It’s been over one year since artificial intelligence (AI) research organization OpenAI released ChatGPT, an AI chatbot powered by the generative pre-trained transformer (GPT) large language model (LLM). Since then, AI advancements have seemingly taken the world by storm. While the use of AI in banking institutions is not new—think operational efficiencies and basic virtual assistants—more sophisticated generative AI (GAI) models have the potential to spark transformative changes in the financial services sector. The perhaps inevitable integration of GAI in financial institutions will challenge firms to approach these changes with caution and foresight. Responsible development, ethical data management and robust cybersecurity measures are essential to harness the power of generative AI while ensuring a financially inclusive and equitable future.

Corporate Insight recently conducted a survey to assess how bank and credit card users feel about the current use and potential growth of GAI in the financial industry. Key takeaways from the survey include:

  • Younger generations were more likely to have already used GAI: 70% of Gen Zers and 63% of Millennials reported that they had used GAI in the past. Meanwhile, just 46% of Gen Xers and 22% of Boomers reported using GAI.
  • Nearly half of respondents (45%) reported that they were more concerned than excited about the idea of their financial institution using generative AI technologies for tasks such as fraud analysis and document automation.
  • The majority of respondents (69%) answered that, within the next decade, artificial intelligence will have a major influence on daily life in the United States.
  • Respondents who had previously used GAI reported that they were more comfortable with the current presence of AI in consumer financial services (e.g., virtual assistants and robo-advisors) with 39% reporting they were somewhat comfortable and 17% reporting they were extremely comfortable. In contrast, just 16% of respondents who had never used GAI responded that they were somewhat comfortable, and just 2% said they were extremely comfortable.
  • Generally, as income increased, so too did the belief that generative AI would improve financial services and banks’ capabilities.

A chart showing the various comfortability levels with Gen AI across generations

Large North American banks—such as J.P. Morgan Chase, Capital One, Wells Fargo and TD Bank—have already started to further develop AI research labs and partnerships. The road ahead may promise revolutionary changes, including impacts on the following sectors.

Enhanced customer service

Recent research from Corporate Insight found that most bank chatbots lack language sophistication, struggling to complete complex tasks beyond basic account servicing before redirecting users to other site pages. While some firms’ chatbots—such as Bank of America’s Erica or U.S. Bank’s Smart Assistant—can handle common account servicing requests, this practice is not yet employed on a larger industry scale. Generative AI assistants—such as ChatGPT or Google’s Gemini—offer detailed answers to more complex queries, complete data pulls more consistently and do not falter when met with spelling or grammar mistakes. American fintechs Dave and Public have recently released LLM-powered chatbots to the public, as has EU firm Bunq. Dave claims that its DaveGPT, created with generative AI company Aisera, provides an 89% resolution rate, higher than its previous chatbot iterations. In addition, the conversational features of GAI create a more natural and engaging customer experience. By tracking conversations and remembering previous client interactions, GAI may be able to anticipate future needs and proactively offer additional information or resources.

Further, there is potential for GAI assistants to mitigate accessibility barriers by, for example, providing multilingual support through verified translations or by enabling sophisticated audio-supported messages and functions for visually impaired users.

Fraud Detection and Prevention

While the use of AI in fraud detection and prevention is not entirely new, as innovative technologies continue to take shape, so too do potential scams and schemes. Fraudsters could create more elaborate and potent ways to deceive both businesses and consumers that appear real. To combat this, highly advanced algorithms powered by AI could analyze vast datasets in real-time without affecting the customer’s experience. In addition, these models could use synthetic datasets to play out a vast number of scenarios to defend against potential fraud risks and test security interventions.

As with all things AI, survey respondents had mixed feelings about using AI to analyze their behavior to prevent fraud: 42% said they would be comfortable, 37% would be uncomfortable, and 21% would be neither. Firms need to ensure that they communicate clearly about how they use AI to assuage customer doubts about the new technology.


Personalized Financial Shopping & Planning

Customers want to feel like they matter to the institutions that they connect with, particularly as digital interactions continue to dominate many aspects of day-to-day life. Personalization matters, driving repeat engagement and, in turn, customer loyalty. In fact, according to recent data from McKinsey, 71% of consumers expect companies to deliver personalized interactions and 76% get frustrated it is not delivered. While many firms respect that customers like to see their own name and offer a personalized greeting upon logging into the authenticated site, generative AI could provide more elaborate content. Beyond just greeting clients, it could contribute to entirely unique interfaces tailored to clients’ specific profiles and individual needs.

Our recent survey revealed that, across generations, approximately one-third of respondents were equally concerned and excited about generative AI analyzing their financial behavior (i.e., spending habits and credit use) to receive customized and/or personalized product offerings; however, 58% of Boomer respondents reported that they were more concerned than excited about this prospect.

A chart showing generational gaps when it comes to excitement about Gen AI personalization

When considering how to safely and effectively integrate generative AI into a range of features within the financial sector, there are naturally issues that firms must take into consideration. These include training and development costs, issues surrounding biases and discrimination, regulatory concerns, concerns with data privacy, a lack of transparency regarding AI-powered decision-making, and potential security vulnerabilities. As the future of generative AI continues to evolve, the landscape of financial services will likely undergo unparalleled changes that, hopefully, benefit institutions and consumers alike.

Check out our Insights section for more on the latest trends across the financial services and healthcare industries. And contact us to learn more on our upcoming research using the survey data in this post.

Larissa Burka

Larissa Burka is an Analyst on CI's Bank and Credit Card team.