Regulatory and compliance are associated with long boring documentation. The same applies to the topic of data governance. Data governance is often reduced to boring rules, policies and standards no one wants to read. A description that fits compliance to a tee. But regulation is used to try to minimize risks and both data governance and compliance requirements are at the heart of all data management activities and can be executed as highly exciting practice-based disciplines.
Authority, control and joint decision-making as planning, monitoring and enforcement have no place in static text documents. These are practices for reducing risk and thus an essential part of regulatory requirements. How about docking them to the data and organizing them as a data asset, manageable and observable at any time? This is exactly what the talk is about: getting out of the dull regulatory environment into data-driven agile data governance in order to mitigate risk in financial data.
What exactly is agile Data Governance?
How to implement regulatory requirements into a DG framework and to mitigate risk in financial data?
Data – driven risk monitor as an example from the insurance industry.