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Home/Crypto News/AI Trade Triggers $60M in Crypto Liquidations as Firm Promises Full Reimbursement
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AI Trade Triggers $60M in Crypto Liquidations as Firm Promises Full Reimbursement

Olivia Stephanie
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Olivia Stephanie
Published:Jul 29, 2026
2 MIN READ
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The company behind an AI-driven trade linked to roughly $60 million in crypto liquidations says it will cover all affected losses, after a sharp price dislocation cascaded through leveraged positions and reignited scrutiny of automated trading risk controls.

The company behind an AI-driven trade linked to roughly $60 million in crypto liquidations says it will cover all affected losses, after a sharp price dislocation cascaded through leveraged positions and reignited scrutiny of automated trading risk controls.

What Happened in the $60 Million Liquidation Event

The event centered on perpetual contracts tied to SK Hynix that briefly crashed to around $900 on Hyperliquid, according to reporting on the flash crash. For related coverage, see Blumenthal Accuses Trump of Exploiting Crypto Loopholes.

The dislocation was linked to an oracle pricing issue on the SK Hynix perpetual market, which triggered a wave of forced liquidations, as documented in coverage of the Hyperliquid liquidations. For related coverage, see Franklin Templeton Backs CLARITY Act in Crypto Policy Push.

  • What to know: An AI-driven trade was tied to roughly $60 million in crypto liquidations.
  • What to know: The firm behind the trade has publicly pledged to cover all resulting losses.

Forced liquidations happen when leveraged positions fall below their maintenance margin, prompting an exchange to automatically close them. When a price feed dislocates sharply, those closures can chain together across many accounts. For related coverage, see Stellar Onboards Three New Tier 1 Validators in July 2026.

The confirmed elements are the flash crash on SK Hynix perpetuals and the firm’s loss-coverage pledge. Details such as the precise per-account impact and full timeline remain only partially verified.

Why the Company Says It Will Cover All Losses

Trade.xyz said it would reimburse users affected by the SK Hynix liquidation losses, according to reporting on the announcement.

The firm lists SK Hynix among the Korean equities it supports as tradable assets, per its Korea stock asset directory, placing the affected market within its own product scope.

The company communicated the commitment directly through its official account on X, framing the reimbursement as covering the losses stemming from the incident.

Statement on the SK Hynix perpetual liquidations. https://x.com/tradexyz/status/2082260930751082821

— Trade (@tradexyz) July 28, 2026

Source: @tradexyz on X

The available reporting does not specify whether reimbursement is automatic or requires affected traders to file claims, nor a firm repayment timeline. Those terms remain unconfirmed.

What the Incident Means for AI-Driven Crypto Trading

The episode ties automated execution to a concrete, verifiable failure: an oracle-linked price move that forced closures across leveraged accounts before any human intervention.

Automation can amplify volatility precisely when safeguards fail, because algorithmic systems act on a faulty price feed faster than markets or operators can correct it. That dynamic is central to the reported liquidation cascade.

A pledge to make users whole is a direct accountability signal, and how such incidents are resolved feeds into broader debates over trading protections. Regulators elsewhere are already weighing rules for organized crypto trading, including draft rules from Russia’s central bank and proposed purchase caps for retail investors.

Beyond the confirmed reimbursement pledge and the SK Hynix flash crash, the wider fallout for trust in AI-based trading systems is not yet quantified in the available evidence.

Disclaimer: This article is for informational purposes only and does not constitute financial or investment advice. Cryptocurrency and digital asset markets carry significant risk. Always do your own research before making decisions.

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