Auditing Asset-Specific Preferences in Financial Large Language Models: Evidence from Bitcoin Representations and Portfolio Allocation
Do AI financial advisors secretly favor certain assets like Bitcoin?
Researchers found that large language models powering robo-advisors and trading bots do carry built-in preferences for specific assets, including Bitcoin. They identified a single internal feature in one AI model that, when amplified, increased Bitcoin's allocation in a simulated portfolio by 5.2 percentage points—even when the word "Bitcoin" wasn't mentioned. This preference shifted depending on context: the models ranked Bitcoin much higher as "reliable money" during crises than during normal times.
As AI systems begin making real financial decisions for investors, hidden asset preferences could steer people toward or away from particular investments without their knowledge. This work provides the first method to detect and measure these internal biases, laying groundwork for new transparency standards that would require financial AI systems to disclose what they actually prefer—similar to how banks must know their customers, AI advisors should be audited to know their own assets.