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Finance

Asset Manager: Protecting Proprietary Trading Models

How a global asset manager deployed sovereign AI to protect proprietary trading models from competitor fingerprinting—achieving measurable alpha on isolated infrastructure.

Model Fingerprinting Attacks

0

Proprietary Data Access

Unrestricted

Regulatory Compliance

100%

The Challenge

The Challenge

This global asset manager's quantitative trading desk operates proprietary models trained on decades of proprietary market data. These models represent significant competitive advantage. When the firm considered deploying models through cloud-based AI APIs, they identified a critical vulnerability: competitors can fingerprint proprietary models by probing API responses, reverse-engineering the decision logic, and building countermeasures.

Cloud infrastructure shares compute and network resources—creating fingerprinting vulnerabilities that don't exist in isolated on-premises systems.

The Solution

The PRYZM Solution

PRYZM deployed the firm's proprietary models on isolated on-premises infrastructure with zero cloud connectivity:

  • Complete Model Isolation: Competitors cannot fingerprint proprietary decision logic
  • Unrestricted Model Behavior: No RLHF constraints limiting strategy execution
  • Hardware Attestation: Proof that decisions were computed in isolated enclaves
  • Evidence Packs: Cryptographic audit trails for regulatory compliance without exposing strategy details

Executive Summary

A global asset manager deployed PRYZM's sovereign AI platform for proprietary trading, achieving complete isolation from competitor fingerprinting while generating cryptographic Evidence Packs for regulatory compliance.

Background

Proprietary trading depends on information asymmetry—models trained on exclusive datasets and optimization logic unknown to competitors. Cloud-based AI services expose this intellectual property to fingerprinting attacks.

Implementation

PRYZM deployed proprietary models on isolated on-premises infrastructure with hardware attestation and cryptographic evidence logging.

Results

Security: Zero successful fingerprinting attacks. Complete isolation from cloud infrastructure prevents competitor intelligence gathering.

Regulatory Compliance: Full audit trails and evidence logs satisfy SEC requirements without exposing trading strategy details.

Key Takeaways

For organizations with proprietary AI models, sovereign deployment unlocks competitive advantages that cloud-based approaches cannot provide.

"Our proprietary models represent decades of research investment. Cloud infrastructure would expose them to competitor fingerprinting. PRYZM's isolated approach lets us benefit from this competitive advantage without risk."

Head of Quantitative Strategies

Head of Quantitative Strategies at Global Asset Manager

Full Testimonial

Cloud-based AI is incompatible with proprietary trading strategies—competitors can too easily reverse-engineer our models. PRYZM gave us the isolation we needed to deploy unrestricted models without exposure. The hardware attestation ensures our compliance team can audit decisions, but our trading teams maintain complete strategic flexibility.

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