AI, or artificial intelligence, is driving a major transformation across financial institutions, especially in community banking. This technology uses machine learning to enable machines to make decisions based on recognized patterns, minimizing the need for human involvement. While AI's presence in banking isn't brand new, its applications continue to grow rapidly, shifting from defensive solutions like spam filters to customer service innovations.
Financial institutions view AI with a mix of enthusiasm and caution, exploring its potential while managing associated risks. Understanding how AI currently supports community banks and its future applications provides valuable insight into how these institutions can effectively implement AI. We recently spoke with Scott Stevens, Chief Information Security Officer at Integrity Technology Solutions, to learn more about how community banks are effectively using AI. Here is what he shared.
AI's Current Impact on Community Banking
AI already plays a significant role in several key areas within financial institutions. One familiar application is spam filtering, which has been in use for nearly a decade. These filters analyze email patterns, adapt to new types of spam, and automatically block unwanted messages. Community banks also benefit from next-generation antivirus software, with tools like SentinelOne, Carbon Black, and CrowdStrike offering advanced security.
These antivirus programs fall under Endpoint Detection and Response (EDR), which continuously monitors activities, detects anomalies, and decides if something appears suspicious or legitimate. Community banks increasingly rely on AI-driven EDR tools to provide a real-time response to potential threats, bolstering their digital defenses against evolving cybersecurity risks.
Expanding AI’s Role in Customer Service and Operations
Community banking leaders are now exploring AI applications beyond security. Many banks use AI to handle repetitive tasks with accuracy, such as answering initial customer service inquiries. Some institutions consider AI-based auto attendants, which could streamline customer interactions, though these solutions are still emerging.
Generative AI capabilities also present intriguing opportunities for community banking. By providing faster access to loan information or helping with vendor management programs, AI can improve the customer experience. Generative AI efficiently processes data, offering insights to guide decisions, which could streamline customer interactions and make services more responsive. However, community banks must balance these efficiencies with the goal of maintaining a personal connection with clients.
Addressing AI's Security and Privacy Challenges
AI offers many advantages but presents unique security and privacy challenges that community banks must address. One significant risk is data leakage, where sensitive information might inadvertently become accessible. Community banks must actively manage vendor relationships and ensure their data remains secure within defined boundaries.
AI’s ability to analyze large data sets can also inadvertently expose sensitive information. For instance, asking an AI system about an employee’s salary could yield unintended results if that information is accessible within the organization. Thus, community banks must strictly control data permissions and restrict access to authorized personnel only.
Another risk is AI "hallucinations," or incorrect and fabricated responses generated in the absence of sufficient information. Community banks should have strong oversight mechanisms to ensure AI outputs remain accurate, especially for customer-facing and internal purposes.
Preparing for AI Implementation in Community Banking
Implementing AI successfully in community banking requires a collaborative, well-planned approach. Experts advise community banks to establish a cross-functional committee with representatives from departments like marketing, HR, and IT. This committee can help map out the benefits and address potential concerns before fully implementing AI solutions.
Setting up a dedicated AI committee enables community banks to create clear policies and set expectations for AI use. By gathering diverse input, community banks can ensure AI aligns with their unique needs and values. Additionally, establishing ground rules and involving employees from various departments builds a solid foundation for ethical, responsible AI adoption.
Steps for Community Banks to Adopt AI Responsibly
For community banks considering AI, a measured approach is advisable. Testing AI solutions on a small scale—such as in marketing or content generation—allows institutions to assess AI’s impact and refine usage policies. With each step, banks can evaluate how AI fits best into their operations.
Some banks, for example, use tools like Microsoft’s Co-Pilot for AI-based content creation and document management. However, implementing Co-Pilot effectively requires data storage on Microsoft’s secure cloud platforms, like SharePoint or OneDrive. Regulatory agencies support these cloud solutions, provided they include robust security controls.
By gradually integrating AI, community banks can address data security and privacy concerns with each new step. Policy updates, staff training, and readiness assessments ensure that AI supports the bank’s objectives without compromising client trust.
Shaping the Future of Community Banking with AI
AI will shape the future of community banking, bringing transformative benefits and new challenges. Tools like EDR systems, auto attendants, and cloud-based solutions like Microsoft Co-Pilot offer community banks enhanced security, improved customer service, and operational efficiency. Implementing AI responsibly requires clear policies, a structured approach, and a commitment to managing security and privacy risks.
Are you looking to help your community bank succeed? Talk to us at Midwestern Securities today. See how an independent broker-dealer can help you grow.