Risk Data Aggregation and Risk Reporting: A Regulatory Perspective
A Regulatory Perspective
Delivering Compliance: Challenges and Opportunities
BCBS 239 at Commerzbank: Applying a Central Standards/De-central Implementation Approach
Data Governance: Embedding a Data Governance Process
What is the Problem with Risk Data, and How Can Executive Data Governance Address it?
Data Architecture and Aggregation
Managing Data Quality: Completeness, Accuracy and Timeliness
This chapter will examine the issue of data architecture and its role in creating a highly aggregable data estate. The background of data architectures in finance is discussed to provide an understanding of the nature of the problem, and why this is seen as a key component in BCBS 239 programmes. Data architectures will be shown to be not just for the technical specialist; with data being one of the most valuable resources in a bank, all areas have to consider their data needs and articulate key concepts to the builders. This understanding of requirements at a conceptual level is fundamental to the creation of an environment where information is manageable. The main component of the data model will be shown to be a powerful tool for both users and technicians, and options for a data model will be considered.
The banking sector has grown exponentially since the early 1990s, and technology has helped to facilitate this growth. However, silos are still common – not least those in risk and finance. The practical application of a data model to the information requirements of these teams will show how a data-centric approach could significantly reduce costs, increase operational effici