– Historically, technology tools have offered solutions that provide conclusions based on the analysis of static data and transactional data associated with specific banking activities. The different types of data vary greatly. To name a few there is big data, data from diverse legacy systems, shared file data, disparate data files from incompatible systems, incomplete data, qualitative data, numeric data, unstructured data, data using competing terminology to describe the same activities, and more. To meet compliance requirements, financial institutions, their financial crimes and compliance leaders and their respective teams must have tools to make sense of it all. To meet the high bar of compliance, financial crimes units have often relied on increasingly larger teams of people to manually comb through reams of information in an effort to address the challenges with “tribal wisdom,” professional experience, human reasoning and brute force.