Artificial intelligence (AI) continues to make its way into every industry, and banking is no exception. Recognizing this, the Office of the Comptroller of the Currency (OCC) has highlighted the importance of modernizing operations and enhancing customer experience through digital banking solutions for community banks.
AI brings promise, but it also introduces new and complex risks that must be properly addressed to protect data, ensure stakeholder and customer trust, and maintain compliance and integrity. So, as community banks look to adopt AI to enhance operational efficiency, improve customer engagement and streamline compliance activities, the importance of proactively managing risk and having the proper personnel in place to manage these risks cannot be overstated.
How Are Community Banks Using AI?
Community banks are using AI to streamline customer interaction and automate document processing. Additionally, they can leverage AI to enhance fraud detection and loan approval workflows. With strategic implementation, community bank employees can redirect their focus to high-level tasks such as building stronger customer relationships.
Why Community Bank AI Systems Face a Unique Challenge
Unlike large financial institutions, community banks often lack specialized personnel, in-house security functions, and the budget required to build and sustain a dedicated IT, cybersecurity or AI governance team. This resource gap can leave their AI system vulnerable to attacks and other unintended consequences of AI adoption, potentially compromising sensitive data and undermining trust in AI technologies.
Without adequate expertise, organizations may also struggle to implement thorough risk assessments and robust security measures to protect AI systems from cyber threats, particularly as they seek to keep pace with evolving fintech trends and rising consumer expectations.
Effective AI systems also require high-quality data for training and operation, yet talent shortages in data science and data engineering can significantly hinder an organization's ability to manage and preprocess this data effectively.
AI Governance for Banking: Mitigating Risk Through Data and Oversight
Generative AI and large language models (LLMs), in particular, can expose institutions to data leaks, manipulation and adversarial threats, often with limited transparency.
Effective governance begins with data, and AI is only as powerful — and safe — as the data it consumes. Without strong data stewardship and lifecycle management, banks risk feeding low-quality or improperly governed data into AI systems, which can lead to biased outputs, decision errors and compliance failures. A robust data governance banking strategy should define data ownership, maintain integrity across systems and align usage policies with regulatory expectations.
In parallel, risk assessments must be refined to identify, evaluate and mitigate potential threats across AI systems. A framework for managing generative AI cybersecurity risks highlights the importance of:
- Defining acceptable use policies
- Aligning risk assessments with business priorities
- Adopting a layered defense strategy
These principles are especially critical in banking, where regulatory scrutiny, fiduciary responsibility and customer trust converge. By anchoring AI governance in both data and risk oversight, community banks can better manage emerging threats and achieve more reliable and compliant outcomes.
Benefits of a vCISO for Community Banks
To help address resourcing challenges and establish AI governance, many community banks are turning to virtual chief information security officers (vCISOs). A vCISO provides executive-level banking cybersecurity and risk leadership on a fractional or as-needed basis, delivering the same strategic value as an in-house CISO but at a lower cost and with scalable flexibility.
A vCISO model helps financial institutions establish and mature AI governance programs by:
- Creating risk-aligned AI and cybersecurity frameworks
- Developing data governance policies tied to AI use
- Conducting gap assessments and regulatory risk analyses
- Enhancing incident response capabilities related to AI misuse
- Educating executives and boards on AI risk and oversight
How We Can Help Banks With AI Readiness
At Cherry Bekaert, our Cybersecurity practice works in tandem with our Financial Institutions industry team to help community banks embed data governance and cybersecurity into every phase of the AI lifecycle from ideation and implementation to oversight, risk management and optimization. Leveraging deep industry experience and relationships, our integrated approach enables banks to move confidently, balance innovation with control and unlock AI’s potential while safeguarding institutional trust.
Our combined teams are ready to assist you and your bank in exploring AI or managing the associated risks. Learn more about our approach to crafting a generative AI strategy to manage cybersecurity risks and how we can tailor a vCISO solution to your institution’s needs.
