Individualized Pricing and Data Privacy: Evolving Regulatory, Enforcement, and Litigation Risk

This CLE course will examine individualized (surveillance) pricing and the data privacy, AI, and consumer protection risks for businesses using electronic monitoring and algorithms for personalized pricing. Participants will learn how key personalized pricing models work, what personal data they rely on, and how regulators and plaintiffs are scrutinizing these practices. The program will provide practical guidance for assessing and mitigating compliance, investigation response, governance, and litigation risk, including evaluating disclosures and data and pricing policies as well as third-party vendor arrangements.

Individualized pricing or so-called "surveillance pricing" is emerging as a major privacy and legal compliance issue, drawing both federal and state scrutiny. Using electronic monitoring technology and AI, businesses now have the scaled ability to set targeted consumer prices based on the personal information collected. Algorithmic pricing is intended to maximize business revenue.

The Federal Trade Commission (FTC) and state regulators are intervening due to the scope and lack of transparency surrounding this kind of personal data collection. Their concerns include market distortions, impacts on housing, food, and retail, and potential for unfair discrimination. Consumer and privacy groups are urging more FTC intervention.

Legislators are also taking action. New York's Algorithmic Pricing Disclosure Act, N.Y. Gen. Business Law Section 349, targets undisclosed algorithmic pricing with some exceptions. Congress has also signaled interest in two pending bills, the One Fair Price Act and the Stop AI Price Gouging and Wage Fixing Act. California is taking a two-pronged approach to surveillance pricing with the California Consumer Privacy Act (CCPA) and pending California Assembly Bill 2564. More states are following suit.

Businesses using personalized pricing should assess their practices for compliance and risk mitigation. In this course, faculty will explain key pricing models and how they rely on personal data and other sources; summarize the federal and state legislative landscape; and discuss how to assess pricing and data-collection policies and comply with applicable privacy, AI, and pricing laws.  

Listen as our authoritative panel of cybersecurity, data privacy, and technology experts discusses surveillance pricing, current federal and state developments, and practical compliance and mitigation strategies. The panel will also address governance considerations, investigative response preparedness, and private litigation risk.