A Post-Trade Data Model defines the structured representation and organization of all information related to a trade after its execution, encompassing confirmation, settlement, clearing, and regulatory reporting requirements within the crypto asset ecosystem. It ensures data consistency and facilitates accurate record-keeping.
Mechanism
This model standardizes data fields for executed trades, including asset identifiers, quantities, prices, timestamps, venue information, and counterparty details. It incorporates blockchain transaction hashes for on-chain settlements and smart contract execution details. The structured data is then processed for reconciliation, risk calculations, and the generation of audit trails, ensuring compliance with internal policies and external regulations.
Methodology
The methodology involves designing a robust data schema that supports immutability and auditability, crucial for distributed ledger technologies. It integrates with various internal systems, such as accounting, risk management, and compliance platforms, to provide a single, authoritative source of truth for all post-trade activities. This data model is critical for accurate financial reporting, operational efficiency, and demonstrating adherence to regulatory obligations in institutional crypto trading and custody operations.
The primary governance challenges in managing a unified post-trade data model are establishing data ownership, ensuring data quality, and adhering to regulations.
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