Information Traceability for Regulatory Compliance

Orion Governance Use Case

Privacy and Cybersecurity for Financial and Healthcare Sectors

Businesses in all countries are facing stricter regulatory compliance. Certain sectors are coming under more severe scrutiny: investment, banking, insurance, and healthcare. Enforcement of existing laws is now more vigorous, and many new regulations are now on the books. Of particular concern is cybersecurity in general and consumer privacy specifically.

Firms do not want, under any circumstances, to be sanctioned with civil or criminal penalties for non-compliance. A worst-case scenario could involve large financial penalties or jail time. The consequential damage to reputation and brand equity is almost unimaginable. Even businesses in less regulated sectors are not immune – they need to stay aware and take corrective action as needed.

Regulators want to make sure that companies are fully accountable for the information they provide for internal use as well as for external consumption. The numbers must be accurate, and the overall picture must reflect reality. Compliance has evolved well beyond ticking boxes on a form with a handshake. Increasing pressure to shorten turnaround times for more complex reports is forcing companies to establish central control over their data supply chains. Without that, companies cannot meet increasing business demands for information while satisfying accountability and compliance requirements.

Enterprise-wide data governance is the only solution that will meet modern requirements for regulatory transparency and accurate reporting. Other approaches for managing enterprise data assets and supply chains will be insufficient and will ultimately fail. With that said, implementing a governance strategy is a massive undertaking that often presents significant obstacles.

Visibility and degrees of control over hundreds (or perhaps thousands) of data repositories and application platforms in organizational silos is both a technical and political challenge. Choosing the right automation toolset for data governance is important because insufficient capabilities could lead to unexpected costs or implementation failure.

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