Toward a Risk Assessment Framework for Institutional DeFi: A Nine-Dimension Approach
For institutional DeFi adopters, the framework provides a more rigorous, composability-aware risk assessment methodology, though it is an incremental extension of existing taxonomies.
The paper proposes a nine-dimension DeFi risk assessment framework extending existing taxonomies with composability risk, comprehension debt, and temporal risk dynamics, validated on 12 major incidents (2024-2026) representing ~$2.5B in losses, where 5 incidents required novel dimensions for complete characterization.
Decentralized finance (DeFi) protocols now intermediate over USD 100 billion in value, including regulated stablecoins and tokenized assets deployed as collateral, yet no widely adopted framework operationalizes risk assessment at the rigor institutional adoption demands. Existing approaches emphasize protocol-specific parameter optimization or conceptual taxonomies without providing explainable, composability-aware, and structurally independent assessment methodologies. We propose a nine-dimension DeFi risk assessment framework extending the six-dimension taxonomy introduced by Moody's Analytics and Gauntlet with three novel dimensions: composability risk, comprehension debt, and temporal risk dynamics. We additionally introduce a transparency confidence modifier separating assessment reliability from risk severity. The framework is grounded in structural analysis of protocol dependencies conducted through an ontology-based protocol intelligence infrastructure covering more than 8,000 DeFi protocols. We retrospectively analyze 12 major DeFi-related incidents from 2024-2026 representing approximately USD 2.5 billion in direct losses. Five of the 12 incidents require at least one novel dimension for complete root-cause characterization, including the two highest-systemic-impact events in the dataset.