Data Segregation & Access Control
Security & Data Protection
Compliable AI is built for sanctions-sensitive industries where confidentiality, integrity, and auditability are mandatory.
Our security model is designed to protect sensitive counterparty information while preserving full compliance oversight.
Data Segregation & Access Control
Compliable operates as a secure multi-tenant SaaS platform with strict logical data segregation.
Counterparty data, documents, screening results, and risk evaluations are partitioned by organization and accessible only to authorized users within that organization.
No organization has visibility into another organization’s compliance data unless explicit counterparty sharing permissions are granted.
Compliance determinations are never pooled or shared across organizations.
Controlled Counterparty Sharing
Where counterparties elect to share approved documentation or key information with prospective trading partners, access is granted only upon explicit authorization.
Each receiving organization independently validates documentation, performs its own screening, applies its own risk model, and makes its own compliance determination.
Shared access does not merge compliance environments or influence another organization’s risk scoring framework.
Encryption & Infrastructure
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Encryption in transit using TLS
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Encryption at rest for stored documents and structured data
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Secure cloud infrastructure with controlled administrative access
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Role-based access controls and permission segmentation
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Continuous environment monitoring and logging
Access to sensitive data is restricted to authorized personnel and governed by strong authentication controls.
Audit & Traceability
All material actions within the platform are logged.
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Timestamped review actions
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User-attributed approvals and overrides
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Screening and scoring inputs preserved
This ensures defensibility under internal audit, banking review, or regulatory examination.
AI Model Governance
Compliable’s AI-assisted capabilities operate within a controlled, private modeling framework.
Customer data is not used to train public models and is not contributed to external AI systems.
Model improvements are developed using internal methodologies and do not expose or redistribute customer counterparty data.
Confidentiality Commitment
Compliable was designed for industries where information sensitivity is inherent.
Counterparty documentation, ownership structures, screening results, and risk evaluations remain confidential and protected at all times.