Bank Run Contagion Simulator

Financial System

Banks 24

Interbank connectivity 0.18

Capital buffer 0.65

Contagion rate 1.0

Shock severity 0.8

Banks failed

0 / 0

Avg capital

–

System loss

–

Cascade depth

–

How it works

Each sphere is a bank; its size and colour encode remaining capital (bright green = fully capitalised, red = failed). The lines between them are interbank exposures — one bank's loans/deposits held with another — with brightness showing how much distress is currently flowing across that link. Triggering a bank run instantly drains one bank's capital (a depositor panic). If its capital falls under a survival threshold it fails, and its losses are passed to every bank it owes money to or borrows from, weighted by the exposure on that link — a simplified DebtRank-style contagion model.

dc_i/dt = −Σⱼ exposure(i,j)·(1−c_j)·contagionRate
        − panicDrain(c_i)  + recovery·(1−c_i)
bank i fails when c_i ≤ 0

Banks — size of the interbank network being simulated.
Interbank connectivity — how densely banks lend to and borrow from each other; denser networks spread shocks further but also share the load, which can dampen or amplify the crisis depending on buffer size.
Capital buffer — the loss-absorbing capital every bank starts with; thin buffers fail faster and drag down more neighbours.
Contagion rate — how strongly a distressed bank's losses transmit across its exposure links to counterparties.
Shock severity — how much capital the initially-triggered bank loses in the run itself, before any contagion begins.

Real-world relevance: this is the core mechanism behind systemic banking crises — Lehman Brothers 2008, the 1930s U.S. bank runs, and repeated European sovereign-bank feedback loops all followed this pattern: a shock at one institution, transmitted through interbank exposure, amplified by thin capital buffers and self-reinforcing depositor panic once a bank looks weak.

Healthy (high capital) Distressed Failed / insolvent Interbank exposure link

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