Data Analysis Secrets for Compliance Professionals

This highly practical webinar will demystify data analysis, remove all of its mystery and perceived complexity, and provide attendees with tools and techniques to effectively identify unusual activity.

Why Should You Attend:

Due to budgetary constraints and lack of expertise, companies sometimes neglect this important function or relegate it to technical experts who are far removed from the subject-matter experts that need to monitor the products and transactions. On other occasions, lack of data analysis expertise by subject-matter experts leads to guesswork or knee-jerk reactions to frontline referrals of doubtful merit.

In this webinar, compliance experts, antifraud analysts and their regulators will learn how to capture the right data, build the right databases and use available tools such as Excel®. Equipped with these new skills, attendees will enter a new realm of detection and analysis possibilities that will protect their institutions from money laundering, fraud and compliance failures, and thus significantly enhance their careers.

Areas Covered in the Webinar:

• Techniques for improving data quality and preparing the data for analysis
• Selecting the most meaningful metrics (key risk indicators or KRIs) to be monitored and utilized in building transactional analysis rules and algorithms
• What algorithms are and how they are built
• Learning how to effectively use Microsoft Excel® and manipulate databases to detect suspicious activity and score transactions
• Describing the data to identify what is normal and then detect deviations from normality
• Data-driven methods for scoring transactions, customers, products and geographies
• Data visualization tools, techniques and best practices

Who Will Benefit:

• Compliance Officers
• Risk Officers
• Internal Auditors
• Operational Risk Managers
• Transaction Monitoring Specialists
• Staff with roles and responsibilities in compliance and risk management departments, as well as businesses and technology departments.