Wall Street is undergoing a fundamental transformation as major financial institutions embrace open-source technology, marking a dramatic shift from the industry’s traditionally secretive and proprietary culture. Morgan Stanley’s managing director Dov Katz revealed that the bank now prioritizes open-source solutions over building proprietary systems, asking developers to consider whether existing open-source alternatives can meet their needs before creating something new.
The numbers tell a compelling story: Financial services workers contributed more than 750,000 commits to GitHub in 2023, representing a 55% increase from 2021 levels. By 2024, commits jumped another 26%, while the Fintech Open Source Foundation (FINOS) surpassed 100 members, including JPMorgan, Goldman Sachs, BlackRock, and Point72. This shift comes as global technology spending in banking reached $650 billion in 2023—roughly equivalent to Belgium’s GDP—with shareholders demanding quantifiable returns on these massive investments.
Major institutions are open-sourcing critical platforms: JPMorgan released its Salt design platform in 2022, Morgan Stanley contributed Morphir in 2020, Citi open-sourced GitProxy, Goldman Sachs shared its Legend data platform, and BlackRock opened up Aladdin, its technological crown jewel. These moves represent utilities like testing frameworks, data connectors, and development tools—what Katz calls “trivial commodity capabilities” that don’t provide competitive advantage.
The benefits extend beyond cost savings: Open source allows firms to share development burdens, free engineers for higher-value work, speed up vendor integrations, and improve talent retention. Goldman Sachs’ chief data officer Neema Raphael noted that “contributing to open source and having your name out there in open source is almost like table stakes” for engineering satisfaction.
AI represents the next frontier for Wall Street’s open-source adoption. FINOS launched an AI-readiness group attracting Citi, Morgan Stanley, and the London Stock Exchange to collaboratively develop frameworks around generative AI, addressing concerns like model bias and technology adoption. The recent emergence of DeepSeek’s open-source AI models—rivaling OpenAI’s proprietary offerings at significantly lower costs—has intensified focus on open versus closed AI approaches. Blackstone is building an open-source library for portfolio companies covering data management and generative AI, allowing them to redirect engineering resources toward proprietary innovations.
Key Quotes
I tell technologists all the time, if you’re building something and it is not a source of competitive advantage, you have to wonder: ‘Is this already outside? Should I be using it if I’m not using it? Is there something or a gap that I should be improving and contributing back my improvement?’
Dov Katz, managing director at Morgan Stanley overseeing tens of thousands of developers, explains the bank’s philosophy of prioritizing open-source solutions over building proprietary systems. This represents a fundamental shift in how Wall Street approaches technology development.
Contributing to open source and having your name out there in open source is almost like table stakes.
Neema Raphael, Goldman Sachs’ chief data officer with over two decades at the bank, highlights how open-source contribution has become essential for engineering talent retention and job satisfaction, demonstrating the cultural transformation within financial institutions.
That’s very much an industry problem, not an individual company problem. What better thing than to mutualize it and try to tackle it together.
Katz explains the rationale behind FINOS’s AI-readiness group, which brings together firms like Citi, Morgan Stanley, and the London Stock Exchange to collaboratively address generative AI challenges like bias mitigation and adoption frameworks, rather than each firm solving these problems independently.
As we go through discussing open source, the more I can pivot engineers away from building functionality that is nonproprietary and duplicative on the Street and just have a smaller set of those engineers build that collaboratively, I can have them focus on delivering much-higher-value work for our clients at the end of the day.
John Stecher, Blackstone’s chief technology officer, articulates the strategic value proposition of open source for private equity, explaining how the firm is building an open-source library for portfolio companies in data management and generative AI to free engineering resources for more meaningful work.
Our Take
Wall Street’s embrace of open-source AI represents a pragmatic recognition that the challenges of implementing generative AI—governance, bias mitigation, regulatory compliance—are too complex and resource-intensive for individual firms to solve efficiently. The DeepSeek disruption has accelerated this realization, demonstrating that open-source models can match or exceed proprietary alternatives at fraction of the cost.
This shift fundamentally redefines where competitive advantage lies in financial services. Rather than hoarding basic infrastructure and utilities, firms are recognizing that true differentiation comes from application and execution, not foundational technology. The 55% increase in GitHub commits from financial services workers signals this isn’t just talk—it’s a measurable transformation in how Wall Street builds technology. As AI becomes increasingly central to financial services, this collaborative approach could determine which institutions successfully navigate the transition while managing costs and attracting top engineering talent.
Why This Matters
This transformation represents a fundamental cultural shift in one of the world’s most competitive industries, with profound implications for AI development and adoption. As financial institutions face mounting pressure to justify massive technology investments, open-source collaboration offers a path to reduce costs, accelerate innovation, and avoid duplicative work across the industry.
The timing is particularly significant as generative AI demands enormous resources and expertise. By pooling knowledge and infrastructure through open-source initiatives, Wall Street firms can tackle common challenges like AI bias, governance frameworks, and regulatory compliance more effectively than individual companies working in isolation. The DeepSeek versus OpenAI dynamic demonstrates how open-source AI models can challenge proprietary approaches, potentially democratizing access to cutting-edge AI capabilities.
This shift could reshape competitive dynamics across financial services, moving competition from infrastructure and utilities to higher-value applications and client services. It also signals that even traditionally secretive industries recognize that collaboration on foundational technologies benefits everyone, while true competitive advantage lies in how these tools are applied to serve customers and generate insights.
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Source: https://www.businessinsider.com/inside-open-source-wall-street-technology-ai-2025-2