A good data governance plan starts out with knowing your data, and understanding how it is used throughout the organization.
DATA MANAGEMENT
While AML data collection is all about “know your customer,” a good data governance plan starts with “know your data” or KYD. KYD means understanding how data is used throughout the organization. KYD also defines the existing documentation, processes and controls of the business and creates metadata (data about the data) to trace the origin and life-cycle of the data as it moves through various processes. Standardizing data protocols can be helpful in meeting regulatory mandates for AML and compliance.
Data management is the foundation for everything from collection and flow of information to accuracy and analytics. Institutions that take on, and succeed in the challenging task of data management will reap improvements in data quality, operational efficiency, AML compliance and risk management.
Data Governance
Data governance is a wide set of management and technical disciplines designed to ensure that an institution has the right data available at the right time and that the data is accurate and in the correct format required to satisfy specific business needs. Much like AML compliance generally, technology enables the process, but it is specific business knowledge and context being applied to a set of information that really adds the value.
Data governance is the best approach to combine the following components: sophisticated software applications, knowledge of what the customer needs, and the accurate understanding of data definitions for inputting the appropriate data. Data governance efforts are viewed well by regulators, who increasingly put pressure on financial institutions to formally document business processes, data controls, source-to-target mapping, and defend all activities around data management. Data governance frameworks should help to make data more consistent, accurate and complete thus improving data quality. Implemented correctly, a better approach to data management should also lower compliance risk, including the risk of regulatory fines and sanctions.
Data Quality 
While technology platforms are certainly enablers in supporting this governance (e.g., data quality monitoring and/or centralized data dictionaries), AML leads must work closely with first-line process owners to ensure a good definition, ownership and monitoring of key data assets required for the AML programming. Technology components supporting this include the management of master and reference data, which helps to ensure uniformity and improve quality across data sets flowing from diverse systems. From a transaction monitoring process standpoint, a single customer with multiple accounts and conducting multiple types of transactions will have the customer name, transaction details and other identifying information appear in multiple records, across multiple systems. The process of consolidating this information into a single customer record for transaction purposes (to prevent the same customer from generating duplicate alerts) can be facilitated through strong reference and master data management. The technology, a key component of AML compliance, cannot work effectively without this kind of maintenance of the information that is fed into it. This is where data governance is key.
For many organizations, meeting these expectations may seem daunting. It is, therefore, important for institutions to define their objectives clearly when designing a data governance function for AML or any other purpose, and scope the undertaking appropriately to help them achieve their specific goals of managing, protecting, ensuring quality, and, ultimately knowing their data.
Having a robust approach to data management enables clear ownership of data, enhances business rules around data activities, improves operational processes, enriches decision-making and increases collaboration. It also helps make core compliance activities quicker and easier to accomplish – reducing resources and costs, and decreases the risks associated with reporting errors and failures.
While AML data collection is all about “know your customer,” a good data management plan starts with “know your data” or KYD. KYD means understanding how data is used throughout the organization. KYD also defines the existing documentation, processes and controls of the business and creates metadata (data about the data) to trace the origin and lifecycle of the data as it moves through various processes. Standardizing data protocols can be helpful in meeting regulatory mandates for AML and compliance.
How we can Help 
Our team of experts can assist you to develop a data management program, or review your current program for efficiency and effectiveness.