87% of organizations’ financial crime risk management processes and systems are only, at best, ‘somewhat,’ efficient. Poor data quality, disparate data sources, manual matching & screening processes and the high rate of false positives are one of the leading causes of poor compliance with AML regulations.
But firms have limited choices. Most AML match programs are unable to catch deeply buried duplicates. Worse, matches result in high false-positive rates, further burdening teams with verification tasks and looming compliance risk.
This is a comprehensive guide on the processes and technologies that firms can implement to safeguard their data against AML compliance risks. It also includes information on how Data Ladder’s one-stop solution can be used to resolve critical challenges of AML name matching.
Data Ladder’s visual approach for business users is cutting-edge. The visual interface and well thought-out options make for simple and effective data cleansing implementations.
Ted Friedman, Gartner – Author Magic Quadrant for Data Quality Tools