We present a human-in-the-loop (HITL) visual analytics approach that enhances systemic risk assessment through the domain-specific integration of hierarchical grouping, clustering, edge bundling, labeling, and zooming techniques. Our contribution is the deliberate combination of these methods to support perceptual scalability, enabling users to explore large, complex networks more effectively and reason about systemic vulnerabilities.

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