Deposit Concentration Risk¶
Judge a bank's funding fragility by the correlation-adjusted effective depositor count rather than the headline number — coupled depositors collapse toward one bet, voiding the law-of-large-numbers smoothing a large base seems to guarantee.
Core Idea¶
Deposit concentration risk is the funding fragility arising when a bank's deposit base is dominated by a few large depositors, or by many whose withdrawal decisions are correlated — sharing an industry, an advisor network, or an information event. The bank looks diversified by count but not by exposure: when the correlation activates, the nominally many behave as one, and funding leaves faster than assets liquidate at par. The 2023 SVB failure is the canonical case.
Scope of Application¶
Deposit concentration risk lives within banking, finance, and prudential regulation, across deposit-taking and funding settings sharing its substrate.
- Commercial banking — the home turf: single-large-depositor or industry-vertical concentration (SVB).
- Prudential supervision — Basel III LCR/NSFR penalties, top-20 depositor lists, uninsured-deposit ratios.
- Money-market funds — institutional flows highly correlated and concentrated.
- Non-bank deposit-takers — credit unions and fintech accounts via partner banks.
- Stablecoin reserves — concentration in the reserve bank becoming concentration in the coin.
- DeFi liquidity pools — pools dominated by a few large providers whose exit breaks the pool.
Clarity¶
Naming the risk makes legible the difference between diversification by count and by exposure. The protective smoothing a large base seems to guarantee is an artifact of the law of large numbers, which requires independence; a shared cause voids it. The question sharpens from "how many depositors?" to "what is the correlation structure, and the effective count once it is applied?"
Manages Complexity¶
The sprawl is the unbounded variety of couplings — industry, region, advisor, insurance status — each suggesting its own ad hoc story. The concept collapses that variety onto one quantity: the effective depositor count under correlation, read against the nominal count. The insured/uninsured split is the branch: insured balances drain slowly, uninsured balances are mutually informative and self-accelerating.
Abstract Reasoning¶
The concept licenses diagnostic reasoning (computing the effective count behind the nominal one), predictive reasoning (the effective count and insurance split fixing the run mode), order-of-events reading of a trigger through a correlated population, interventionist reasoning (diversify against the cause, not the count), and boundary-drawing on the broken independence assumption and the substrate edge.
Knowledge Transfer¶
Within banking the mechanism transfers in full across every deposit-taking and funding structure, the SVB case instructive throughout. Beyond it is a strong shared-mechanism case: the parent concentration_risk/correlated_exposure (with run_dynamics/contagion and liquidity_under_stress) recurs in customer, supplier, and counterparty concentration, where the same effective-count diagnostic and diversify-against-the-cause remedy apply literally. The deposit-specific flavor stays home.
Relationships to Other Abstractions¶
Current abstraction Deposit Concentration Risk Domain-specific
Parents (3) — more general patterns this builds on
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Deposit Concentration Risk is a kind of Funding Fragility Domain-specific
Deposit concentration risk is funding fragility caused by concentrated or correlated withdrawal-capable funding claims.
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Deposit Concentration Risk is a decomposition of, conditional Apparent Variety Masks Shared Driver Prime
In the nominally broad but correlated-depositor branch, stripping banking reveals surface multiplicity coupled by a hidden driver and an effective count that collapses under stress.
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Deposit Concentration Risk is a decomposition of Dependency Distribution Concentration Prime
Removing deposits, insurance, run dynamics, and asset-liquidity framing leaves dependency weight concentrated across funding providers, with fragility governed by effective rather than nominal provider count.
Hierarchy paths (12) — routes to 9 parentless roots
- Deposit Concentration Risk → Funding Fragility → Coordination Problem and Equilibrium Selection → Coordination → Concurrency
- Deposit Concentration Risk → Apparent Variety Masks Shared Driver
- Deposit Concentration Risk → Dependency Distribution Concentration → Dependency
- Deposit Concentration Risk → Funding Fragility → Maturity Mismatch → Coupling
- Deposit Concentration Risk → Funding Fragility → Coordination Problem and Equilibrium Selection → Path Dependence → Collingridge Dilemma
- Deposit Concentration Risk → Funding Fragility → Coordination Problem and Equilibrium Selection → Coordination → Dependency
- Deposit Concentration Risk → Funding Fragility → Coordination Problem and Equilibrium Selection → Path Dependence → Dependency
- Deposit Concentration Risk → Funding Fragility → Coordination Problem and Equilibrium Selection → Equilibrium → Fixed Point
- Deposit Concentration Risk → Funding Fragility → Coordination Problem and Equilibrium Selection → Path Dependence → Time
- Deposit Concentration Risk → Funding Fragility → Coordination Problem and Equilibrium Selection → Coordination → Task Interdependence → Dependency
- Deposit Concentration Risk → Funding Fragility → Coordination Problem and Equilibrium Selection → Coordination → Mobilization → Latent Realizable Capacity
- Deposit Concentration Risk → Funding Fragility → Coordination Problem and Equilibrium Selection → Coordination → Task Interdependence → Network → Reservoir-Flux Network → Conservation Laws → Invariance
Neighborhood in Abstraction Space¶
Deposit Concentration Risk sits in a sparse region of the domain-specific corpus (74th percentile for distinctiveness): few abstractions share its structure, so a faithful description tends to retrieve it precisely.
Family — Monetary Mechanics & Macro Trilemmas (7 abstractions)
Nearest neighbors
- Wholesale-Funding Run — 0.86
- Flight to Quality — 0.83
- Concentration Illusion — 0.82
- Money Multiplier — 0.82
- Modigliani–Miller theorem — 0.82
Computed from structural-signature embeddings · 2026-07-12