Finance
Verifiable financial data workflows
Financial institutions rely on data from market feeds, internal systems, counterparties and third-party providers.
Ensuring data provenance, integrity and quality is critical for risk management, trading and regulatory reporting.
Regulatory frameworks such as BCBS 239 explicitly require institutions to maintain reliable, traceable and auditable risk data across their systems.
- Traceable data pipelines
Financial data flows through multiple transformation layers, including enrichment, aggregation, analytics and reporting pipelines. Institutions must maintain complete data lineage across these processing chains.
- Governed analytical models
Trading, pricing and risk calculations rely on complex models. Financial institutions must ensure model governance, version control and traceability of the data used in model execution.
- Auditability and regulatory evidence
Financial institutions must be able to reconstruct calculations and data flows supporting regulatory reporting, risk metrics and trading activities. This requires audit-ready evidence across the entire data lifecycle.
Built for trusted financial operations
A trusted financial data architecture must provide:
- End-to-end data provenance across financial data pipelines
- Traceability of data transformations and calculations
- Verifiable outputs from analytics and risk models
- Audit-ready evidence supporting regulatory compliance
These capabilities must operate without disrupting existing financial systems and infrastructures.