Forbright, Inc.FRBT

Technological advances including generative and agentic AI may impact Forbright's business.

“Technological advances, including the development and implementation of generative and agentic AI and other AIML technologies, may impact our business and our ability to successfully adopt and implement new technologies that our customers desire.”

Agentic and generative AI present risks including incorrect output, bias, IP infringement and privacy violations.

“The emergence of agentic and generative AI in particular presents unique risks and challenges that may adversely impact our business, including the production of output or taking of action that is incorrect. We or our third-party vendors or counterparties may develop or utilize such AIML in certain business processes, services, or products. Particularly agentic or generative AI models, may produce output or take action that is incorrect, that reflect biases included in the data on which they are trained, or that is otherwise harmful, which would likely degrade the effectiveness of such AI and could adversely impact us to the extent that we, our affiliates and our service providers or other third parties engaged by us rely on the work product of such AI. Use of AIML models may also infringe on the intellectual property rights of others or otherwise be affected by claims of infringement, misappropriation or other violations of intellectual property, including based on the use of large datasets used to train AI or the use of output generated by AI, in either case which contain or are substantially similar to material protected by intellectual property, including patents, copyrights, trademarks, or trade secrets. Furthermore, the use of personal or nonpublic information in connection with agentic or generative AI by the Company could result in a violation of certain laws, including data privacy laws and the data privacy and security requirements of the Gramm-Leach-Bliley Act of 1”

Forbright anticipates AI agents maximizing deposit yields will disrupt banking.

“We believe AI will accelerate this shift by lowering the cost and raising the quality of deposit-gathering and the disruption is about to intensify as AI agents that maximize deposit yields for consumers gain widespread adoption. JPMorgan's "Smart Cash," for instance, automatically sweeps idle balances into higher-yielding accounts. As these agents proliferate, they strip away the inertia that lets branch banks hold large balances in low- or no-interest accounts. Money will move fluidly to whoever offers a fair rate through the cleanest digital rails - a clear advantage for digitally native banks like Forbright.”

Forbright uses a proprietary chat-style AI agent to monitor pricing and perform real-time tracking.

“We currently use AIML tools to better personalize customer interactions and scale operational agility. For example, we use large language models to process and report on our semantic text datasets (customer segmentation, call center transcripts and others). We believe that leveraging AIML tools to summarize large data into actionable insights, such as bespoke customer sentiment scores and trend tracking, allows us to better predict churn rate, analyze deposit opportunities, and suggest appropriate customer responses. Our proprietary chat-style AI agent, which integrates into our data layer, monitors peer bank pricing strategies and performs real-time tracking, is designed to enable us to run analytics and access trend data without any technical skills, thus increasing data-driven decision making without the need for additional resources. We also use AI-driven marketing tools to analyze landing pages, support creation of ad assets and extensions, and identify relevant search queries to strengthen our marketing funnel.”

Technological advances in generative and agentic AI may impact the business and adoption of new customer-desired technologies.

“Technological advances, including the development and implementation of generative and agentic AI and other AIML technologies, may impact our business and our ability to successfully adopt and implement new technologies that our customers desire.”

Agentic and generative AI present risks including incorrect biased or harmful output and potential IP or privacy violations.

“The emergence of agentic and generative AI in particular presents unique risks and challenges that may adversely impact our business, including the production of output or taking of action that is incorrect. We or our third-party vendors or counterparties may develop or utilize such AIML in certain business processes, services, or products. Particularly agentic or generative AI models, may produce output or take action that is incorrect, that reflect biases included in the data on which they are trained, or that is otherwise harmful, which would likely degrade the effectiveness of such AI and could adversely impact us to the extent that we, our affiliates and our service providers or other third parties engaged by us rely on the work product of such AI. Use of AIML models may also infringe on the intellectual property rights of others or otherwise be affected by claims of infringement, misappropriation or other violations of intellectual property, including based on the use of large datasets used to”

Use of agentic or generative AI could violate data privacy laws including GLBA exposing the company to liability.

“train AI or the use of output generated by AI, in either case which contain or are substantially similar to material protected by intellectual property, including patents, copyrights, trademarks, or trade secrets. Furthermore, the use of personal or nonpublic information in connection with agentic or generative AI by the Company 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.”

Forbright uses AIML tools, LLMs, a proprietary chat-style AI agent, and AI-driven marketing tools.

“We currently use AIML tools to better personalize customer interactions and scale operational agility. For example, we use large language models to process and report on our semantic text datasets (customer segmentation, call center transcripts and others). We believe that leveraging AIML tools to summarize large data into actionable insights, such as bespoke customer sentiment scores and trend tracking, allows us to better predict churn rate, analyze deposit opportunities, and suggest appropriate customer responses. Our proprietary chat-style AI agent, which integrates into our data layer, monitors peer bank pricing strategies and performs real-time tracking, is designed to enable us to run analytics and access trend data without any technical skills, thus increasing data-driven decision making without the need for additional resources. We also use AI-driven marketing tools to analyze landing pages, support creation of ad assets and extensions, and identify relevant search queries to strengthen our marketing funnel.”

Technological advances in generative and agentic AI may impact Forbright's business.

“Technological advances, including the development and implementation of generative and agentic AI and other AIML technologies, may impact our business and our ability to successfully adopt and implement new technologies that our customers desire.”

Agentic and generative AI present risks of incorrect output, bias, IP infringement, and legal violations for Forbright.

“The emergence of agentic and generative AI in particular presents unique risks and challenges that may adversely impact our business, including the production of output or taking of action that is incorrect. We or our third-party vendors or counterparties may develop or utilize such AIML in certain business processes, services, or products. Particularly agentic or generative AI models, may produce output or take action that is incorrect, that reflect biases included in the data on which they are trained, or that is otherwise harmful, which would likely degrade the effectiveness of such AI and could adversely impact us to the extent that we, our affiliates and our service providers or other third parties engaged by us rely on the work product of such AI. Use of AIML models may also infringe on the intellectual property rights of others or otherwise be affected by claims of infringement, misappropriation or other violations of intellectual property, including based on the use of large datasets used to”

Agentic and generative AI present risks of incorrect output, bias, IP infringement, and legal violations for Forbright.

“train AI or the use of output generated by AI, in either case which contain or are substantially similar to material protected by intellectual property, including patents, copyrights, trademarks, or trade secrets. Furthermore, the use of personal or nonpublic information in connection with agentic or generative AI by the Company 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.”

Forbright uses a proprietary chat-style AI agent to monitor peer bank pricing and run analytics.

“We currently use AIML tools to better personalize customer interactions and scale operational agility. For example, we use large language models to process and report on our semantic text datasets (customer segmentation, call center transcripts and others). We believe that leveraging AIML tools to summarize large data into actionable insights, such as bespoke customer sentiment scores and trend tracking, allows us to better predict churn rate, analyze deposit opportunities, and suggest appropriate customer responses. Our proprietary chat-style AI agent, which integrates into our data layer, monitors peer bank pricing strategies and performs real-time tracking, is designed to enable us to run analytics and access trend data without any technical skills, thus increasing data-driven decision making without the need for additional resources. We also use AI-driven marketing tools to analyze landing pages, support creation of ad assets and extensions, and identify relevant search queries to strengthen our marketing funnel.”

Forbright cites risk that generative and agentic AI advances may impact its business.

“Technological advances, including the development and implementation of generative and agentic AI and other AIML technologies, may impact our business and our ability to successfully adopt and implement new technologies that our customers desire.”

Forbright lists risks of incorrect, biased or infringing output from agentic and generative AI.

“The emergence of agentic and generative AI in particular presents unique risks and challenges that may adversely impact our business, including the production of output or taking of action that is incorrect. We or our third-party vendors or counterparties may develop or utilize such AIML in certain business processes, services, or products. Particularly agentic or generative AI models, may produce output or take action that is incorrect, that reflect biases included in the data on which they are trained, or that is otherwise harmful, which would likely degrade the effectiveness of such AI and could adversely impact us to the extent that we, our affiliates and our service providers or other third parties engaged by us rely on the work product of such AI. Use of AIML models may also infringe on the intellectual property rights of others or otherwise be affected by claims of infringement, misappropriation or other violations of intellectual property, including based on the use of large datasets used to”

Forbright warns that using personal data with agentic AI could violate privacy laws including GLBA.

“train AI or the use of output generated by AI, in either case which contain or are substantially similar to material protected by intellectual property, including patents, copyrights, trademarks, or trade secrets. Furthermore, the use of personal or nonpublic information in connection with agentic or generative AI by the Company 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.”