Why AI Financial Agents Need Forensic Traceability Beyond Basic Logging

When an AI agent executes a financial decision, standard logs of prompts and API calls often fail to capture the full context of what the agent actually knew at the time. Forensic traceability goes further by reconstructing the evidence, authorization state, policy versions, tool interactions, and risk evaluations that surrounded the original decision. A key architectural recommendation is assigning a durable decision ID to each consequential workflow, distinct from a trace ID, so evidence across multiple systems and retries can be linked to one logical business action. Immutable references to retrieved documents, policy versions, and account states — including content hashes and timestamps — help distinguish what existed at decision time from what exists today. This level of traceability is especially critical in financial systems, where post-incident investigations may require a precise replay of the information and controls that participated in a given action.