LLMs used in financial applications contain identifiable internal features that causally influence asset preferences and portfolio decisions—a critical finding for auditing AI financial agents and developing transparency standards.
This paper audits whether large language models have built-in biases toward specific financial assets, using Bitcoin as a case study.