Morgan Stanleyof Geoff McMillan As head of enterprise artificial intelligence, he is focused on the development and deployment of AI across the $212 billion financial institution’s operations.
The New York-based FI McMillan will assume the newly created role on March 14.he said Bank Automation NewsMcMillan served as chief data and analytics officer at FI for eight years. LinkedIn profile.
“Morgan Stanley created this role to ensure the right AI strategy and governance is in place,” McMillan said. Ban.
In an interview Bank Automation NewsMcMillan discussed his priorities, including Morgan Stanley’s objectives for adopting AI and the potential impact of this generation on the financial services industry. Below is an edited version of the conversation.
Bank Automation NewsWhat is Morgan Stanley’s overall strategy?
Jeff MacMillanThrough a unique partnership with Open AIMorgan Stanley has early access to the firm’s new products and AI experts to create unique solutions tailored to our needs. The first use case in our wealth management division, Morgan Stanley Assistant’s AI delivers Morgan Stanley’s vast intellectual capital to our advisors in seconds and in an easy-to-understand format. Think of it as having our Chief Investment Strategist, Chief Global Economist and Global Equity Strategist on standby 24 hours a day.
The company has successfully deployed the AI Morgan Stanley Assistant to financial advisors, with a full rollout expected in September 2023.
Ban: What are some of the use cases you are considering?
James: To optimize efficiency, Morgan Stanley is introducing AI into Debrief, a tool that acts as an AI-enabled assistant to take notes on behalf of advisors during client meetings, summarize key discussion topics, and surface action items. The tool works by transcribing client meetings if the client gives prior explicit consent. After the meeting, the tool summarizes key points, creates an email for the financial advisor to edit and send, and stores the notes in Salesforce. Note that Debrief does not share information with third parties and all clients are given the opportunity to consent to the technology before its use. If a client is not comfortable with it, the technology will not be used for meetings.
Ban: What are your short-term and long-term goals for AI at Morgan Stanley?
James: We are identifying near-term use cases where all areas of the business can get involved, learn, and deliver value. To this end, we also plan to develop and roll out a series of company-wide training modules, tailored to different roles, many of which are aimed at showing the value and challenges these tools bring to all employees and getting them to think creatively about the future.
Longer term, Morgan Stanley AI will be an interaction layer that sits between our employees (advisors, bankers, salespeople, etc.) and all of the tools and information they have access to today. The goal is to reduce the complexity of the platform and make everything more seamless by getting what they need using language rather than the traditional formats of menus, search and clicks.
Eventually, you’ll be able to engage with them entirely through voice. AI can write proposals, evaluate alternative market scenarios, rebalance portfolios, create financial spreadsheets, and assist with a variety of repetitive operational or administrative tasks. I want to reiterate that the value here is in helping people do a better job for clients by making them smarter and more efficient.
Our hope is that AI will give us more time, not less, to do the things we enjoy: working with clients to solve complex problems and engaging with them. This won’t happen any time soon, but we’ve been mapping out the various building blocks.
Ban: How is Morgan Stanley going to implement generative AI?
JamesAs part of my new role, I will be working closely with the Morgan Stanley team to leverage Generation AI in a control-first, scalable way for use cases that fall into one of five categories:
- Search capabilities: Provide users with access to structured and unstructured content, as well as data and analytics using natural language prompts.
- Summarize: Allows employees to summarize, categorize, and summarize incoming documents or transcribed audio/video.
- Interpret and evaluate applications: Analyze text or audio content, apply logic, and draw conclusions.
- Generate solutions: Create original content based on reference material and prompts in text or image format.
- Translation: Provides the ability to translate content into 53 languages.
Ban: How will generative AI impact financial services?
James: Generative AI will usher in a new era of innovation with the potential to enable new business capabilities, pioneer value delivery, and expand the reach of companies’ products and services. It will enable organizations to create new products and technologies with significantly less friction. Additionally, companies will increasingly be measured and recognized for their ability to leverage and integrate AI to improve operational efficiency and productivity.
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