Capitalizing on the Generative AI Opportunity

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CCG Catalyst Commentary

Capitalizing on the Generative AI Opportunity

By: Kate Drew

February 4, 2025

Artificial intelligence (AI) is everywhere. Not only in banking but also across industries, everyone is talking about how they can capitalize on it.

Importantly, this is not because the technology is new — far from it. Traditional AI-based technologies like machine learning and natural language processing (NLP) have been around for decades. What is new, however, is the massive leap forward that AI is experiencing with the advent of generative AI. Generative AI is a specific subset of AI that can quickly generate outputs of many formats from data inputs. It does this using large language models (LLMs), which are models that can analyze and generate human language. The most well-known LLM is Open AI’s GPT-4, on which ChatGPT is built. 

In banking, there are a slew of potential uses for this technology. However, because financial services is a highly regulated industry, there are also high barriers. In our latest report, Generative AI in Banking: Today, Tomorrow, and Beyond, we explore all of this.

Here’s a look at a few of the key areas we found generative AI proliferating among financial institutions (FIs):

  • Knowledge management. FIs are using generative AI to create “supercharged” intranets that often manifest as internal chatbots. These assistants can help employees surface information quickly and improve their efficiency.
  • Content development. Generative AI can be used to generate many forms of content, especially in sales and marketing. But we’re also seeing some unique use cases, such as developing procedures and creating training materials.
  • Customer service (with guardrails). Customer service is the buzziest use case for generative AI — chatbots are everywhere. But in financial services, the technology’s tendency to hallucinate, or draw inaccurate conclusions, is making implementation difficult. As such, for now, FIs are experimenting with generative AI for customer service but with a human in the loop.

Overall, we determined that, while generative AI represents an exciting opportunity for bankers, they are also moving slowly. There is a lot of risk involved with this technology, because it is so new. And because it can be inaccurate, putting it directly in front of customers is a nonstarter. As you can see, the use cases we’ve identified tend to be internal, even when it comes to customer service. We expect this to continue in the near term, until the technology matures, and society grows more comfortable.

That said, executives should ensure they understand the technology and how it can be used responsibly, so that they are able to identify it as a solution when it makes sense.  

Our report takes a close look at the generative AI opportunity in banking. It examines what the technology is and isn’t, how it is being used already, and how it may be used in the near and longer term. It includes case studies and real-world examples of its use in the field. The goal is to provide a baseline for financial services executives who want to understand this technology and how it is poised to impact the industry. You can download it here.

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