Exploring privacy-preserving data analysis
Many of our clients in the automotive sector face a multitude of obstacles when sharing data. These clients need an effective solution to protect their customers’ privacy while leveraging metadata to optimize products and improve user experience. The same is true for many actors outside of the automotive sector as well.
Protecting customer privacy remains a crucial issue for corporations of all sizes. The growing scale of digital operations now grants companies vast quantities of consumer data, which can unlock insights into their preferences and behaviors as well as power the next generation of innovations.
Consumers, CEOs and government regulators are rightfully concerned about the privacy of raw data and how it is used and processed. To protect consumers and shield corporations from liability, governments worldwide have instituted a number of data privacy laws and regulations. Many regard Europe’s General Data Protection Regulation (GDPR) as the global standard, which sets safeguards and mandates that personal data must be “processed lawfully, fairly and in a transparent manner in relation to the data subject”. One such safeguard is related to techniques that prevent the identification of individuals. However, once the possibility of identifying an individual either directly or indirectly is removed, GDPR no longer applies to that data.
Other regions have modeled similar rules of consent inspired by GDPR, including California’s Consumer Privacy Act and the China Personal Information Protection Law. Just like with GDPR, these regulations do not mention any specific technologies to safeguard individuals.
