Risk Analytics Function

Group Level FCC/AML Risk Analytics Function is an essential risk-discovery and risk- mitigating component of a strong Anti Financial Crimes / AML Programme. It enables Financial Institutions to uncover and understand risks effectively and efficiently by utilizing the readily available AML/KYC/Sanctions data. We consider FCC/AML Risk Analytics Function an essential risk discovery tool that enables the creation of an enterprise level “Risk Analytics Intelligence Engine” and makes it possible for the Financial Institution to finally “connect the dots”, gain risk clarity and understand its enterprise level Risk Footprint. Enterprise Level Footprint includes Customer, Geography, Products & Services, Transactional, Activity as well as Division/Business Unite Risk and more.

Organization’s Risk Footprint however, is never static. It changes as the Financial Institution changes, as its expands into new markets, as it starts to offer new products or services. Hence FCC/AML Risk Analytics Function also enables the Organization to continuously uncover and loop in new risk findings and obtain current, accurate risk picture.

AML & Risk Analytics begins with strong data management. If done correctly, it can enable Group-Level strategic, efficient and proactive risk management as well as extraction of robust and comprehensive Risk KPIs and MIS. Not acknowledging the growing importance of data analytics may results in a lost opportunity for your Organization to advance its Anti-Financial Crimes Programme.

Our AML Compliance Risk Analytics & Risk Modeling Practice was established in 2006, same year Vesta LLC pioneered the concept of Horizontal, Enterprise-Level AML Risk Assessment and the alignment of AML Risk Assessment & its key Risk Factors and Red Flags with Organization’s AML Transactions Monitoring System and its Detection Scenarios, Models and Rules (Risk Topology Driven AML Transactions Monitoring Coverage). Our Risk Analytics methodology relies on Descriptive Source System Statistical Data Analysis for the use in Anti-Financial Crimes, Risk Based Customer & Product Segmentation Modeling as well as utilization in Predictive Analytics.