Which cognitive biases were evident in Three Arrows Capital's collapse?

5 bias patterns are documented in this case, led by Recency Bias. The full set: Overconfidence Bias, Recency Bias, Confirmation Bias, Anchoring Bias, Hindsight Bias. Each is mapped to Decision Intel's 22-bias R²F taxonomy with stable IDs and academic citations.

Did these cognitive biases cause Three Arrows Capital's collapse?

Decision Intel identifies reasoning-risk indicators correlated with poor outcomes — it does not claim to establish causation. That honesty is the procurement weapon: a CSO can defend a score that names the risk indicators a committee should pressure-test, not one that pretends to prove the cause. Recency Bias and the other documented patterns were detectable in the reasoning before the outcome was known; whether they caused it is a question no audit can settle — too many other factors (market, timing, execution) are in play. A reasoning audit names the risk indicators a committee should pressure-test, not a verdict it should accept.

What is Decision Intel's reasoning audit?

Decision Intel runs a Recognition-Rigor Framework (R²F) audit on strategic memos, detecting cognitive biases from a 22-bias canonical taxonomy and producing a Decision Quality Index (DQI) score. The audit produces a hashed, tamper-evident Decision Provenance Record (DPR) suitable for audit-committee review.

All case studies

Catastrophic failureFinancial Services2022

Three Arrows Capital

Three Arrows Capital Insolvency

Estimated impact: $3.5B in creditor losses

F14

Decision Quality Index (simulated)

Critical · 5 biases detected, 2 toxic combinations

Crypto hedge fund 3AC defaulted on $3.5B in loans from multiple lenders after making concentrated, leveraged bets on LUNA/UST and Grayscale Bitcoin Trust. Founders Zhu Su and Kyle Davies had publicly promoted positions they were secretly unwinding.

Decision context

Whether to maintain highly concentrated, leveraged positions in correlated crypto assets without adequate hedging or liquidity reserves.

Deep hindsight-stripped analysis coming soon. This case is part of our ongoing backfill to reconstruct what was flaggable in the record at decision time. The summary and bias profile below are drawn from primary sources.

Decision anatomy

Monetary stakes

Very high

Dissent suppressed

Yes

Time pressure

Present

Unanimous consensus

Yes

Decision participants

Dissent encouraged

External advisors

Iterative process

Red = risk factor present · Green = protective factor present

Biases present in the decision

Overconfidence Bias

high

★Recency Bias

critical

Confirmation Bias

high

Anchoring Bias

high

Hindsight Bias

medium

★ Primary driver · Severity estimated from bias type and decision outcome

3D Decision Knowledge Graph

Three Arrows Capital · 5 biases, 2 toxic combinations

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Decision

Critical

High

Medium

Toxic

Bias Intensity Profile

Severity × confidence across 5 detected biases

Toxic combinations

!Recency Spiral

Compound cognitive failure pattern identified in this decision.

!Optimism Trap

Overconfidence and availability bias create a systematically positive outlook that ignores base rates.

The curated library this case sits in

Across all 155 curated case studies in our library, by documented outcome:

123

documented failures

partial / mixed

documented successes

The library is curated toward documented failures, so this split describes the library, not the base rate of deals. The case above is one row in it.

■ Failure■ Partial■ Success

Lessons learned

Recency bias from crypto bull markets led to position sizing that assumed perpetual upward trends
Counterparty risk in crypto lending is amplified by opacity — lenders had no visibility into total exposure
Hindsight bias after the collapse obscured that many participants knowingly accepted concentrated risk for yield

Source: Three Arrows Capital liquidation proceedings, BVI Commercial Court (2022); BlockFi bankruptcy filings (Case Study)

Pilot slots available

These patterns were flaggable in Three Arrows Capital's own record — before the outcome.

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Workflows that fire on decisions like Three Arrows Capital’s

The same Recognition-Rigor Framework that documents this case audits memos in the same shape — before the outcome forces the lesson.

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The curated library this case sits in

Across all 155 curated case studies in our library, by documented outcome:

123

documented failures

partial / mixed

documented successes

The library is curated toward documented failures, so this split describes the library, not the base rate of deals. The case above is one row in it.

■ Failure■ Partial■ Success

Lessons learned

Recency bias from crypto bull markets led to position sizing that assumed perpetual upward trends

Counterparty risk in crypto lending is amplified by opacity — lenders had no visibility into total exposure

Hindsight bias after the collapse obscured that many participants knowingly accepted concentrated risk for yield