Generative artificial intelligence, the technology popularized by ChatGPT, is significantly transforming banking operations. As per McKinsey, this innovative AI could contribute an additional \(200 to \)340 billion annually to banks, equating to 9–15 percent of their operating profits. This article explores how Morgan Stanley, a prominent financial entity, has integrated relational AI and its potential applications within the banking and finance sectors.
Unveiling Morgan Stanley’s Innovative AI Assistant
In 2023, Morgan Stanley introduced a cutting-edge internal AI assistant powered by OpenAI’s ChatGPT models. Known as the AI @ Morgan Stanley Assistant, this platform is designed to streamline access to and comprehension of over 100,000 research reports for Morgan Stanley financial advisors and support personnel.
Essentially functioning as a tailored financial encyclopedia, the AI assistant empowers professionals in the finance industry to address queries regarding investment recommendations, overall business performance, and even internal processes like form completions. It serves as a virtual “copilot” for Morgan Stanley staff, enhancing their operational efficiency. Beyond finance, conceptual AI is making headway as a versatile tool across various sectors, including healthcare, software development, education, and more.
In a communication to Morgan Stanley employees, co-president Andy Saperstein highlighted the AI assistant’s potential to “revolutionize client interactions, introduce operational efficiencies to advisor practices, and ultimately liberate time for focusing on core client services.”
Generative AI excels in interpreting verbal prompts, processing vast data sets, and generating user-friendly solutions based on acquired knowledge. Hence, Morgan Stanley’s initial adoption of conceptual AI aims to optimize research and administrative tasks, allowing professionals to concentrate on value-added activities. Moreover, ongoing developments include tools like Debrief, intended to summarize client interactions swiftly and review subsequent correspondence.
Brokerage Scenarios and Prospects in Banking
Given conceptual AI’s capacity for data analysis, modeling, and information synthesis, financial institutions can leverage this technology to enhance decision-making, foster growth, and elevate customer service standards.
For instance, AI-powered banking chatbots can offer round-the-clock assistance in addressing queries and resolving issues. Customer onboarding processes can be streamlined with the aid of conceptual AI, guiding customers through tasks like account transitions effectively. This shift heralds a new era of conversational banking that closely mimics traditional in-person interactions.
Personalization emerges as a key application in banking, enabling tailored tools and recommendations to help customers manage their finances prudently. Generative AI facilitates a deeper understanding of customer preferences and behaviors, empowering banks to develop bespoke products and services. By discerning how distinct features resonate with various customer segments, banks can deliver personalized offerings that cater to diverse needs effectively.
Another pivotal use case involves automating administrative functions within financial institutions, encompassing tasks like financial analysis and content creation. Generative AI can be instrumental in crafting credit assessment models, formulating user-friendly explanations for application rejections, enhancing fraud detection mechanisms, optimizing asset management strategies, and fortifying risk management protocols.
Adoption of Generative AI Across Banks
The integration of generative AI is already underway in several banking institutions. For instance, NatWest, in collaboration with IBM, is enhancing its virtual assistant, Cora, to provide customers with personalized information through interactive conversations.
Square, a financial services platform under Block Inc., is leveraging generative AI to offer innovative solutions for customer engagement, onboarding, and setup processes. Noteworthy features include a Menu Generator tool for creating restaurant menus online swiftly and an AI-powered email function for crafting personalized messages. Moreover, a website copy generator is available for generating website content efficiently. Looking ahead, banks could harness generative AI to develop time-saving tools and products for their corporate clientele.
Additionally, global bank HSBC has identified numerous potential applications for generative AI across its operations.
In conclusion, banking institutions have evolved into tech-savvy entities in recent years. Generative AI is poised to elevate this transformation further, enabling banks to streamline operations and elevate customer service standards. Any financial entity that overlooks the potential of generative AI risks lagging behind in this era of technological advancement.
