Approved IAR CE Courses

This course develops the investment adviser representative's professional
responsibility toward older and vulnerable clients. It establishes why senior
protection is a fiduciary obligation rooted in the duty of loyalty rather than
a compliance topic, maps the exploitation landscape and its warning signs,
sets out the legal framework built to let advisers act on suspicion, and then
works the hardest problem the subject presents: what loyalty requires when
protecting a client means acting against that client's stated wishes.

It is written for advisers who already hold the foundational knowledge of
their fiduciary duties and who serve clients at or near the decumulation
phase, where a loss cannot be recovered through future earnings. Three
extended case studies carry the analysis into practice.

This course develops the investment adviser representative's ability to manage
investment decisions for after-tax outcomes. It builds a working model of how
investment income is taxed under current law, then works through the
tax-management toolkit — asset location, loss and gain harvesting, vehicle
selection, charitable giving, and Roth conversions — quantifying each
technique rather than asserting its value, and closes on the process and
professional boundaries that govern tax-aware advice.

It is written for advisers who already understand portfolio construction and
who serve clients holding assets across taxable, tax-deferred, and tax-free
accounts. Content reflects federal law as of the 2026 tax year, including the
individual-investor provisions of the One Big Beautiful Bill Act of 2025 and
the IRS inflation adjustments published in Revenue Procedure 2025-32.

This course examines what fiduciary duty requires when investment adviser
representatives use artificial intelligence. It grounds enrollees in how the
major tool categories actually work — large language models, meeting
notetakers, robo-advisory algorithms, and predictive analytics — and then
examines each through the duties of care and loyalty, covering confidentiality
when client data enters an AI system, reliance on output that may be
fabricated or stale, conflicts embedded in optimization targets, honesty about
AI capabilities, and the supervision and recordkeeping that make AI use
answerable.

Every module pairs the technical mechanics with the ethical analysis, and the
course is built on the premise that technology changes how advice is produced
but not what the client is owed. It is written for advisers who already work
with AI tools, deliberately or otherwise, and who carry personal
responsibility for advice those tools help produce.

This self-study course provides a comprehensive exploration of ethical considerations in investment adviser fee structures and compensation models. It emphasizes the principles of transparency, fairness, and fiduciary duty in disclosing compensation practices to clients. The course examines common fee structures, conflicts of interest arising from revenue sharing and 12b-1 fees, and outlines best practices for clear and complete disclosures. Through case studies, regulatory guidance, and ethical frameworks, participants will strengthen their ability to align compensation models with fiduciary obligations and client trust.

This course prepares investment adviser representatives to analyze, recommend,
and monitor alternative investments as fiduciaries. It surveys the major
alternative asset classes and their return drivers and risks, then covers the
mechanics that distinguish alternatives from registered securities —
eligibility standards, offering exemptions, the subscription-to-exit
lifecycle, valuation of illiquid holdings, and layered fees — and turns that
product knowledge into practice through client-fit analysis, sponsor and
offering-document due diligence, and red-flag recognition in private
placements.

It is written for advisers whose clients are encountering private markets
through retail access vehicles, inherited holdings, or direct solicitation.
Content reflects federal law and regulatory posture as of mid-2026 and
distinguishes throughout between what is in force and what is proposed.