Banking Brief: Financial Services Insights

Banks of all sizes must confront the rapid integration of artificial intelligence within their institutions (and everywhere, for that matter). AI tools are already widely used, often without proper oversight, as employees and vendors use AI platforms to draft correspondence, analyze datasets, or streamline processes. Without an intentional AI policy, banks face significant legal, regulatory, and ethical risks that can bring headaches or worse.

While AI presents challenges and opportunities to all types of organizations, banks must be especially aware of the risks of unchecked AI use. A well-defined policy identifies permissible AI tools, establishes protocols for their use, enforces ethical safeguards, and ensures rigorous vetting of practices and procedures.

1. Reducing the Risk of AI in Credit Decisions

AI can rapidly analyze borrower financials and other metrics to provide almost instant input on creditworthiness. However, algorithms may profile customers based on protected characteristics, such as race, gender, or age, violating regulations like the Equal Credit Opportunity Act and the Fair Housing Act.

 Even if unintentional, discriminatory outcomes that are driven by AI can create significant risk for regulated lenders. An AI policy can mandate regular audits of algorithms to detect and correct biases, require human oversight for critical decisions, and maintain detailed compliance records. These measures help banks avoid penalties and reputational harm while meeting regulatory expectations.

2. Vetting AI Vendors

Selecting and managing AI vendors is a critical component of responsible AI adoption. Not all vendors prioritize compliance or transparency, and their tools may introduce hidden risks, such as biased algorithms or insecure data handling. Banks must thoroughly vet vendors to ensure their AI solutions align with regulatory requirements and ethical standards. This includes reviewing the vendor’s data sourcing practices, security protocols, and track record for addressing bias.

An AI policy should outline a due diligence process for vendor selection, including contractual obligations for regular audits and compliance with laws like the Gramm-Leach-Bliley Act. By holding vendors accountable, banks safeguard their operations and maintain customer trust.

3. Upholding Ethical Standards

Ethical considerations are paramount in AI deployment. AI systems lack judgment about fairness or accountability, relying solely on provided data. Unchecked, they can produce outcomes that erode trust or conflict with a bank’s values, such as unfair customer segmentation.

A robust AI policy enforces periodic review of AI outputs, implements stringent data privacy protections, and prioritizes transparency. These safeguards ensure AI aligns with the bank’s commitment to ethical banking and fosters confidence among customers and regulators.

4. Ensuring Operational Clarity

Operational control requires visibility into AI usage. Banks must catalog all AI tools in use to assess risks and ensure compliance. Without this, unregulated tools could expose sensitive data or produce inconsistent results.

A policy specifies approved AI applications, authorized users, and usage conditions, while mandating employee training on AI’s capabilities and limitations. This structure minimizes vulnerabilities, enhances efficiency, and aligns AI with strategic goals.

5. Seizing a Competitive Advantage

The absence of an AI policy exposes banks to avoidable risks, while a proactive approach offers a competitive edge. For community banks in particular, which rely on trust and relationships, responsible AI governance reinforces both. By identifying the risks and benefits of AI, and by implementing clear guidelines now, banks can leverage AI’s benefits while mitigating pitfalls.

A forward-thinking policy signals preparedness for the technological future, enhancing market position. Although this technology is in its infancy, it will be adopted rapidly and in ways we cannot imagine. Establishing and regularly reevaluating an AI policy is critical for sustainable success.