Financial regulations rely on regulator-controlled models to generate probabilistic forecasts which determine firm constraints. I refer to these forecasts as regulator model-implied beliefs. Using the U.S. life insurance sector as a laboratory, I measure both regulator model-implied and insurer expectations. I show that the regulator model disagrees with insurers yet quantitatively mirrors the systematic belief patterns observed in human forecasters, embedding these patterns into regulatory constraints. Insurers, in turn, pass through these belief dynamics into their portfolio decisions, effectively coordinating behavior at the sector level. This mechanism reveals a new channel linking well-documented belief dynamics to financial intermediary decisions.
