Data protection startup Anonos raises $50M for PII anonymization

Data protection startup Anonos raises $50M for PII anonymization

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For all too many organizations, processing customer data has become as much a legal liability as it is an asset. While gathering and processing personally identifiable information (PII) can help unlock new insights, it also leaves the door open to costly compliance liabilities. That is, unless an organization has a solution to anonymize it. 

Data protection provider Anonos, which today announced it has raised $50 million in growth financing from Aon and GT Investment Partners, has attempted to address these challenges by building a platform to obfuscate PII. 

Anonos’ Data Embassy solution uses a combination of statutory pseudonymization, synthetic data and other computation techniques to protect customers’ identities by unlinking personal data from direct and indirect identifiers, such as the user’s name or address. 

This approach aims to balance data utility and protection concerns, to ensure that enterprises can process PII for data analytics, artificial intelligence and machine learning purposes without violating regulations such as the General Data Protection Regulation (GDPR) and Schrems II

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Surviving data protection perils through de-identifying 

The announcement comes as organizations have found it increasingly challenging to process and gather insights from their data without falling afoul of data protection regulations.

One of the most notable examples of this occurred earlier this year when Meta warned it might be forced to withdraw its services from Europe due to uncertainty over the legality of EU-U.S. data transfers. 

In the current regulatory climate, any exposure of PII data can be extremely financially damaging, as Morgan Stanley Smith Barney learned after receiving a fine of $35 million for failing to properly dispose of PII data from approximately 15 million customers.

More and more organizations are finding that collecting and processing PII to generate insights substantially increases legal risk. 

“Data-driven enterprises haven’t been able to use their data assets to their fullest advantage because of privacy and security restrictions,” said Gary LaFever, co-CEO and general counsel of Anonos. 

However, by removing potential identifiers from PII, organizations can continue to obtain accurate insights from comprehensive datasets while ensuring that data can’t be relinked to an individual user’s identity or device. 

To this purpose, tools like Data Embassy provide a mechanism for de-identifying personal data so that enterprises can process it in a way that’s compliant with international data protection regulations.  

“Other vendors have attempted to resolve this issue, but we believe Anonos’ 10 years of R&D on Data Embassy is game-changing for organizations that depend on accessible yet compliant and uninterrupted data supply chains,” LaFever said. “The technology’s 26 granted international patents and more than 70 additional patent assets serve as the backbone of this financing that takes us to a new level of business execution.” 

A look at the data protection market and de-identification services 

The data protection market has grown rapidly ever since the GDPR came into effect in 2018, with researchers valuing it at $49.72 billion in 2016 and projecting it will reach $119.95 billion by 2022. 

It’s worth noting that Anonos isn’t the only provider offering enterprises data de-identification capabilities. 

Google Cloud Data Loss Prevention (Cloud DLP) enables organizations to create an automated data transformation pipeline to identify sensitive data through the use of de-identification techniques like tokenization and pseudonymization. Google Cloud also announced revenue of over $6 billion earlier this year. 

Another provider attempting to address this challenge is IBM. IBM InfoSphere Optim Data Privacy uses a range of transformation techniques to mask and obfuscate PII, and integrates with the Information Governance Catalog to provide 30 out-of-the-box data classifications and 30 data privacy rules. 

IBM recently announced $15.5 billion in revenue during the second quarter of 2022. 


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