CNOB, CNOBP · NJ · Mid-size bank ($1B to $50B)
Total assets of FDIC-insured bank subsidiaries: $14B at the end of 2025
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 |
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| In the 2025 report | This bank | Banks of its size |
|---|---|---|
| Using AI now | Yes | 26 of 221 (12%) |
| Explains how AI is controlled | Yes | 55 of 221 (25%) |
| Sees AI as a risk | Yes | 184 of 221 (83%) |
| Mentions generative AI | Yes | 112 of 221 (51%) |
| Mentions AI agents | No | 18 of 221 (8%) |
6 passages new in the 2025 report, 0 passages from the 2024 report no longer there. The most specific passage is more detailed than last year.
Mr. Sorrentino added, “As one of the most efficient banks in the country, we remain committed to further enhancing our operating performance by driving productivity gains through technological innovation, including agentic workflows.”
"Expenses remain well-controlled as we continue to leverage merger synergies and drive additional productivity gains through increasing use of AI workflow across the organization." Mr. Sorrentino added, "During the first quarter, our strong retained earnings supported loan growth, share repurchases, and a 1.7% increase in tangible book value per share; we are now approximately one quarter away from returning to our pre-merger tangible book value per share of $24.16."
The development and use of artificial intelligence (“AI”) present risks and challenges that may adversely impact our business.
We have begun and intend to continue to selectively incorporate AI technology in certain business processes, fraud detections, services or products, including technologies that process sensitive financial and/or personal data. We have also selectively employed AI technologies to assist in drafting standardized documents and communications, and to search information on the internet. Furthermore, our third-party vendors, clients or counterparties may develop or incorporate AI technology into their business processes, services or products.
The development and use of AI present a number of risks and challenges to our business. The legal and regulatory environment relating to AI is uncertain and rapidly evolving at both the state and federal level, and includes regulation targeted specifically at AI as well as provisions in intellectual property, privacy, consumer protection, employment and other laws applicable to the use of AI. These evolving laws and regulations could require changes in our implementation of AI technology and increase our compliance costs and the risk of non-compliance, including in relation to data privacy and security requirements under laws such as the Gramm-Leach-Bliley-Act (“GLBA”), which mandates the protection of consumer financial information.
AI models, particularly generative AI models, may produce output or decisions or take action that is incorrect, that results in the release of private, confidential or proprietary information, that reflects biases included in the data on which they are trained or that are inherent in their algorithms, that produces output that is, or is perceived to be, discriminatory or unfair, that infringes on the intellectual property rights of others, or that is otherwise harmful.
While we have policies and governance structures prohibiting our employees from using non-approved generative AI applications or websites on the Company or the Bank’s network or devices, there can be no assurances that our employees will adhere to these policies or that such policies and governance structures will be effective in mitigating the risks associated with using AI technology.
Since personally identifiable or nonpublic information may be used with AI applications, there is a risk that these technologies generate output that improperly discloses such personally identifiable or nonpublic information. The use of personally identifiable or nonpublic information could result in a violation of certain laws, including data privacy laws and the data privacy and security requirements of the GLBA, exposing us to legal liability or regulatory penalties. In addition, the complexity of many AI models makes it challenging to understand why they are generating particular outputs. This limited transparency increases the challenges associated with assessing the proper operation of AI models, understanding and monitoring the capabilities of the AI models, ensuring adherence to our privacy policies, reducing erroneous output, eliminating bias and discrimination and complying with regulations that require documentation or explanation of the basis on which decisions are made. Further, we may rely on AI models developed by third parties, and, to that extent, would be dependent in part on the manner in which those third parties develop and train their models, including risks arising from the inclusion of any unauthorized material in the training data for their models, and the effectiveness of the steps these third parties have taken to limit the risks associated with the output of their models, matters over which we may have limited visibility.
● Artificial Intelligence;
● Artificial Intelligence;
● Artificial Intelligence;
● Artificial Intelligence;