With the emergence of generative AI over the past 18 months, adding a new perspective to the financial landscape, financial institutions are unknowingly using AI in their daily lives. From fraud detection systems to customer service chatbots, AI-powered tools are quietly optimizing and strengthening our operations. Misconceptions about its use underscore an urgent need to update policies to accurately reflect the pervasiveness of AI in institutions’ operational frameworks.
While AI is not a new phenomenon and has long supported industries such as cybersecurity and fraud prevention, generative AI represents a recent advancement, using sophisticated algorithms to generate unique content, make decisions, and revolutionize customer interactions. While this advancement holds great promise, it also presents a variety of opportunities and challenges.
Improving efficiency while mitigating risks
It is essential to understand the dual nature of AI: it functions as an internal asset while also representing external threats. Internally, AI streamlines processes, reduces costs, and improves customer experience. Externally, vigilance is essential against AI-generated threats such as complex phishing schemes or deepfake technologies aimed at manipulating information or stealing identities.
As we integrate these technologies into systems, a balanced perspective on risk is essential to protect operations and members. It is important to ask: How can we (institutions) embark on this journey? How can AI be integrated wisely and effectively into existing business frameworks?
Practical Steps to Integrate AI into Operations
1. Conduct an AI risk assessment: As with anything in financial services, start with a comprehensive risk assessment to understand both the internal benefits and external threats of AI. This assessment will guide your AI strategies and security measures, helping you identify potential vulnerabilities and opportunities.
2. Update and improve policies: Ensure your institution’s policies accurately reflect the AI technologies already in use. Clear, up-to-date policies are essential to ensuring compliance and creating a solid foundation for further AI integration.
3. Form your team: It’s critical that leaders and operational staff understand the nuances and applications of AI. This knowledge is key to harnessing its benefits and mitigating its risks. Ongoing training and workshops can help fill knowledge gaps and ensure everyone is aligned with AI best practices. And while you may suspect otherwise, someone could be using ChatGPT from their smartphone with your sensitive information.
4. Develop a Generative AI Blueprint: Start by exploring less critical applications to discover the potential of generative AI. This experimentation can include areas such as member interactions or internal automation. Starting with small, manageable projects allows you to assess the impact of AI before scaling it up.
5. Foster a culture of innovation: Foster a culture that fosters innovation and encourages employees 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 safe experimentation and learning.
6. Collaborate with AI experts: Partner with trusted third parties who excel in AI to provide you with expert knowledge and guidance. These partnerships can help you navigate the complexities of AI and implement best practices that are tailored to your institution’s needs.
7. Monitor AI applications: Regularly monitor 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 the intended benefits and allows for timely adjustments.
8. Adapt constantly: AI is a rapidly evolving field. Stay up-to-date with developments and regulatory changes to continually refine your approach and policies. Regular reviews and updates of your AI strategy will ensure its effectiveness and compliance.
As you implement AI into your institution’s operations, there are tools available to help. AI risk assessment tools provide a foundational template designed to help you assess the risks and benefits of AI in your operations. A generative AI policy blueprint can kick off your generative AI initiatives responsibly by providing a foundational document to get started.
In the digital age, the adoption of AI as a transformative force in the fintech industry allows us to continue to move forward with innovation and integrity. With the right preparation, tailored to your institution’s operations, you can meet the opportunities and challenges that lie ahead.
Beth Sumner
Beth Sumner is vice president of customer success at Finosec, an Alpharetta, Georgia-based cybersecurity company serving financial institutions.
