Title
A multidimensional analysis of data quality for credit risk management: New insights and challenges
Abstract
Recent studies have indicated that companies are increasingly experiencing Data Quality (DQ) related problems as more complex data are being collected. To address such problems, the literature suggests the implementation of a Total Data Quality Management Program (TDQM) that should consist of the following phases: DQ definition, measurement, analysis and improvement. As such, this paper performs an empirical study using a questionnaire that was distributed to financial institutions worldwide to identify the most important DQ dimensions, to assess the DQ level of credit risk databases using the identified DQ dimensions, to analyze DQ issues and to suggest improvement actions in a credit risk assessment context. This questionnaire is structured according to the framework of Wang and Strong and incorporates three additional DQ dimensions that were found to be important to the current context (i.e., actionable, alignment and traceable). Additionally, this paper contributes to the literature by developing a scorecard index to assess the DQ level of credit risk databases using the DQ dimensions that were identified as most important. Finally, this study explores the key DQ challenges and causes of DQ problems and suggests improvement actions. The findings from the statistical analysis of the empirical study delineate the nine most important DQ dimensions, which include accuracy and security for assessing the DQ level.
Year
DOI
Venue
2013
10.1016/j.im.2012.10.001
Information & Management
Keywords
Field
DocType
credit risk management,additional dq dimension,dq problem,dq level,dq issue,important dq dimension,credit risk databases,improvement action,data quality,multidimensional analysis,dq dimension,key dq challenge,dq definition,new insight,data definition,information quality,credit risk
Data quality,Multidimensional analysis,Data definition language,Knowledge management,Balanced scorecard,Engineering,Credit risk,Empirical research,Statistical analysis,Information quality
Journal
Volume
Issue
ISSN
50
1
0378-7206
Citations 
PageRank 
References 
6
0.47
54
Authors
4
Name
Order
Citations
PageRank
Helen-Tadesse Moges1121.59
Karel Dejaeger229210.10
Wilfried Lemahieu317123.09
Bart Baesens42511145.52