Eagle Bancorp Inc

Operational risk is inherent in our business. We rely on business processes and branch activity that largely depend on people and technology, including access to information technology systems as well as information, applications, payment systems and other services provided by third parties. Operational risks that may have an adverse effect on our operations, include (i) risks related to our work productivity; (ii) increased spending on our business continuity efforts; (iii) increased strain on certain risk management practices, including, but not limited to, the effectiveness and accuracy of our models, given the potential lack of data inputs and comparable precedent; (iv) risks related to the effectiveness of our anti-money laundering and other compliance programs; (v) increased cybersecurity risk due to, among other things, the increased connectivity of third parties and electronic devices to our systems, hybrid work arrangements and new technologies, such as artificial intelligence; (vi) risks related to providing banking services through digital channels; and (vii) operational disruptions at our third-party service providers. Increased cyber risks in this context may include greater phishing, malware and other cybersecurity attacks, vulnerability to disruptions of our information technology infrastructure and telecommunications systems for remote operations, increased risk of unauthorized dissemination of confidential information, limited ability to restore the systems in the event of a systems failure or interruption, greater risk of a security breach resulting in destruction or misuse of sensitive, confidential, personal or proprietary information and potential impairment of our ability to perform critical functions, including wiring funds, all of which could expose us to risks of data or financial loss, litigation, reputational damage and liability and could seriously disrupt our operations and the operations of any impacted customers.

The financial services industry is undergoing rapid technological changes, with frequent introductions of new technology-driven products and services, including those based on artificial intelligence and blockchain technologies. The effective use of technology increases efficiency and enables financial institutions to better serve customers and reduce costs. Our future success will depend, in part, upon our ability to address the needs of customers by using technology to provide products and services that will satisfy customer demands for convenience, as well as to create additional efficiencies in our operations. Many of our competitors have substantially greater resources to invest in technological improvements. We may not be able to implement new technology-driven products and services effectively or be successful in marketing these products and services to customers. Failure to successfully keep pace with technological change affecting the financial services industry could harm our ability to compete effectively and could have a material adverse effect on our business, financial condition or results of operations. As these technologies are improved in the future, we may be required to make significant capital expenditures in order to remain competitive, which may increase our overall expenses and have a material adverse effect on our business, financial condition and results of operations.

The use of statistical and quantitative models and other quantitatively-based analyses is endemic to bank decision-making and regulatory compliance processes and the employment of such analyses is common in our operations. Liquidity stress testing, interest rate sensitivity analysis, allowance for credit loss measurement, portfolio stress testing, assessing capital adequacy and the identification of possible violations of anti-money laundering regulations are examples of areas in which we are dependent on models and the data that underlies them. We anticipate that model-derived insights will be used more widely in decision-making in the future, including as the use of artificial intelligence increases. While these quantitative techniques and approaches are intended to improve our decision-making, they also create the possibility that faulty data, flawed quantitative approaches or poorly designed or implemented models could yield adverse or faulty outcomes and decisions, and could result in regulatory scrutiny. In addition, because of the complexity inherent in these approaches, especially those based on artificial intelligence, misunderstanding or misuse of their outputs could similarly result in suboptimal decision-making, which could have a material adverse effect on our business, financial condition, results of operations and share price.

Risk to our operations is inherent in our business. We rely on business processes and branch activity that largely depend on people and technology, including access to information technology systems as well as information, applications, payment systems and other services provided by third parties. Operational risks that may have an adverse effect on our operations, include (i) risks related to our work productivity; (ii) increased spending on our business continuity efforts; (iii) increased strain on certain risk management practices, including, but not limited to, the effectiveness and accuracy of our models, given the potential lack of data inputs and comparable precedent; (iv) risks related to the effectiveness of our anti-money laundering and other compliance programs; (v) increased cybersecurity risk due to, among other things, the increased connectivity of third parties and electronic devices to our systems, hybrid work arrangements and new technologies, such as artificial intelligence; (vi) risks related to our efforts to provide banking services through digital channels; and (vii) operational disruptions at our third-party service providers. Increased cyber risks in this context may include greater phishing, malware and other cybersecurity attacks, vulnerability to disruptions of our information technology infrastructure and telecommunications systems for remote operations, increased risk of unauthorized dissemination of confidential information, limited ability to restore the systems in the event of a systems failure or interruption, greater risk of a security breach resulting in destruction or misuse of sensitive, confidential, personal or proprietary information and potential impairment of our ability to perform critical functions, including wiring funds, all of which could expose us to risks of data or financial loss, litigation and liability and could seriously disrupt our operations and the operations of any impacted customers.

The financial services industry is undergoing rapid technological changes, with frequent introductions of new technology-driven products and services, including those based on artificial intelligence technologies. The effective use of technology increases efficiency and enables financial institutions to better serve customers and reduce costs. Our future success will depend, in part, upon our ability to address the needs of customers by using technology to provide products and services that will satisfy customer demands for convenience, as well as to create additional efficiencies in our operations. Many of our competitors have substantially greater resources to invest in technological improvements. We may not be able to implement new technology-driven products and services effectively or be successful in marketing these products and services to customers. Failure to successfully keep pace with technological change affecting the financial services industry could harm our ability to compete effectively and could have a material adverse effect on our business, financial condition or results of operations. As these technologies are improved in the future, we may be required to make significant capital expenditures in order to remain competitive, which may increase our overall expenses and have a material adverse effect on our business, financial condition and results of operations.

The use of statistical and quantitative models and other quantitatively-based analyses is endemic to bank decision-making and regulatory compliance processes and the employment of such analyses is common in our operations. Liquidity stress testing, interest rate sensitivity analysis, allowance for credit loss measurement, portfolio stress testing, assessing capital adequacy and the identification of possible violations of anti-money laundering regulations are examples of areas in which we are dependent on models and the data that underlies them. We anticipate that model-derived insights will be used more widely in decision-making in the future, including as the use of artificial intelligence increases. While these quantitative techniques and approaches are intended to improve our decision-making, they also create the possibility that faulty data, flawed quantitative approaches or poorly designed or implemented models could yield adverse or faulty outcomes and decisions, and could result in regulatory scrutiny. In addition, because of the complexity inherent in these approaches, especially those based on artificial intelligence, misunderstanding or misuse of their outputs could similarly result in suboptimal decision-making, which could have a material adverse effect on our business, financial condition, results of operations and share price.