AI Prototype: Policy-Driven Governance for KYC Remediation Agents

This prototype explores how governance policies influence the behavior, access decisions, and risk posture of AI agents operating in compliance environments.

Using a KYC remediation case, the AI agent analyzes the issue, determines required actions, and recommends remediation steps. The prototype then compares traditional broad-access models with Zero Standing Privilege (ZSP) and Just-In-Time (JIT) access, demonstrating how policy-driven controls can significantly reduce customer data exposure while maintaining operational effectiveness.

Architecture

KYC Remediation Case

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AI Agent

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Policy Evaluation

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Access Determination

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Risk Assessment

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Remediation Plan

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Governance Recommendation

Key Capabilities

• AI-driven KYC case analysis

• Policy-based access decisions

• Broad Access vs. ZSP + JIT comparison

• Risk and exposure assessment

• KYC remediation recommendations

• Governance and compliance insights

This prototype demonstrates how modern identity and access management principles can be extended to AI agents, enabling secure, policy-driven operations across KYC, AFC, and compliance processes.

Prototype Screenshots