Why Corporate Risk Management Needs Data Vault

In September 2019, Paul Ramsay delivered a webinar on how Data Vault architecture can transform risk management for modern organizations. Here’s a summary of the key insights and practical takeaways from that session.

What Is Corporate Risk Management?

Corporate risk management involves identifying, evaluating, and prioritizing risks—defined by ISO 31000 as “the effect of uncertainty on objectives.” The process includes applying resources to minimize, monitor, and control the probability or impact of unfortunate events, or to maximize opportunities. ISO 31000:2018 provides a universal framework for managing risk, applicable to organizations of any size or sector.

The Layers of Risk

Risk management operates at multiple levels:

• Strategic: Board-level reputation risks (e.g., failing to honor commitments)

• Tactical: Functional and computational risks (e.g., credit, market, operational risks)

• Operational: Programming and compliance risks (e.g., GDPR violations, cyberattacks)

Each layer requires robust data models and reporting to ensure risks are identified and managed effectively.

The Challenge: Reporting Corporate Risk Exposure

A central question for risk managers is: What is the risk of a corporate customer failing? To answer this, organizations need a core data model that captures:

• Customer ratings

• Exposure values

• Industry classifications (NACE codes)

• Product details

The NACE system (“nomenclature statistique des activités économiques dans la Communauté européenne”) is the EU standard for industry classification and is essential for consistent risk reporting.

Data Vault for Corporate Risk: The Logical Model

Data Vault provides a flexible, scalable architecture for managing risk data. The core logical model includes:

• Customer Hub: Centralizes customer information

• Product Hub: Captures product data

• NACE Hub: Stores industry classification

• Rating Value Hub: Manages customer ratings

• Satellites: Store historical and descriptive data for each hub

• Links: Connect customers, products, ratings, and exposures

This structure supports both historical tracking (using SCD Type 2, 4, and 6 patterns) and real-time reporting.

Unified Data Vault Architecture for Risk Management

The webinar illustrated how Data Vault can unify risk data across the organization:

• Supply Systems: Feed data into the Data Vault

• Reporting Rules: Standardize risk exposure reporting

• Business Rules: Enable advanced risk assessments and computations

• Artificial Intelligence: Integrate AI for predictive risk analytics

By layering reporting rules, business rules, and AI on top of the Data Vault, organizations can achieve a unified, consistent, and auditable view of corporate risk exposure.

Key Benefits of Data Vault for Risk Management

• Consistency: Standardized data models ensure uniform risk reporting

• Auditability: Historical tracking supports compliance and transparency

• Scalability: Easily adapts to new risk types, products, and regulations

• Integration: Combines data from multiple sources, including AI-driven insights

Conclusion

Data Vault architecture is a powerful enabler for modern corporate risk management. By adopting a unified, scalable, and auditable approach, organizations can better identify, assess, and mitigate risks—while supporting regulatory compliance and strategic decision-making.

For more resources and expert guidance, visit your Data Community or connect with Paul Ramsay.