Data Quality
From Open Risk Manual
Definition
Data Quality (also Data Integrity) refers to the condition of information sets (data) that are to be used as inputs for qualitative or quantitative risk assessment e.g. in the form of Portfolio Information, Algorithms and/or other decision support tools
Regulated institutions are required to have in place a formal Data Quality Management Framework[1]
Examples
- In order to support to the development of an internal Credit Scorecard, a firm must have access to historical credit data that meet data quality criteria
- In Data Privacy context data quality[2] refers to a set of principles laid down in Article 5 of the GDPR and Article 4 of Regulation (EU) 2018/1725, namely:
- Lawfulness, fairness and transparency
- Purpose limitation
- Data minimisation
- Accuracy
- Storage limitation
- Integrity and confidentiality
Issues and Challenges
- During the Financial Crisis data quality was identified as a contributing cause to poor risk management [3]
- Data quality issues are a significant component of Model Risk, colloquially referred to as the "garbage in, garbage out" principle.
See Also
References
- ↑ ECB guide to internal models - Credit Risk, Sep 2018
- ↑ EDPS Glossary
- ↑ BCBS 239: Principles for effective risk data aggregation and risk reporting
