Social Contagion and Bank Runs: An Agent-Based Model with LLM Depositors
An agent-based model with 4,900 simulations shows how social media amplifies financial panic.
Researchers Chris Ruano and Shreshth Rajan developed an agent-based model where depositors are simulated by a constrained large language model (LLM). The model, validated against lab data, simulates 4,900 bank-run scenarios on a network calibrated to real Twitter activity. It found that within-bank connectivity raises cascade likelihood, and a 10% cross-bank spillover rate triggers a sharp phase transition. The model successfully reproduced the failure order of banks like SVB and First Republic.
Why It Matters
Provides a new, data-driven framework for regulators to measure and mitigate social media-driven financial contagion risk.