Fireside Chat #4:
Defending the Lawfulness & Ethics of Desired Processing

This is Doug Laney, Data & Analytics Strategy Principal at Caserta and author of the book “Infonomics: How to Monetize, Manage and Measure Information as an Asset.” I am here today with Gary LaFever, CEO and General Counsel at Anonos, to discuss an approach to “Defending the Lawfulness and Ethics of Desired Processing.”

Some people may wonder why digital insights are so important in the post-pandemic world. It's because organisations need new sources of value to replace those that have been lost, and they also need to diversify revenue streams. In addition, they need to solidify relationships with their existing customer base and improve upon partnerships via commercial data exchange relationships.

It seems to me that Anonos can help to reconcile the opposing forces of regulation and monetisation necessary to achieve these results. On the one hand organisations have new controls and regulations to contend with, which reduces their ability to derive digital insights from leveraging data assets both internally and externally. On the other hand, they have an imperative to monetise data in new and innovative ways to generate new value streams. Gary, can you explain how Anonos helps to bridge this widening divide?

Anonos data protection technology can be integrated into data lakes, into streaming data, into batch processing, or applied at the network edge, to enable decentralised data use, sharing and combining to be accomplished in a flexible and scalable way. This means that digital insights can be achieved in compliance with global data protection standards, vertical industry regulations and data sovereignty or localisation requirements. Anonos does this by combining the benefits of anonymisation, Pseudonymisation (as newly defined in the GDPR), CCPA-heightened de-identification and patented proprietary techniques. Using this combined approach, Anonos enables accurate decentralised data use, sharing and combining in compliance with regulatory and risk management requirements.

The core of Anonos' capabilities is centered around our non-identifying versions of data, called Variant Twins, which are our patented approach to controlling selective date use and disclosure.

With Variant Twins, organisations only provide the type and level of identifiable data needed for each authorised process. This aligns with modern data protection principles like data minimisation and purpose limitation. Because all Variant Twins are derived from the original source data, organisations suffer no degradation in data value or accuracy.

Variant Twins deliver resistance to re-identification of anonymous data; enable data controllers to retain absolute control over the re-linkability of their data; provide 100% accuracy; protect data in use; and activate express statutory benefits under data protection laws.

Variant Twins improve upon the statutory capabilities and benefits allocated to state-of-the-art privacy techniques like Pseudonymisation under the GDPR and heightened de-identification under the CCPA. They do so in a way that enables digital insight objectives to be achieved while respecting and enforcing the fundamental rights of data subjects as consumers in a data-driven ecosystem.

Gary, can you share a use case where Anonos technology helped to “Defend the Lawfulness and Ethics of Desired Processing”?

Doug, we are working with a European bank that is interested in using enhanced market intelligence to develop new cross-sale and upsell opportunities for existing and prospective customers. But to create useful market intelligence to generate new opportunities for clients and partners, the bank required access to timely digital insights and data use expansion.

Some of the challenges were:

• Sharing and exchanging data with partners and third parties to better serve customers and partners was necessary to create better business outcomes.
• Customer needs and expectations could not be met or understood without the data.
• Access to the data, processing and resulting insights was not lawful without enhanced data protection capabilities being put in place, but protection could not reduce data utility or enablement.

By leveraging BigPrivacy Variant Twins, the bank is able to preserve data value while enabling sophisticated risk-based decentralised processing so that it can benefit from:

• Access and use of data that they otherwise would not have.
• Enhanced accuracy in insights and market intelligence.
• Data exchange with partners for more effective offerings to customers.
• Increased availability, and improved stability, of data assets.

Contact Anonos at LearnMore@anonos.com or Caserta at hello@caserta.com for more information.