Building and Performance Validation of a Digital Twin Regulatory Framework for Financial Compliance and Market Transparency

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Abstract

Proposes Reg-Twin—a digitalization of the end-to-end process from transaction → alert → case → SAR/SEC reporting. It incorporates a built-in policy rule engine, reconciliation and drift monitoring, and strategy A/B sandboxing. Through hash-chain data inheritance + selective zero-knowledge proofs (ZK), it demonstrates key compliance points to regulators without data leakage. In simulations and replays across 3,500+ funds and 70+ institutions: - Consistency defects reduced by 41% - Cross-report discrepancies decreased by 36% - Closing cycles shortened by 22% - Estimated alert volume/personnel efficiency/SLA error for strategy changes ≤ ±5% ZK proofs minimize sensitive field disclosure while enabling auditable verification. Reg-Twin demonstrates a technical pathway where enhanced transparency coexists with reduced compliance costs.

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