Description
Recent studies have indicated that companies are increasingly experiencing Data Quality related problems as more and more complex data are being collected. In order to address such problems, literature suggests the implementation of a Total Data Quality Management Program that should consist of the following phases: data quality definition, measurement, analysis and improvement. Data Quality is often defined as “fitness for use”. Although “fitness for use” captures the essence of quality, it is difficult to measure Data Quality using this broad definition. Thus, it has long been acknowledged that the quality of data is best described or analyzed via multiple attributes or dimensions.
Despite broad discussion in the Data Quality literature, there is no one definite set and exact definition of Data Quality dimensions because Data Quality is context dependent. Therefore, Data Quality dimensions should be identified and defined in relation to tasks to achieve a suitable level of Data Quality.
Our research identifies important Data Quality dimensions for evaluating the quality of the data for credit risk assessment. We also explore the key Data Quality challenges and causes of Data Quality problems in financial institutions, based on statistical analysis.
Notable Publications
- Moges, H., Dejaeger, K., Lemahieu, W., Baesens, B. (2012). A multidimensional analysis of data quality for credit risk management: new insights and challenges. Information & Management.
- Moges, H., Dejaeger, K., Lemahieu, W., Baesens, B. (2012). A total data quality management for credit risk: new insights and challenges. International Journal of Information Quality, 3 (1), 1-27.
- Moges, H., Lemahieu, W., Baesens, B. (2012). The use of data quality information (DQI) for decision-making: an exploratory study. In Nag, A. (Ed.), Proceedings of the International Conference on Business Management and Information Systems (ICBMIS 2012). International conference on business management and information systems (ICBMIS 2012). Singapore, 22-24 November 2012 (pp. 386-394). New Delhi 110 070: Bloomsbury Publishing India Pvt. Ltd..
- Moges, H., Dejaeger, K., Lemahieu, W., Baesens, B. (2011). Data quality for credit risk management: new insights and challenges. . International Conference on Information Quality (ICIQ) 2011. University of South Australia, Adelaide (Australia), 18-20 November 2011.
