Mastercard’s Privacy Enhancing Technologies (PETs) white paper outlines how PETs can strengthen financial systems under attack from AI-driven fraud, identity theft, and money laundering. PETs include differential privacy, synthetic data, zero-knowledge proofs, homomorphic encryption, federated learning, and secure multi-party computation. These tools enable secure, privacy-preserving data sharing across borders and organizations without exposing sensitive information. Mastercard tested homomorphic encryption in Singapore’s PETs Sandbox, showing global financial crime intelligence sharing without data leakage. While PETs face challenges like computational cost and regulatory gaps, they promise safer collaboration. Adoption requires regulators, financial institutions, and policymakers to ali

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