One control layer. Many regulators satisfied.

Regulatory context

US financial regulators emphasize data integrity, auditability, third-party risk management, operational resilience, and model risk governance. Supervisory expectations are principles-based and enforced through examination, rather than prescriptive technical mandates.

Problem addressed

Sensitive data is often distributed across applications, vendors, and environments — creating gaps in integrity, access traceability, and audit evidence. These gaps increase supervisory, operational, and litigation risk.

EpositBox control approach

• Immutable, blockchain-anchored records.
• Machine-to-machine access with deterministic authentication.
• Full access history and data lineage.
• Separation of data custody from application logic.
• Aligns with SR 11-7 model risk expectations and supervisory guidance on AI governance.

Regulatory context

UK regulators emphasize operational resilience, accountability, third-party risk, and demonstrable control effectiveness. Firms are expected to evidence how critical services remain resilient under stress and how data integrity is preserved.

Problem addressed

Distributed data custody models make it difficult to demonstrate integrity, traceability, and recoverability during incidents, audits, or supervisory reviews.

EpositBox control approach

• Immutable records supporting provable integrity.
• Zero-trust, non-human access controls.
• Deterministic audit trails aligned to supervisory review.
• Strong separation of duties between applications and custody.
• Immutable AI inputs and access histories support accountable AI adoption.

Regulatory context

EU regulators emphasize data protection, integrity, accountability, long-term confidentiality, and explainability. Supervisory frameworks increasingly address AI governance, third-party risk, and operational resilience through prescriptive regulation.

Problem addressed

Long-term retention of sensitive data creates risks related to integrity, unauthorized access, explainability, and future cryptographic exposure — particularly in complex multi-vendor environments.

EpositBox control approach

• Immutable data integrity and versioning.
• Full access traceability and auditability.
• Separation of data custody from processing systems.
• Cryptographic agility supporting long-term confidentiality.
• Immutable lineage supports explainability under emerging EU AI governance.

Regulatory context

DORA establishes a unified EU framework so financial entities can withstand, respond to, and recover from ICT-related disruptions. It shifts expectations from policy intent to demonstrable, operationally enforced controls — across ICT risk, recoverability, integrity, third-party ICT risk, and evidence-based oversight.

Problem addressed

Fragmented data architectures hinder DORA compliance: difficulty proving integrity during incidents, limited visibility into historical access, complex recovery and forensic reconstruction, and increased third-party concentration risk.

EpositBox control approach

• ICT Risk Management — minimize human access, immutable integrity, clear trust boundaries.
• Incident Response & Recovery — controlled recovery and forensic review without log reconstruction.
• Operational Resilience Testing — deterministic data integrity under simulated disruption.
• Third-Party ICT Risk — pre-validated, auditable custody layer reduces concentration exposure.
• Information Sharing & Oversight — comprehensive immutable audit trails for supervisory review.