Maximizing AI Impact: A Guide for Community Financial Institutions

With the emergence of generative AI in the past 18 months adding a fresh perspective to the financial landscape, financial institutions unknowingly leverage AI daily without realizing it. From fraud detection systems to customer service chatbots, AI-powered tools quietly optimize and strengthen our operations. Misperceptions around its usage underscore an urgent necessity: Updating policies to accurately reflect AI’s omnipresence in the operational framework of institutions.

While AI isn’t a new phenomenon and has long supported sectors like cybersecurity and fraud prevention, generative AI represents a recent breakthrough, utilizing sophisticated algorithms to generate unique content, make decisions and revolutionize customer interactions. While this advancement holds great promise, it also introduces various opportunities and challenges.

Enhancing Efficiency While Mitigating Risk

Understanding AI’s dual nature is vital: It functions as an internal asset while posing external threats. Internally, AI streamlines processes, reduces costs and improves customer experiences. Externally, vigilance is essential against AI-driven threats such as complex phishing schemes or deepfake technologies aimed at manipulating information or identity theft.

As we integrate these technologies into systems, a balanced perspective on the risks is crucial for safeguarding operations and members. It’s important to ask: How do we (institutions) embark on this journey? How can AI be wisely and effectively integrated into existing business frameworks?

Practical Steps to Embedding AI into Operations

1. Conduct an AI risk assessment: Just like everything else in financial services, begin with a comprehensive risk assessment to understand both the internal benefits and external threats of AI. This evaluation will guide your AI strategies and security measures, helping to identify potential vulnerabilities and opportunities.

2. Update and improve policies: Ensure that your institution’s policies accurately reflect the AI technologies already in use. Clear and updated policies are essential for compliance and creating a strong foundation for further AI integration.

3. Educate your team: It’s vital that both leadership and operational staff understand AI’s nuances and applications. This knowledge is crucial for harnessing its benefits and mitigating its risks. Ongoing training and workshops can help bridge knowledge gaps and ensure everyone is aligned on AI best practices. And even if you suspect otherwise, someone might just be leveraging ChatGPT from their smartphone with your sensitive information.

4. Develop a generative AI blueprint: Begin by exploring less critical applications to discover generative AI’s potential. This experimentation could include areas such as member interactions or internal automation. Starting with small, manageable projects allows you to evaluate AI’s impact before expanding.

5. Foster a culture of innovation: Encourage a culture where innovation is embraced, and employees are motivated to explore new AI applications safely. Ensure that all experimentation is conducted without using sensitive information. You can drive AI adoption more effectively by supporting an environment that values secure experimentation and learning.

6. Collaborate with AI experts: Work with trusted third parties who excel in AI to provide specialized knowledge and guidance. These partnerships can help you navigate the complexities of AI and implement best practices tailored to your institution’s needs.

7. Monitor AI applications: Regularly check the performance and impact of AI applications. Establish metrics and key performance indicators (KPIs) to measure success and areas for improvement. Continuous monitoring ensures that AI tools are delivering expected benefits and allows for timely adjustments.

8. Adapt continually: AI is a rapidly evolving field. Stay up to date on advancements and regulatory changes to continually refine your approach and policies. Regular reviews and updates to your AI strategy will ensure it remains effective and compliant.

As you implement AI into your institution’s operations, there are tools out there to assist you. AI risk assessment tools provide a foundational template designed to aid in evaluating the risks and rewards of AI within your operations. A generative AI policy blueprint can kickstart your generative AI initiatives responsibly by providing a fundamental document to start.

In this digital era, embracing AI as a transformative force in the financial technology industry ensures we continue to move forward with innovation and integrity. With proper preparation that aligns with your institution’s operations, you can address the opportunities and challenges that lie ahead.

Beth Sumner is Vice President, Customer Success at the Alpharetta, Ga.-based Finosec, a cybersecurity firm serving financial institutions.