The establishment of an enterprise-wide risk management system requires, at the very least, that the existing data within the banks source systems is comprehensive and reliable. Several issues arise out of either lack of data or lack of data reliability, or both. Recognizing the need for clean and comprehensive data and to ensure that there are no surprises during implementation, we, through close interaction with the bank, conduct thorough Data Gap and Data Quality Assessments, which include:     

  • Preparation of a comprehensive list of all essential data attributes required for implementation    
  • Defining and analyzing the source systems within the bank and the frequency of data updation    
  • Field / table mapping of all metadata to the identified source systems    
  • Identifying and highlighting the gaps in data availability with varying levels of gap severity    
  • Analyzing credibility and relevance of existing data    
  • Advising the bank on the approaches to address the identified gaps