Data Quality

From Open Risk Manual


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]


  • 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

See Also


  1. ECB guide to internal models - Credit Risk, Sep 2018
  2. EDPS Glossary
  3. BCBS 239: Principles for effective risk data aggregation and risk reporting