Approved IAR CE Courses

This course provides students with knowledge and understanding of the threats and problems created by money laundering and how money launderers operate—including their techniques. Students will learn the laws, rules, and regulations that have been put in place to combat the problems. They will also learn their role in identifying signs that money laundering is taking place and their responsibilities once they have recognized unusual and suspicious activities.

This course explains the SEC's purpose behind passing Reg BI and includes details on the essentialterms and definitions. Readers will examine how Reg BI applies to the relationships that firmsestablish with retail customers and also how to identify when a recommendation is being made tocustomers. Since providing the Client Relationship Summary (Form CRS or Form ADV Part 3) is a new requirement, the course will examine the questions that are asked on the form as well as thelinks that are included for clients to obtain more information about their financial services firm.Finally, the course will analyze the SEC's guidance related to conflicts of interest that firms mayexperience with their clients and, through situational examples, how the firms can be certain thatthey're acting ethically.

An increasing volume of research is making clear what financial planners have long known - thatclients do not always act in a purely rational manner. But it's one thing to recognize that clientssometimes make irrational decisions, and another to really understand what drives those decisionsand how to help clients avoid the most damaging mistakes. In this session, advisors will learn what the behavioral finance research has shown about our not-always-rational decision-making process,and how to consider making adjustments to the delivery of their financial planning services to helpclients achieve more desirable outcomes through better communications and enhanced trust.

This course explores the integration of artificial intelligence and machine learning into investment research, portfolio construction, and risk management. It addresses both the practical uses and ethical challenges of these technologies, emphasizing fairness, transparency, and the importance of human oversight in AI-driven decision-making.