Compliant AI Infrastructure for Regulated Finance: A tiered multi-agent framework with DLT audit trails for financial operations in DACH

Battle Count: 0

While the architecture is relevant for the operational and compliance side of quantitative trading (e.g., order execution gating, audit trails, risk limits), it does not propose new trading strategies, alpha generation models, or market prediction algorithms. It focuses on infrastructure and governance.

High complexity due to the integration of multi-agent orchestration, a custom policy compiler, legal corpus indexing, and a permissioned DLT/DAG infrastructure. Requires significant engineering effort to ensure determinism, security, and regulatory alignment.

The paper presents a theoretical reference architecture and pseudocode. It explicitly states that empirical evaluation at meaningful scale requires full system deployment beyond academic scope. No code or dataset is publicly available; data and code are available only on reasonable request.