Gartner defines the anti-money-laundering (AML) solutions market as the IT systems used to comply with the set of regulations, policies, and procedures designed to detect, prevent, and report those financial crimes that are associated with money laundering. Money laundering is the process used by criminals and criminal organizations to disguise illicitly obtained funds as legitimate revenue through the use of payments and funds transfers that exploit “money mules” and shell/holding companies. AML tools aim to prevent bad actors gaining benefits from their illegal activities and to combat crimes such as drug trafficking, tax evasion and human slavery.
Gartner defines augmented data quality (ADQ) solutions as a set of capabilities for enhanced data quality experience aimed at improving insight discovery, next-best-action suggestions and process automation by leveraging AI/machine learning (ML) features, graph analysis and metadata analytics. Each of these technologies can work independently, or cooperatively, to create network effects that can be used to increase automation and effectiveness across a broad range of data quality use cases. These purpose-built solutions include a range of functions such as profiling and monitoring; data transformation; rule discovery and creation; matching, linking and merging; active metadata support; data remediation and role-based usability.