Maximizing Data Value: The Key Distinction Between Unlocking Data and Freeing Up Its Value
Top Four Takeaways From the Fireside Chat
The accelerated pace towards cloud migration presents unique challenges for regulated industries. For instance, the insurance sector handles extensive amounts of PII (Personally Identifiable Information) and sensitive health data. To mitigate the risks that come with the shift of insurance data to the cloud, it's essential to implement robust privacy technologies.
Freeing up the data for use requires to consider technologies that address the multi-party aspect of data usage, rather than relying solely on access controls, single-step anonymization, or protection by subtraction.While it may be possible to remove direct identifiers or mask them in an enclosed environment, once the data is out in the open, it becomes susceptible to being combined with other third-party datasets to reveal sensitive information.
A more effective approach involves leveraging technologies like AWS cleanrooms and Anonos that uses Privacy-Enhancing Computation (PEC) technologies such as synthetic data, Statutory Pseudonymisation, and other protections to protect data during computation and ensure that privacy controls travel with the data.
Confidential compute environments have two primary uses. Firstly, they are utilized to to generate confidential results, as is the case with AWS cleanrooms. Secondly, they can be used to protect sensitive data during processing. To achive the protection of data in use, Anonos Data Embassy software can be deployed to create transformed and protected outputs, Variant Twins. These outputs can then be securely used and shared among multiple parties while remaining compliant with regulatory requirements.
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Head of Worldwide Business and Market Development, Life Insurance Industry