Artificial Intelligence
AI is increasingly becoming a valuable tool for community banks, helping streamline operations and improve customer experience. Community banks typically have smaller budgets and fewer resources compared to larger national institutions, making AI a powerful ally in achieving efficiency. By automating repetitive tasks such as data entry, AI frees up staff to focus on higher-value, customer-focused activities.
Bankers widely understand AI and remain optimistic about its transformative potential in the industry. Those at institutions with an asset size between $1B - $5B were most likely to strongly agree about feeling optimistic about AI’s potential.
I understand what artificial intelligence is and how it can be used in banking.
I am optimistic about the potential of AI in banking.
When asked how they envision applying AI in operations, bankers are interested in applications across business units.
I would be interested in using AI for fraud and AML detection and prevention.
I would be interested in using AI for customer service.
I would be interested in using AI for sales/relationship management.
I would be interested in using AI for back-office tasks.
Nevertheless, bankers have adopted a measured approach, as about eight in 10 are very or somewhat concerned about AI’s potential in banking.
I am concerned about the potential of AI in banking.
- This is a slight increase from last year when 73% reported concern.
Industry Insight
Institutions have deployed AI-driven chatbots and other customer communications for years, leading to increased levels of automation. Like last year’s results, many respondents continue expressing measured optimism around AI, awaiting more use cases beyond these applications.
Due to AI’s growing prominence in the industry, many regulatory bodies have been investigating various risks surrounding AI. Some have issued AI guidelines, frameworks and/or requirements around how banks should use and govern AI technology to help ensure responsible practices.7 Banks should evaluate and implement AI governance recommendations to mitigate risk and establish clear guidelines for acceptable use.
Expert Perspective
It’s been nearly two years since ChatGPT emerged, and a recent industry report shows about half of banks are actively investing in exploring generative AI use cases and working to understand the capabilities and risks of this technology.8 GenAI can leverage vast amounts of unstructured data and can produce content and answers quickly. In contrast, discriminative AI is often used in more straightforward classification tasks such as spam detection, image recognition or risk prediction and mostly requires structured data (typically quantitative) to operate.
As institutions develop their GenAI strategies, it’s critical to be mindful of security. Securing your data is critical to ensure that your AI engine is not training on any confidential information and your sensitive files are protected. As referenced earlier, banks should implement AI governance and risk management frameworks to ensure compliance and data security. With thoughtful implementation, AI has the potential to benefit banks, from delivering services at scale to identifying network vulnerabilities.