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AI for fraud detection

18 of 270 banks (7%) in their 2025 annual reports. Banks that say they use or plan AI for detecting fraud.

The banks

• Capital Bancorp Inc
  MD · Mid-size bank ($1B to $50B)

  Capital Bank uses data analytics, including AI and proprietary models, throughout the OpenSky™ customer lifecycle to support fraud prevention and credit decisioning.

  Using AI nowRead it in the report
• Princeton Bancorp, Inc.
  PA · Mid-size bank ($1B to $50B)

  These include Sophos for advanced cybersecurity threat detection and response, Verafin for fraud detection and AML compliance, the Glia Chatbot for enhancing customer service interactions, and CATO Networks for AI-driven network security and optimization.

  Using AI nowRead it in the report
• U.S. Bancorp
  MN · Large bank ($50B and above)

  The Company also uses several models that employ methodologies based on AI or machine learning, which bring unique complexities, such as the need for large datasets for training, the potential for algorithmic bias, and the need for greater explainability in interpreting model decisions.

  Sees AI as a riskRead it in the report
• Avidbank Holdings, Inc.
  CA · Mid-size bank ($1B to $50B)

  we currently use a software product with AI technology to enhance our fraud detection capabilities for our clients’ banking activity

  Using AI nowRead it in the report
• CVB Financial Corp
  CA · Mid-size bank ($1B to $50B)

  We have adopted an AI Policy that establishes a governance framework for developing, deploying, and managing AI and Generative AI (GenAI) solutions and initiatives, including those involving vendors.

  Explains how AI is controlledRead it in the report
• Capital One Financial Corp
  VA · Large bank ($50B and above)

  we use models and AI in certain processes and may expand our use of AI in additional processes in the future. Some examples may include determining the pricing of products, identifying potentially fraudulent transactions, grading loans, extending credit

  Using AI nowRead it in the report
• Charles Schwab Corp
  TX · Large bank ($50B and above)

  Schwab manages model risk, including use of artificial intelligence, through use of policies, standards, and controls which evaluate the conceptual and technical soundness of models used by the Company. Prior to the use of any artificial intelligence, we employ procedures which require

  Explains how AI is controlledRead it in the report
• Community Financial System, Inc.
  NY · Mid-size bank ($1B to $50B)

  The increase in data processing and communications expenses is reflective of the Company’s continued investment in key technologies, including artificial intelligence applications, customer payment fraud and cybersecurity risk management software

  Using AI nowRead it in the report
• ConnectOne Bancorp, Inc.
  NJ · Mid-size bank ($1B to $50B)

  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.

  Using AI nowRead it in the report
• F.N.B. Corporation
  PA · Large bank ($50B and above)

  We rely heavily on a broad range of quantitative models, advanced analytics, AI, and generative AI technologies across multiple areas of our operations, including credit decisioning, fraud detection, risk monitoring, customer engagement, productivity enhancement and internal operational processes.

  Using AI nowRead it in the report
• Finwise Bancorp
  UT · Small bank (Under $1B)

  We use generative AI for certain tasks like document drafting and data analysis, with an implementation of strict controls to protect customer data. Third-party AI assists us in cybersecurity, fraud detection, and code review, while our own agents handle compliance, policy analysis, and workflow

  Using AI nowRead it in the report
• First Busey Corp
  KS · Mid-size bank ($1B to $50B)

  The use of artificial intelligence-powered tools provide additional layers of fraud and threat detection, enabling proactive management.

  Using AI nowRead it in the report
• Juniata Valley Financial Corp
  PA · Small bank (Under $1B)

  Although the Company does not currently make significant use of artificial intelligence (“AI”), machine learning, or similar advanced data analytics technologies in its operations, the financial services industry is increasingly incorporating AI-enabled tools in areas such as credit underwriting,

  Sees AI as a riskRead it in the report
• Northern Trust Corp
  IL · Large bank ($50B and above)

  Northern Trust uses a variety of machine learning and artificial intelligence (AI) solutions to process transactional activity more efficiently and to mitigate risk. These uses currently include, among others, digitizing documents, detecting anomalous, fraudulent transactions and training services

  Using AI nowRead it in the report
• PNC Financial Services Group
  PA · Large bank ($50B and above)

  we increasingly use models related to how we do business with customers and for internal process automation that leverage AI/machine learning algorithms.

  Using AI nowRead it in the report
• Sierra Bancorp
  CA · Mid-size bank ($1B to $50B)

  the Company’s deployment of AI at this time is generally limited to fraud detection or prevention; we continue to evaluate whether to implement additional AI tools, or agentic AI, in certain limited capacities

  Using AI nowRead it in the report
• UNIVEST FINANCIAL Corp
  PA · Mid-size bank ($1B to $50B)

  We utilize certain AI/ML models provided by third-party vendors, including models used for credit scoring and fraud detection, and may use other AI/ML models in the future.

  Sees AI as a riskRead it in the report
• Union Bankshares Inc
  VT · Mid-size bank ($1B to $50B)

  We have begun piloting artificial intelligence (“AI”) and machine learning tools in certain internal and support functions, such as data analysis, fraud monitoring support, compliance processes, and operational efficiency initiatives.

  Testing or planning AIRead it in the report