Operational disruptions in retail payments can induce behavioral responses that outlast technical recovery and may amplify liquidity stress. We propose a multi-agent model linking card payment outages to trust dynamics, channel avoidance, and threshold-gated withdrawals. Customers and merchants interact through repeated payment attempts, while customers additionally influence one another on a Watts-Strogatz small-world network. Customers update bounded memory variables capturing accumulated negative experience (scar) and perceived systemic risk (rumor), with merchants contributing persistent broadcast signals that may lag operational recovery. We prove that, under mild conditions on memory persistence and threshold gating, aggregate withdrawal pressure can peak strictly after the outage nadir, including during the recovery phase. Simulations reproduce behavioral hysteresis and confirm delayed peaks of outflows. We further study payment substitution via instant transfer: substitution consistently reduces peak avoidance, yet its effect on cumulative outflows is non-monotonic under realistic merchant broadcast persistence. Robustness experiments across random seeds show stable qualitative behavior. The model highlights why "status green" is not equivalent to risk resolution and motivates incident response strategies that address perception, merchant messaging, and post-recovery communication in addition to technical remediation.

翻译：零售支付系统的运营中断可能引发超出技术恢复时长的行为反应，并可能加剧流动性压力。本文提出一种多智能体模型，将银行卡支付中断与信任动态、渠道规避及阈值门控提现行为相联结。客户与商户通过重复支付尝试进行交互，同时客户还在Watts-Strogatz小世界网络上相互影响。客户持续更新记录累积负面体验（创伤）与感知系统风险（传闻）的有界记忆变量，商户则提供可能滞后于运营恢复的持续广播信号。我们证明，在记忆持续性与阈值门控的温和条件下，总提现压力可能在中断低谷期之后达到峰值，包括在恢复阶段。仿真结果重现了行为滞后效应，并证实了资金流出的延迟峰值现象。我们进一步研究了通过即时转账实现的支付替代：替代行为持续降低峰值规避率，但在现实的商户广播持续性条件下，其对累计资金流出的影响呈现非单调性。跨随机种子的稳健性实验显示出稳定的定性行为特征。该模型揭示了为何“状态正常”不等于风险化解，并提出了除技术修复外还需关注认知管理、商户信息传递及恢复后沟通的事件响应策略。