Bank decisions without the optimizer: rules distilled from LLM agents hold annual ROE within 0.31 points across ten simulated bank-years
In a stylized euro-area bank model of deposit pricing and bond reinvestment, large language model agents play the bank and four customer types, and equation-based decision rules are estimated from their choices. On simulations not used for estimation, the final rule keeps annual ROE within 0.31 percentage points in ten Claude simulated bank-years, meeting every fit criterion in seven; the three failures all involve deposit runs. With GPT-5.5 the gap stays within 0.71 points, but only six of eighteen simulated bank-years meet all criteria.