By Victoria Ruojie Li
AI agents built on different language models can still share the software that presents their choices. We study one shared component, the order in which a borrowing agent's actions are listed, in a simulated collateralized lending market populated by three open-weight model families. In fixed decision states, moving the borrowing action from last to first raises valid borrowing requests by 27 percentage points. In 12 matched pairs of 15-agent markets, all agents in one market see the same order; the other spreads the six possible orders across agents. A common order moves whole markets: the four markets that listed borrowing first raised net debt by 1.8 to 2.7 times their initial unused borrowing capacity, while those that listed debt reduction first cut debt. These groups account for 96 percent of the sample variation among common markets, whose standard deviation is three times the balanced one. The borrowing cap stops 40 percent of valid borrowing requests made when borrowing is listed first, but it values collateral at the pool price, so correlated purchases raise borrowing capacity and leave positions above 70 percent of reference value. Under a 30 percent shock, an 8 percent liquidation bonus produces write-offs on loans that are fully collateralized before liquidation, and liquidation triggers that read the pool price add exposure. Common ordering does not put more borrowers into the write-off zone; it concentrates them in the markets whose shared order favored borrowing. Collateral valuation and liquidation rules determine how much of it creditors fail to recover.
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