Data Completeness: A Critical Need for Regulatory Compliance and Performance Management
October 5, 2015
The collection and usage of data has continued to grow in the financial services industry, requiring banks and non-banks alike to properly ensure data is complete and accurate to meet reporting requirements. An in-depth understanding of each requirement and its business purpose enables one to identify which information is necessary to satisfy expectations. Data quality should be examined as a business-wide issue and treated with a high level of importance. Looking at data completeness from a regulatory compliance perspective provides a good benchmark for all other practices. This paper uses regulatory compliance as an example while discussing data collection and measurement.
Using the regulatory compliance example, the process starts with identifying applicable regulations for each line of business and determining which questions need to be answered in order to show compliance. This paper outlines five main steps recommended to ensure data completeness:
- Determine the end state
- Determine what constitutes “complete”
- Perform a gap analysis comparing what is required to what is available
- Layout a plan to close the gaps identified
- Close the gap on data incompleteness by executing on the plan
A well-planned, purposeful approach can prove to be powerful.
When data completeness is not a priority, the business can be negatively affected. Financial penalties can be steep when an organization does not capture all requirements. Additionally, a focus on data can help maximize profits and reduce risk by accurately presenting an organization’s performance to senior management and stakeholders.
For more detail around this topic, a full PDF version of this white paper is available for download.