Abstract: A method for implementing and integrating biometrical markers, identification, real-time transaction monitoring with fraud detection and anti-money laundering predictive modeling systems as the means of identifying, measuring, detecting and reporting the importance assigned to each member of a population of transactions coupled with images of participants whereby a relationship exists, or groups of relationships, by and between the transactions and the persons identified in the images and/or being affected by at least one suspicious activity factor, transaction or pattern. According to the method, an image is captured and attached to a financial transaction. An identifier is assigned to each member of the image population of persons making transactions for the benefit of one or more financial accounts. The image is cross-referenced against a cloud-based relational database of identified images, known associate persons per images and notations to purported activities and potential risk factors.