Knowledge base · Risk & sizing

Crypto loss modes

Educational reference from the platform knowledge base — written agent-readable first, rendered here for humans. Mechanics, not advice: nothing here is a recommendation to buy or sell any security.

Crypto loss modes

Definition

Crypto’s realized catastrophic losses cluster in modes mostly ABSENT from listed-market investing: venue failure and misappropriation (FTX 2022, Mt. Gox 2014), protocol and contract exploits, key compromise and irreversible theft, fraud at asset level (Terra/UST 2022), and permanent operational errors (wrong-rail transfers, lost keys). These are not tail decorations on price risk — for the asset class’s history, custody-and-fraud losses are a first-order loss category alongside drawdowns (crypto-drawdown-behavior), and they are the reason structure (venue limits, custody choice, wrappers) is part of any crypto position’s design.

How it works / structure

The catalog, each mode with its canonical exhibit:

  • Venue failure / misappropriation: operator diverts or loses customer assets; customers become unsecured creditors (crypto-custody-models). Exhibits: FTX (CFTC fraud complaint, 2022 — customer funds diverted at scale), Mt. Gox (DOJ charges document the multi-year hack draining ~647,000 bitcoin).
  • Protocol / contract exploits: code vulnerabilities in token contracts, bridges, and DeFi protocols drained at scale; bridge exploits produced several of the largest single-incident thefts on record (FBI/IC3 and industry incident data; industry loss tallies labeled as such).
  • Key compromise: phishing, SIM-swap, malware, and insider theft against hot wallets — the dominant retail loss channel by incident count (IC3 fraud reporting; crypto-wallets-keys).
  • Asset-level fraud: instruments engineered or misrepresented to fail — Terra/UST’s collapse with SEC fraud charges is the canonical case (crypto-stablecoins); IC3 data documents “pig butchering”-style investment fraud as the largest dollar category of reported crypto crime.
  • Irreversible operational error: mis-addressed transfers, unsupported-network sends, seed loss — no recovery mechanism exists (crypto-transfer-settlement).

When it applies

Position and venue structuring (every crypto allocation states its custody exposure and venue concentration), scenario analysis (risk-scenario-analysis grids for crypto include a venue- failure row, not just price shocks), and due-diligence framing: the platform treats “which loss modes does this structure remove” as the first question a crypto position answers — wrappers remove key risk and add issuer/custodian risk (crypto-etps); self-custody inverts that trade.

Risk profile & failure modes

  • Clustering with stress: venue failures and depegs land in drawdowns — loss modes correlate with price risk exactly when diversification is most needed.
  • Opacity until failure: venue solvency and contract soundness are unobservable from outside; the signal that matters (withdrawal suspension) arrives after the exit narrows.
  • Recovery is slow and partial: bankruptcy processes run years; some proceedings settle claims at petition-date fiat values, converting a recovery into a missed rally.
  • Survivorship illusion: venues and protocols that failed vanish from datasets; backtests over surviving venues understate the category’s base rate (quant-backtest-hygiene).

Evidence & limits

The canonical incidents are government-documented (CFTC, DOJ, SEC actions cited above); aggregate fraud magnitudes come from FBI/IC3 reporting (reported losses — an undercount by construction) and industry incident tallies (methodology varies — labeled). Per-venue or per-protocol risk today is not assessable from public data; this entry supports structural mitigation, not venue scoring.

Falsifiable-thesis examples

Illustrations only, not signals:

  • “At least one exploit exceeding $100M occurs in bridge or DeFi infrastructure this year (exploit-persistence thesis)” — falsified by the incident record.
  • “IC3-reported crypto fraud losses decline year over year for the first time (enforcement-effect thesis)” — falsified by the next annual report.

Cross-references

  • The structural levers: crypto-custody-models (who holds), crypto-wallets-keys (key perimeter), crypto-transfer-settlement (irreversibility)
  • Asset-level fraud case: crypto-stablecoins (Terra/UST)
  • The risk frame: risk-scenario-analysis, crypto-drawdown-behavior (price-risk companion)

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