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In this use case, Oblivious partnered with an insurance company to tackle a common tension between data privacy and utility: how to retain meaningful insights from personal data while complying with legal requirements to delete it. By applying Differential Privacy, the organization can preserve actuarial insights without violating global privacy laws, generating differentially private statistical […]

Mastercard’s use of Fully Homomorphic Encryption (FHE) demonstrates how Privacy Enhancing Technologies (PETs) can support fraud detection across borders without compromising sensitive data. In this use case, Mastercard collaborated with Singapore’s Infocomm Media Development Authority to pilot a system that allows encrypted International Bank Account Numbers (IBANs) to be checked for fraud risk without revealing […]

This Preview highlights key findings from FPF’s forthcoming report “2025 U.S. State AI Legislation: An Examination of State Approaches to AI,” which provides a data-driven snapshot of enacted and key AI bills affecting the private sector, organizes activity into distinct approaches, and helps stakeholders understand emerging trends and obligations. As AI technologies rapidly integrate into […]

In the U.S., state lawmakers are seeking to regulate various pricing strategies that fall under the umbrella of “data-driven pricing”: practices that use personal and/or non-personal data to continuously inform decisions about the prices and products offered to consumers. Using a variety of terms—including “surveillance,” “algorithmic,” and “personalized” pricing—legislators are targeting a range of practices […]