When Good Data Happen to Good People

Boosting Productivity with High-Quality Data.

Investing in data quality can provide a range of substantial cost savings by improving the productivity of the analytical risk management process. A direct correlation exists between data quality and productivity improvements within the risk management function. Poor data quality can result in:

Increased time needed to develop models

Lower confidence in the model results

Less time to actually analyze results

Need for higher capital buffers and loss allowance provisions

There are several processes available for banks to define data quality, and guiding principles that can be implemented to improve data quality. Download When Good Data Happen to Good People to learn more on the guidelines for defining a data quality framework.

Please complete this form to receive the white paper. Required fields are marked with an (*).