Data Quality: A Perspective
from Data Examiners of a Financial Regulator
Gene Draschner & Elliott Blake
Just as institutions are, more than ever, becoming aware of the importance of data quality, regulators are shifting toward a more comprehensive view when evaluating an institution's data quality. The purpose of this article is to explore this more complete view of data quality and begin to lay out a framework for evaluating data quality at regulated institutions.
We propose six principles to guide our data quality evaluation strategy.
- build on the institution's work
- perform risk-based examinations
- define data from repositories to management reports
- identify issues, but leave issue resolution up to institution
- ensure safety and soundness; don't manage the business
- treat all institutions equally
Our goal is to engage all interested parties in a discussion that can help shape an approach to data quality evaluation that satisfies these principles.