been created, trillions of dollars of value and tech firms.

[B]

You made a good comparison about Amazon in your story.

[C]

Yeah, so, exactly right. So about 15 years ago, Amazon, which was then early 2000s, an online marketplace, it realized that it had something valuable. It had this extra capacity on all of its computer servers that it wasn't using it. And so what if we sold that? Now Amazon Web Services is the largest provider of cloud computing and it accounts for like 3/4 of Amazon's profits. So oh wow, not that much. It's massively profitable. So banks are looking at this and thinking, well, what do we have that's like that, that we kind of have lying around that we could use ourselves? Or we could also try to see if anyone wants to buy it. And they have risk management, that's what big banks are. They manage a lot of risk and they see a lot of things and they can analyze portfolios and that kind of stuff.

[B]

And in the case of Goldman, the developers would have to a GitHub account in order to do this.

[C]

That's right. Anybody can open that account. There'll be certain types of data and certain types of analysis that you'll have to be a Goldman client, that you'll have to ask them for permission and they'll share it with you. So you know, they're not throwing the doors totally wide open. This is a crack.

[B]

And some of Golden's rivals are looking to do the same sort of thing.

[C]

Everybody's trying to figure this out. I would say the most advanced is probably JP Morgan, which has its own version of that database secdb that we talked about. For the most part they have spent their time in the commercial payment side. They have some very good technology that allows developers at big companies to get a very good, for example, real time sense of their payments and their cash balances. I would say Goldman is more advanced on the trading side. But look, it's not a home run that this is going to work. There's so much, the expectations are so high at these really quantitative shops. They really want extremely good data, they want extremely good service and they're very picky about the tech that they use. So if this isn't good, it isn't gonna work.

[B]

All right. Well, we'll see if it does. Good reason to keep it tuned to the Wall Street Journal, WSJ.com and Liz Hoffman's coverage of Goldman Sachs. And she's good enough to join us here in our studio. Liz, thanks for coming on the show.

[C]

Happy to be here.

[B]

And that's your money briefing. I'm J.R. whelan in New York for the Wall Street Journal.

[A]

This episode is brought to you by Charles Schwab. Decisions made in Washington can affect your portfolio every day, but what policy changes should investors be watching? Washington Wise is an original podcast from Charles Schwab that unpacks the stories making news in Washington right now and how they may affect your finances and portfolio. [e-mail] WashingtonWise.