Third-Party Risk in the Age of AI and Outsourcing
As institutions scale AI initiatives and lean heavily on external partners, the nature of third-party risk has changed. Resilience and control now extend far beyond the four walls of the enterprise.
Why It Matters
In today’s operating model, third parties aren’t just vendors, they’re critical extensions of enterprise capabilities. From AI engines to cloud-native KYC providers, outsourced entities now directly influence customer experience, data protection, and regulatory posture. The complexity? Risk ownership is often unclear, and control visibility is fading fast.
Where Institutions Fall Short
- Lack of real-time risk monitoring across third-party ecosystems
- AI providers without explainability or ethical alignment
- Inadequate contractual clauses for regulatory or operational transparency
- Weak resilience testing for critical outsourced services
- No central inventory or tiering based on risk and criticality
Modernizing TPRM for Today’s Realities
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Focus Area
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What Best-in-Class Looks Like
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Tiering Frameworks
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Based on regulatory impact, data sensitivity, and operational dependency
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Continuous Monitoring
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Risk dashboards and telemetry for key third parties
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AI Model Oversight
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Explainability, fairness, and usage audit trails
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Contractual Controls
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Rights to audit, data use clauses, resilience SLAs
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Incident Response Integration
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Clear escalation paths and third-party response alignment
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How Wyman Helps
- Build enterprise-wide Third-Party Risk Management (TPRM) frameworks
- Design AI vendor governance models (model explainability, fairness audits)
- Conduct third-party concentration and criticality reviews
- Implement resilience testing scenarios with outsourced service providers
- Create regulatory-ready documentation and scorecards for top vendors
Case Insight: AI Vendor Oversight for a Tier-1 Bank
Client: A top-tier global bank deploying multiple AI tools for customer servicing and risk scoring
Challenge: No formal risk or model governance structure for third-party AI providers
Wyman’s Solution:
- Developed an AI vendor control framework covering explainability, entitlements, and ethical risks
- Embedded usage audits and alignment to internal risk taxonomy
- Enabled monitoring dashboards and model risk escalation protocols
Outcome:
- Achieved model transparency across all AI tools
- Reduced third-party risk exposure ratings by 45%
- Passed regulatory review without follow-up findings
Why This Matters
Third-party risk is no longer just about vendor onboarding and offboarding. It’s about controlling what’s being done with your data, your processes, and your customers by someone else. And as AI adoption rises, this risk only multiplies.