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An empirical study on risk data quality management

Risk management is a critical core process of a financial corporation, which has been attracted more attention by the governors since The Financial Crisis. New regulations require more strict control over corporation's risk, which needs data of better quality. In this paper, we propose a comprehensive framework for risk data quality management. New data quality dimensions that combine business rules are designed to reflect the risk management requirements. According to the detailed dimensions, we examine large amount of heterogeneous data in a bank to find the difference between the normal standard and the current data. Enterprises should take appropriate measures to improve the data quality to meet the standard. Experiments show that the framework is effective.