AI in Morgan Stanley: Reshaping the Future of Financial Services with AI

Morgan Stanley is a prominent global investment bank and wealth management firm, employing over 82,000 people worldwide and operating in 42 countries. The firm provides a diverse array of services, including investment banking, securities, wealth management, and investment management, catering to corporations, governments, institutions, and individuals.

As a titan in the financial sector, Morgan Stanley has adopted AI as a transformative power to enhance various aspects of its business, particularly in wealth management, client engagement, and operational efficiency.

The company’s strategic investment in AI and its disciplined approach to tech adoption highlight its commitment to driving innovation and maintaining its leadership in the financial industry.

This article explores how Morgan Stanley has embraced AI technologies to improve its functions, enhance consumer experiences, and remain competitive in the marketplace.

AI in Morgan Stanley

Launch of AI @ Morgan Stanley Assistant

In September 2023, the firm launched AI @ Morgan Stanley, an internal assistant powered by OpenAI’s ChatGPT technology.

According to the press release, this tool allows financial advisors to quickly retrieve information and answers. The tool also allows increasing document retrieval efficiency from 20 percent to 80 percent.

According to the company’s press release, this tool enables quick information retrieval and answers to financial advisors’ questions, significantly reducing search time and increasing document retrieval efficiency from 20 percent to 80 percent.

It’s a custom encyclopedia for finance professionals, helping them answer questions on investment recommendations, business performance, and internal processes.

Think of it as a sort of ‘copilot’ for Morgan Stanley staff, helping them do their jobs more efficiently.

Expanded offerings with AI @ Morgan Stanley Debrief

Building on this success, the company expanded its AI offerings with ‘AI @ Morgan Stanley Debrief’, a meeting summary tool for financial advisors. This tool automatically transcribes and summarizes Zoom meetings into actionable outputs, integrating client notes and draft follow-ups into CRM systems.

Upon the successful rollout of the AI initiative, Vince Lumia, Head of Morgan Stanley Wealth Management Client Segments said:

“AI @ Morgan Stanley Debrief drives immense efficiency in an Advisors’ day-to-day, allowing more time to spend on meaningful engagement with their clients.

Because at the end of the day, the Financial Advisor’s service, advice, and relationships with clients—the human touch—remains fundamental.”

Likewise, Jeff McMillan, Head of Firmwide Artificial Intelligence at Morgan Stanley, said:

“As we progress with our AI initiatives at Morgan Stanley, we foresee AI serving as a vital efficiency-enhancing layer that connects our colleagues to a range of essential applications. This includes execution and order entry systems, customer relationship management tools, reporting systems, and risk analysis platforms.”

“Through this rollout, Financial Advisors continue to see firsthand the real benefits GenAI delivers to their practices.

And we’re just getting started in unlocking the true power of this technology for all of Morgan Stanley”.

Launch of AskResearchGPT

Recently, Morgan Stanley launched AskResearchGPT, a cutting-edge AI tool powered by OpenAI’s GPT-4.

AskResearchGPT is the first application in the ‘Institutional Securities’ sector, joining a steadily expanding collection of generative AI-powered tools. This collection includes the AI @ Morgan Stanley Assistant and the AI @ Morgan Stanley Debrief, both of which were successfully launched for the firm’s ‘Wealth Management’ financial advisors and staff over the past year.

Building on the AskResearch chatbot, AskResearchGPT incorporates OpenAI’s GPT-4 model to synthesize unstructured data and provide more in-depth insights. It allows teams to tackle complex client queries with ease, making research accessible through commonly used productivity and communication tools.

AskResearchGPT also integrates with Morgan Stanley’s patented workflow solution, allowing staff to export research findings directly into email drafts.

These drafts, equipped with hyperlinks to original reports, ensure clients can explore the material further, offering a streamlined experience that improves efficiency and service quality.

With the latest launch of AskResearchGPT, Morgan Stanley is reinforcing its role as a leader in AI-driven financial services.

Implementing an evaluation (eval) framework

Implementing AI at Morgan Stanley required assurance that the technology would provide significant value while adhering to the firm’s stringent quality and reliability standards.

Morgan Stanley met this challenge by implementing an evaluation framework to test every AI use case before deployment. The evaluation (evals) framework measured how models perform against real-world use cases. It helped bring improvements, with expert feedback, at every step.

However, the evaluation framework wasn’t static; it evolved as the team learned.

They introduced translation evals for multilingual clients and worked closely with OpenAI to fine-tune retrieval methods, ensuring AI could handle an ever-expanding document library. 

“We went from being able to answer 7,000 questions to a place where we can now effectively answer any question from a corpus of 100,000 documents,” says David Wu, Head of Firmwide AI Product & Architecture Strategy at Morgan Stanley.

Likewise, to maintain compliance and security, Morgan Stanley has integrated quality assurance into its evaluation framework. This is to ensure data privacy and regulatory standards are met.

OpenAI’s zero data retention policy further addresses key security concerns, preventing proprietary data from being used to train public AI models. 

Things to note for CTOs and other business leaders

This case study of AI in Morgan Stanley demonstrates the diverse approaches organizations can take to AI implementation. It offers valuable insights for businesses developing their AI strategies.

Leaders and organizations that thoughtfully adapt these lessons to their specific contexts will be better positioned to realize AI’s full potential.

However, leaders should note that AI systems, despite their advancements, face several limitations. 

AI systems face several limitations, including difficulties with commonsense reasoning, creativity, and emotional intelligence. They also encounter challenges in ethical decision-making and understanding context. Moreover, AI can perpetuate biases that exist in the training data and often struggles with interpretability and explainability. Recognizing these constraints is essential for establishing realistic expectations.

However, through continuous research, ethical considerations, and collaborative efforts, leaders can unlock AI’s full potential while addressing its inherent limitations.

Additionally, AI can perpetuate biases present in training data and may struggle with interpretability and explainability. Acknowledging its current constraints is crucial for setting realistic expectations. 

However, through continuous research, ethical considerations, and collaborative efforts, leaders can unlock AI’s full potential while addressing its inherent limitations.

In brief

Financial services are using AI to improve efficiency and deepen the relationship between their advisers and customers.  As AI advances, these firms will likely see even more sophisticated tools that will further optimize business operations, serve greater ROI, and provide more customer satisfaction.