AI & Technology in Financial Services

The practical guide to AI in financial services. From robo-advisors and algorithmic underwriting to compliance automation and regulatory guidance — understand what AI can and cannot do for your practice.

6 Units

20 minutes per unit

Curriculum Map

What You Will Learn

AI in Practice

Move beyond hype. Understand specific AI applications in compliance, research, client communication, and underwriting — with realistic capability assessments.

Regulatory Landscape

SEC, NAIC, and state regulators are rapidly developing AI guidance. Know what is required, what is coming, and how to stay ahead.

Strategic Adoption

Future-proof your practice. A framework for evaluating AI tools, managing risk, and building competitive advantage without violating fiduciary obligations.

All Units

20 minutes

AI in Financial Services: Capabilities and Limitations

A practical overview of artificial intelligence capabilities and limitations for insurance producers, investment adviser representatives, and financial planners — separating genuine utility from marketing hype.

•Distinguish between narrow AI, machine learning, and generative AI as applied to financial services
•Identify the specific tasks AI can and cannot reliably perform for financial professionals today
•Recognize the regulatory significance of AI hallucination, opacity, and data dependency

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20 minutes

Robo-Advisors, Algorithm-Driven Underwriting, and Client-Facing AI

An examination of client-facing AI applications — robo-advisors, algorithmic underwriting, and automated client service tools — and the regulatory framework governing their use.

•Explain how robo-advisory platforms construct and manage portfolios using algorithmic models
•Identify the regulatory obligations that apply to algorithm-driven underwriting in insurance
•Evaluate the risks and benefits of client-facing AI tools including chatbots and automated recommendation engines

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20 minutes

Using AI for Compliance, Research, and Client Communication

Practical guidance on deploying AI for compliance monitoring, tax and regulatory research, and client communications — including verification protocols and supervisory requirements.

•Identify appropriate and inappropriate uses of AI for regulatory compliance tasks
•Apply verification protocols when using AI-generated research in client-facing work
•Describe the supervisory requirements for AI-assisted client communications

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20 minutes

Regulatory Response: SEC, NAIC, and State Guidance on AI

A comprehensive review of the regulatory landscape governing AI in financial services — from SEC enforcement actions to the NAIC Model Bulletin to state-level AI legislation — and what each means for practicing professionals.

•Summarize the SEC's enforcement posture and examination priorities regarding AI in investment advisory services
•Explain the NAIC Model Bulletin's requirements for insurer use of AI systems
•Identify state-level AI regulations affecting insurance producers and financial advisors

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20 minutes

Ethical Considerations: Bias, Transparency, and Fiduciary Duty

An examination of the ethical dimensions of AI in financial services — algorithmic bias, transparency obligations, data privacy, and the intersection of AI capabilities with fiduciary and suitability duties.

•Analyze how algorithmic bias can produce unfairly discriminatory outcomes in insurance and investment services
•Evaluate the tension between AI efficiency and the professional's duty of transparency to clients
•Apply fiduciary and suitability standards to scenarios involving AI-generated recommendations

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20 minutes

Future-Proofing Your Practice: Strategic AI Adoption

A strategic framework for adopting AI in financial services practice — from vendor evaluation to governance policies to ongoing compliance monitoring — designed for practitioners who want to use AI responsibly and effectively.

•Develop a framework for evaluating AI tools against professional and regulatory requirements
•Identify the stages of AI adoption and their associated compliance checkpoints
•Create a practical AI governance policy appropriate for a financial services practice

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