Data Quality: Is the Glass Half Empty or Half Full?
The Risk Management Association (RMA) and Automated Financial Systems, Inc. (AFS) sponsored the fourth annual survey on Enterprise Data to Support Credit Risk Management in the winter of 2010. RMA and AFS conducted the first Credit Data Quality Survey in fall 2007, when the current credit crisis just began and was thought to be limited.
Given the turmoil in the credit markets over the past several years and the resulting regulatory response, the need for accurate, timely data to make well-thought-out strategic decisions has become even more essential. Financial product innovation, globalization of capital markets, competition, transparency, and regulatory requirements continue to drive banking organization to collect broader and deeper data sets. These objectives also place an enormous strain on the legacy accounting and management information systems still prevalent in today’s large complex banking organizations.
Pulling data from disparate systems located throughout the bank—throughout the world in some cases—and feeding one or more data warehouses—all to be kept current and accurate on, essentially, a real-time basis—remains one of the biggest challenges to banking organizations.
In 2010, participants reported that the primary benefits of increasing the quality of data supporting credit risk management are:
- More timely identification of emerging problems.
- More efficient capital allocation/utilization.
- Reduced regulatory and legal risks.
- Improved transparency in reporting results to the market.
Many valuable insights are presented in this important survey. The Executive Summary of this study provides an overview. The detailed results that follow will provide you with extensive coverage of this topical, relevant study.
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