Wall Street Banks Are Doubling Down on AI

JPMorgan Chase and Goldman Sachs are leading the charge

Summary
  • JPM embraces AI for personalized investment advice, exploring blockchain technology, prioritizing ethical AI practices and aims to enhance operational efficiency.
  • The bank focuses on data analytics, AI and a multi-vendor public cloud strategy to drive business value, optimize operations and enhance customer experiences.
  • Goldman Sachs is edging on AI and ML for operational efficiency, leveraging generative AI for software development and an AI-powered networking platform called Louisa.
  • Goldman’s AI leads in private market investments, operational workflow, and software development for enhanced productivity and efficiency, overcoming challenges for full implementation.
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Wall Street giants JPMorgan Chase & Co. (JPM, Financial) and Goldman Sachs Group Inc. (GS, Financial) have tightened their grip on artificial intelligence. The banking powerhouses are harnessing the potential of the technology to revolutionize investment advice, optimize operational workflows and enhance customer experiences.

JPMorgan is leveraging AI algorithms for personalized guidance, exploring blockchain technology and championing ethical AI practices. Meanwhile, Goldman is at the forefront of AI adoption, utilizing generative AI for software development and introducing an AI-powered networking platform.

Let's explore how, with these bold strides, leading Wall Street banks are paving the way for a new era of AI-driven innovation.

JPMorgan Chase

The development of IndexGPT, a ChatGPT-like software service for investment advice, signifies JPMorgan's (JPM, Financial) objective to capitalize on the power of AI in the financial sector. By leveraging algorithms, the company aims to provide its customers with personalized and efficient investment guidance. The move indicates the bank is actively exploring opportunities to leverage AI technology to improve its services and differentiate itself.

Additionally, JPMorgan's exploration of blockchain technology through projects like Quorum highlight its efforts on the transformative potential of distributed ledger technology. By actively exploring applications beyond cryptocurrency, the company aims to optimize processes, improve client experiences and build new revenue streams.

As the bank intensifies its capabilities, it emphasizes the importance of ensuring ethical and socially good AI practices. Establishing the Explainable AI Center of Excellence demonstrates the company's lead in transparency and accountability in AI algorithms. The focus on ethical AI practices aligns with the growing societal demand for responsible deployment, benefiting JPMorgan in the ESG space.

Further, its objective of applying AI to improve the client experience and empower employees reflects its commitment to delivering competitive services and optimizing operational efficiencies. By leveraging AI to personalize client interactions, analyze behavior and increase productivity, the company aims to provide an enhanced experience for both clients and employees. The customer-centric approach suggests JPMorgan may continue to invest in AI solutions to improve its services and strengthen customer relationships.

The bank has demonstrated a strong focus on leveraging data and AI technologies to drive value ($1 billion) and enhance its operations. With a multi-vendor public cloud strategy, it concentrates on optimizing its data centers while taking advantage of the benefits offered by the public cloud. The strategic approach allows the company to scale its operations effectively and improve their data management capabilities.

Additionally, the company's emphasis on data analytics and machine learning is evident in its effort to employ over 2,000 data managers, data scientists and machine learning engineers. By harnessing the potential of data-driven insights, JPMorgan is attempting to optimize processes, enhance risk management and improve customer experiences. Its lead on data analytics and machine learning indicates the company may continue to leverage these technologies to gain a competitive edge and deliver value for its customers.

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Source: JPM Global Technology

Moreover, JPMorgan has made significant progress in implementing AI use cases, with over 300 in production across various areas, such as risk, prospecting, marketing, customer experience and fraud prevention. These use cases have already delivered substantial business value, with more than $220 million in benefits generated from personalized retail products and experiences alone. Leveraging AI in sales will provide $100 million of benefits in 2022, enhancing client relationships and driving growth in the commercial bank.

The company's modernization investments have played a vital role in enabling the migration of large amounts of data to the public cloud and enhancing the capabilities of its data platforms. The modernization facilitates faster model development with embedded governance, reflecting its investment discipline in deploying AI throughout the organization. JPMorgan has seen strong returns on investment, with a 25% year-over-year increase in 2022, and it anticipates this trend will continue.

Looking ahead, the company is actively exploring the potential of large language models like GPT4, with several use cases leveraging these models currently under testing and evaluation. It is configuring their environment and capabilities to enable these models and are committed to the responsible use of AI, employing an interdisciplinary team to assess risks, build appropriate controls and ensure compliance.

Overall, JPMorgan's annual investment of $12 billion in technology demonstrates its dedication to staying ahead of the curve. With a team of 50,000 technologists, the ongoing investment indicates the financial giant may continue to adopt and integrate new technologies, potentially disrupting traditional banking practices.

Goldman Sachs

Goldman (GS, Financial) has acknowledged the transformative implication of AI technology and is actively exploring its implementation across various aspects of its business operations. With AI and machine learning at the front of its digital transformation strategies, Goldman is trying to enhance operational efficiency, mitigate risks and deliver improved services to its clients.

Additionally, the company has measured the rapid advancements in generative AI and LLMs. These technologies can potentially automate document categorization, coding and summarization tasks. Goldman is currently in the proof-of-concept stage of utilizing generative AI for software development. Its software engineers are experimenting with AI to create and test code autonomously.

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Source: Goldman Sachs Research

Further, Goldman has also ventured into AI-powered networking with the spinoff of its first startup, Louisa. Louisa is a networking platform designed for corporate use, aiming to address the challenges of establishing connections within large organizations. By automatically generating user profiles and leveraging AI algorithms, Louisa proactively connects individuals who may benefit from networking with each other. The startup has gained traction within Goldman and plans to expand its client base beyond the bank. The innovative platform aligns with the evolving needs of remote and hybrid work arrangements, where traditional networking methods are becoming less effective.

Looking forward, Goldman emphasizes the impact of AI on the company's private market investments. By integrating AI tools into operational workflows, companies in sectors like health care and education can enhance productivity and improve operational efficiencies. Goldman is actively evaluating opportunities in companies that have successfully integrated AI technology. The shift in investment strategy reflects a broader trend in the private market, favoring smaller add-on acquisitions over capital-intensive exertions like leveraged buyouts.

Notably, Goldman views AI as a tool to augment the productivity of its software engineers. By automating coding tasks and utilizing algorithms for document classification and categorization, the company aims to achieve significant efficiency gains. These initiatives have demonstrated double-digit coding efficiencies and document classification accuracies comparable to human performance.

However, challenges remain in the adoption of AI. Talent acquisition, cost considerations and data privacy concerns are barriers that must be overcome. While Goldman is actively experimenting with AI and making progress, it will still be some time before full implementation of generative AI solutions can be expected.

Takeaway

In conclusion, it is difficult to determine a clear winner between JPMorgan and Goldman regarding their adoption of AI. Both banks have shown strong commitment and progress in leveraging the technology.

Comparatively, JPMorgan emerges as the stronger contender in the adoption of AI, with its focus on personalized investment advice, ethical practices, data analytics and commitment to customer-centric innovation. On the other hand, Goldman's moves in generative AI for software development and the release of the Louisa networking platform demonstrate its forward approach.

Disclosures

I/we have no positions in any stocks mentioned, and have no plans to buy any new positions in the stocks mentioned within the next 72 hours. Click for the complete disclosure