Inside Wall Streets biggest tech projects, from Blackstone’s DocAI to Goldman Sachs’ Legend

Project name: Citi Integrated Digital Assets Platform

What it is: A blockchain platform for the bank to offer institutional clients digital-asset products

Lead executive: Nimrod Barak, head of Citi Innovation Labs

Despite crypto’s upturns and downturns on Main Street among retail investors, a top tech exec at Citi says there’s still value and potential for the underlying technology on Wall Street.

The bank launched CIDAP this summer for its blockchain offerings for institutional clients. The aim is to consolidate Citi’s digital-asset products and services, which span liquidity management, trade finance, bonds, and custody. Doing so not only makes it easier for the bank to manage and update its offerings but could make it faster to onboard any new use cases, Barak told BI.

Citi offers several blockchain-based services. One is tokenizing cash to quickly move deposits between Citi branches globally at any hour. Another is digital custody and settlement services to speed up processing times.

Barak said that blockchain was maturing, now able to be used for enterprise infrastructure and institutions. He added that corporate clients were increasingly interested in the technology.

“We see that blockchain has emerged as a materially positive impact on financial services across the value chain,” Barak said.

Project name: Legend

What it is: Creating one platform for all the bank’s data to automate more tasks

Lead executive: Neema Raphael, chief data officer

At Goldman Sachs, every dollar invested, trade executed, company met, and loan financed is another data point that could fuel the bank’s analytics engines.

But as it amassed large troves of data, less time was spent organizing that data and figuring out how different teams would access it. That’s why Goldman Sachs developed Legend about a decade ago to be its one place for accessing all its important data.

Doing so could allow employees to quickly unearth connections that could lead to multimillion-dollar deals, automate some operations-heavy work, and let quants and data scientists build AI models that can find new patterns.

Now Legend has become a priority, thanks to the explosion of data — and its potential to train generative-AI models and automate back-end processes.

“The most important things that we do, every business function and every business process, has some touchpoint to Legend and Legend data,” Raphael told BI.

Legend allows everyone at Goldman — software developers, risk-management experts, and bankers — to see and use the same set of data, giving the bank “one version of the truth for all use cases,” Raphael said. Through that consolidation, Goldman can also save on infrastructure and operational costs, since data doesn’t need to constantly be reconciled, processed, and copied from system to system.

Raphael said the bank wants to use Legend to help grow its asset- and wealth-management business and its sales and trading business, where data issues could hinder automation for certain processes.

“What we’ve noticed is that at some tipping point, the automation and scale falls down a bit,” he said, referring to back-end processes, “and it’s usually because of data issues that you couldn’t automate.”

Project name: Condor

What it is: Rebuilding a key platform for Man Group’s systematic-trading business to take on more data and asset classes

Lead executive: Barry Fitzgerald, cohead of front-office engineering

The world’s largest publicly listed hedge fund is in a multiyear rebuild of its systematic-trading and quantitative-research platform.

The new platform, called Condor, was initially designed to serve Man AHL, the firm’s systematic-investing arm. But Fitzgerald has bigger plans: more asset classes, more investing styles, and more data.

“The worst thing we could do with this is build something that fulfills our need for exactly today,” Fitzgerald told BI, adding: “We don’t know how we will trade in two years’ time, but I would hope this platform runs for 10 years or longer. It is a big multiyear project, so it should get the payback.”

Fifteen years ago, Man AHL was known mostly for its systematic futures trading, but the firm has expanded to other asset classes, like equities, corporate bonds, and options, with varying holding periods. Over time, Man built different systems to trade them all.

With Condor, Fitzgerald aims to bring those together — the research, the trading, and the logging — into a single platform. Because Condor will replace what is now a bunch of different systems, a variety of workers will use it: Quant researchers could develop investing strategies, tech teams could add features, and risk and operations teams could support trading systems. He said that having one platform for all these uses would help provide a cross-asset view of its risk exposure, conceptualize allocations across all assets, and do more analytics.

Work on Condor began about 18 months ago, and Fitzgerald expects it’ll be another two or three years until it’s fully integrated. Quantitative researchers are already using it to experiment with statistical models. He added that some calculations for big multiasset research graphs now take 30 minutes instead of 12 hours. Over time, he said, it’ll hopefully expand to encompass all of Man’s asset classes and trading styles.

Project name: Lightning

What it is: A firmwide data platform designed to quickly move and process data, saving engineers time and speeding up analytics

Lead executive: Mona Eldam, head of technology in Singapore and distinguished engineer

When Morgan Stanley began migrating to the public cloud in 2021 from its on-premise data centers, it needed something that could help the bank move its data quickly, handle loads of different types of data, and ensure that the data quality didn’t falter during the transfer.

Eldam rounded up her troops of data engineers spread out across 10 locations globally. Her team is responsible for managing data on behalf of the bank’s investment and wealth-management businesses as well as its institutional securities unit.

In those early days, Eldam had to solve for moving about 20 sources of data, numbering hundreds of entries, every 10 minutes.

Lightning, which was initially built to move and bring together these disparate types of data, has become the standard for how Morgan Stanley moves data, regardless of whether it’s on-premise or the cloud. Lightning underpins more than 80 client applications. It moves several terabytes of data for Morgan Stanley every day, and the firm says overall data-migration turnaround time has been reduced by 75% on average. Thanks to Lightning, engineers don’t have to spend time developing their own frameworks for moving data.

Eldam said her team was adding functions to Lightning, including the ability to handle data in graph databases and ways to flag when a job needs more cloud capacity.