Our current and future uses of Artificial Intelligence (AI) and other emerging technologies may create additional risks.
Sees AI as a riskDetail: GeneralNew this year
Similar wording appears in 4 other banks' reports.
WA · Mid-size bank ($1B to $50B)
Total assets of FDIC-insured bank subsidiaries: $1.4B at the end of 2024
Filings on the SEC website · This bank on Bankgraph
| Report year | Using or planning AI | Explains how AI is controlled | Sees AI as a risk | Other mentions |
|---|---|---|---|---|
| 2022 | ||||
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| 2024 |
| In the 2024 report | This bank | Banks of its size |
|---|---|---|
| Using AI now | No | 10 of 230 (4%) |
| Explains how AI is controlled | Yes | 21 of 230 (9%) |
| Sees AI as a risk | Yes | 144 of 230 (63%) |
| Mentions generative AI | No | 70 of 230 (30%) |
| Mentions AI agents | No | 0 of 230 (0%) |
4 passages new in the 2024 report, 0 passages from the 2023 report no longer there. The most specific passage is more detailed than last year.
Our current and future uses of Artificial Intelligence (AI) and other emerging technologies may create additional risks.
Similar wording appears in 4 other banks' reports.
The increasing adoption of AI in financial services presents significant opportunities but also introduces a range of risks that could impact our operations, regulatory compliance, and customer trust. AI introduces model risk, where flawed algorithms or biased data could result in inaccurate credit decisions, compliance violations, or discriminatory outcomes in lending or customer service. Cybersecurity threats, such as data breaches, adversarial attacks, and data poisoning, pose significant challenges, particularly as these systems handle large volumes of sensitive customer information. Additionally, the opaque nature of some AI models, often referred to as "black-box" systems, raises regulatory compliance concerns, as regulators increasingly require transparency and explainability in AI-driven decision-making.
Operational risks also arise from potential system failures, over-reliance on AI, and integration challenges with existing infrastructure. Disruptions in AI systems could impact critical functions such as fraud detection, transaction monitoring, and customer support. Ethical and reputational risks, including unintended consequences or perceived unfairness in AI-driven decisions, may erode customer trust and expose us to regulatory scrutiny.
Mitigate these risks requires a robust governance framework, regularly testing and auditing of AI models, and strong human oversight. Investments in cybersecurity, data privacy protections, and employee training are critical to managing these risks.
Similar wording appears in 4 other banks' reports.