Use data to gain insights while protecting people’s privacy
Create privacy-protected datasets and reduce your risk of exposure
HIPAA, GDPR
CryptoNumerics enables you to create privacy protected datasets with quantifiable privacy risk. In addition, you can build statistical and machine learning models that protect people’s privacy.
HIPAA, GDPR
CryptoNumerics enables you to create privacy protected datasets with quantifiable privacy risk. In addition, you can build statistical and machine learning models that protect people’s privacy.
Use Cases
Financial Services
One of the largest aggregators of credit card transaction data wanted to significantly improve data utility of its assets, so it could help its business partners such as retailers, banks, and ad companies achieve better conversion on ad campaigns, improve customer satisfaction etc. All these, while complying with privacy regulations and safeguarding consumer information.
With CryptoNumerics they were able to derive the same analytical value before privacy protection was applied. Thus opening new partnership opportunities that were restricted due to privacy issues.
Life Sciences
A large healthcare network, with millions of patients, wanted to unlock patient data for research, training of new staff and improving patient outcomes. Additionally, they needed to comply with privacy regulations.
With CryptoNumerics they were able to preserve the granularity of the relevant analytical data elements while protecting all the identifying attributes, ensuring compliance.
Privacy Crash Course
Understanding the differences between Data Privacy and Data Security
This is the first blog in our Crash course in Privacy series Privacy is all over the news these days, from Facebook scandals to European fines associated with failing to comply with GDPR. This is caused in part because protecting the privacy of your customer’s data is...
read more
Why protecting sensitive data is important
This is the second blog in our Crash course in Privacy series Privacy risk is the probability of extracting information about a specific individual in a dataset. Organizations must protect the significant personal information they have from exposure.Governments around...
read more
Why masking and tokenization are not enough
This is the third blog in our Crash course in Privacy series Protecting consumer privacy is much more complex than just removing personally identifiable information(PII). Other types of information such as quasi-identifiers can re-identify individuals or expose...
read more
Six things to look for in privacy protection software
This is the fourth blog in our Crash course in Privacy series Enterprises want to:Leverage their data assetsComply with privacy regulationsReduce the risk exposure of consumer information.If the goal is to maintain data utility while protecting privacy here is a list...
read moreCryptoNumerics Team
We are a team of engineers and visionaries with previous experience in C-Level roles at Fortune 500 companies, in R&D roles at global organizations, and as founding teams of successful venture-backed start-ups.
Monica Holboke
Co-Founder & CEO/CSO
Ash Munshi
Co-Founder & Executive Chairman
Charles Marker
CTO
David Jensen
Head of Research
Peter Scholl
Cryptography Expert
Jimmy Fan
Co-Founder, Engineering
Roberto Cervantes
Co-Founder, Marketing
Hassan Bhatti
Co-Founder, Commercial
