OpenAssets Blog
Perspectives from the team building the data layer for institutional RWA ownership.
The problem is not that custodians send wrong data. The problem is that they each send correct data in a format that is incompatible with every other custodian. Here is what that looks like in practice and how a canonical data layer resolves it.
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Most asset managers know GLBA applies to them. Fewer know exactly what the 2023 updated Safeguards Rule demands from data systems handling customer financial information.
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Building a data layer for institutional RWA ownership is different from building a general-purpose data platform. The design constraints come from regulation and auditability, not just scale.
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Automating reconciliation is not just about removing manual steps. The hard part is automating in a way that preserves the complete, attributable audit trail your compliance team needs.
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SEC Rule 17a-4 specifies how broker-dealers and investment advisers must preserve electronic records. The non-rewriteable, non-erasable, and immediately accessible requirements have direct implications for how ownership data systems are designed.
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Book close is not slow because operations teams are slow. It is slow because the data arrives in incompatible formats that require manual normalization before any reconciliation can begin.
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The technical infrastructure for tokenizing real-world assets has matured. The compliance data infrastructure for those tokenized assets has not. Here is where the gap lives and why it matters for institutional adoption.
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Data quality in institutional ownership records is not an abstract concept. There are specific, testable dimensions: completeness, accuracy, timeliness, and consistency. Here is how to apply each one.
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Compliance requirements cannot be retrofitted onto a data system that was not designed for them. Audit trails, retention structures, and non-repudiation must be architectural decisions, not post-hoc features.
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Fund close is a deadline with fixed inputs and non-negotiable outputs. Reconciliation problems during that window are not just inconvenient. They delay reporting and introduce compliance exposure.
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Standard fintech data infrastructure optimizes for latency, throughput, and availability. Compliance data infrastructure must also optimize for auditability, retention, and regulatory producibility. The design decisions are different.
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Choosing a data standard for ownership records is not a technical preference. It is a structural decision that affects every downstream system that touches that data for years. Getting it wrong compounds.
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