GenAI In Banking & Financial Services

What was an emerging transformation is already underway… by Elena Christopher

Elena Christopher is Chief Research Officer and Head of Financial Services Research at HFS Research, a global research and analysis firm specialized in the disruptive power of emerging technologies.
The banking and financial services industry stands on the cusp of a transformative era, propelled by the advent of generative AI (GenAI). GenAI is not merely an evolutionary step in technology; it is a revolutionary force capable of redefining industry standards, operational efficiencies, and customer experiences with the power to redefine how financial institutions operate, engage with customers, and manage risks. However, the path to realizing GenAI’s full potential is fraught with challenges—from ethical dilemmas to regulatory hurdles—necessitating a strategic and thoughtful approach to adoption. We’ll cover the roses and the thorns, but first a little context.

The Three Phases Of AI: Foundational, Generative, And Purposeful
While the hype and pace of announcements around all things artificial intelligence have exploded since large language model (LLM) darling ChatGPT 3 was announced in late 2022, AI has been an active element of the financial services sector for decades.

HFS categorizes the modern era of AI into three phases ( Exhibit 1): foundational, generative, and purposeful.

• Foundational AI (2010-2023): Phase 1 represents the technology building blocks, such as machine learning, computer vision, and natural language processing, that form the foundations of AI capabilities for the enterprise—the essential first steps for extracting greater value from AI. In Phase 1, we learned how to organize and use data in a way that can learn and become useful for workflows and interactions.
• Generative AI (2023-2027): Phase 2 is when the foundations are ready to exploit the value of AI and data at scale. Projects in this phase involve applying GenAI to vast amounts of information and asking it to generate useful output, such as developing code, identifying new process flows, generating dynamic chatbots that continually update business context, continually correlating data sources to drive probabilistic decision making, and collating cyber threat assessments via accessing industry-specific GenAI networks. As an example, HFS Research has Phase 2 in production on our website, where rather than using a basic web search, visitors to the HFS website can ask our large language model (LLM) a question and receive a natural language response it generates from all the research on our website.
• Purposeful AI (2025 onward): Phase 3 is where AI operates independently and effectively at scale, and humans set the guardrails by which AI will operate. Phase 3 projects take the principles of Phases 1 and 2 to the next level by leveraging multiple technologies and ecosystems to take the human out of the loop but allow the human to orchestrate the loop. Humans set the goals and boundaries, but the AI is empowered to deliver on the actions. If purposeful AI can navigate the complex apps ecosystem of today’s enterprise, we can imagine asking a digital assistant to onboard an employee and it automatically triggering tasks and executing device procurement, benefits briefing, training, and the like. Or, with a click of a button, one could plan demand, forecast, and optimize the supply chain network.