5 Steps to Clean Data and Reduce Risk
Accurate data that cannot be manipulated is crucial to preventing financial crime. If your fraud or anti-money laundering (AML) program is undermined by poor data, then your organization becomes vulnerable.
Developing and implementing a plan to support data accuracy, consistency and life cycle as part of your financial crime risk management program will help ensure risk detection and mitigation, regulatory compliance and protection from reputational harm.
Read this point of view paper to learn more about these three areas to help ensure clean data:
- Data accuracy – Ensuring the data's veracity
- Data consistency – Maintaining the integrity of data over its life cycle
- Data life cycle – Monitoring data origins and changes throughout the data life cycle (also called data lineage)
- Country
- United States
- Solution
- Financial Performance & Risk Management
- Industry
- Insurance, Credit Unions, Banks
- Published
- November 2018
