How finance teams can safely deploy AI-built applications

Finance teams at banks and large financial institutions are increasingly turning to AI coding assistants like ChatGPT, Claude, and Cursor to develop internal applications rapidly, often surpassing traditional IT processes. These AI-built applications are designed to meet specific needs such as custom reporting and reconciliation, which are often neglected by engineering teams due to other priorities. However, the rapid deployment of these tools raises significant risks, including unscoped data access, hardcoded credentials, and a lack of segregation-of-duties reviews, which are crucial when handling sensitive financial and customer data. To mitigate these risks, a structured deployment process is essential, involving data access scoping, sandbox testing, and thorough review steps involving IT, security, and internal audit teams. Platforms like Northflank provide infrastructure controls such as sandboxed environments, role-based access control, and audit logs to support the secure deployment of these applications. This approach helps ensure that AI-built finance applications adhere to necessary compliance and security measures, while allowing finance teams to innovate quickly without bypassing critical controls.

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