Solutions for monetizing data safely start with makingdata safe to share

Differential privacy masks individual entries without significantly altering overall patterns and insights.DP unlocks new revenue streams without compromising compliance with privacy regulations.



Why is differential privacy the best fit for privacy-compliant data monetization?

Differential privacy is a technology that prioritizes individual privacy while enabling businesses to analyze, share, and monetize aggregated data insights. It helps companies balance data use for growth with strict data protection laws, supporting ethical and secure data strategies. Businesses can offer aggregated insights without compromising user information, maintaining trust and compliance with privacy standards. By focusing on aggregated data, businesses can offer insights without compromising individual user information, maintaining trust and compliance with global privacy standards.

For example, differential privacy allows for the safe anonymization of transaction data for market research or the development of risk models for financial institutions, thereby protecting customer privacy. In the healthcare sector, it specifically enables the sharing of aggregated data, such as trends in disease occurrences or the effectiveness of certain treatments, rather than individual patient records. This ensures that sensitive personal health information, like drug history or test results, is not disclosed, in compliance with privacy laws such as HIPAA. By using differential privacy, organizations can ethically use sensitive data to generate valuable insights, opening new opportunities for innovation and revenue, even under stringent data regulations.



Compliance and risk mitigation

Align with global data protection laws. Reduce the risk of data breaches and misuse.


Data utility

Share more data, enable more insights, and monetize data by offering aggregated insights to third parties.


Innovation and market competitiveness

Open new opportunities for ethical and secure data monetization.


Dr. Rachel Cummings
Associate Professor
Columbia University
“If you focus on privacy and make it a priority, in the end it leads to better data that can be monetized.”
“Are You Afraid of Data? Balancing Privacy and Data Monetization”, CPO Magazine


Differential privacy supports significant additional solutions for your organization.

Unlock new data collaboration opportunities with clean rooms

Facilitate secure multi-party collaboration, including joint research and analysis.

Assure safe internal data sharing and reuse

Reduce the data governance burden with rapid, safe production of statistical summaries for internal users of sensitive data.

Systematize disclosure avoidance

Safeguard sensitive information; reduce the risk of privacy breach.


How does differential privacy enable safe data monetization?


Differential privacy makes it possible to aggregate and anonymize transaction data to provide insights into spending habits for market research firms or develop risk assessment models for lending that are sold to other financial institutions, all while ensuring the privacy of their customers' data.

What types of data can we monetize using differential privacy?


In banking and finance, types of data that can potentially be monetized using differential privacy include aggregated transaction data, consumer spending patterns, credit risk assessments, and market analysis reports. In healthcare, types of data that can be potentially be monetized using differential privacy include anonymized patient health records, aggregated treatment outcomes, epidemiological study data, and healthcare service utilization patterns.

How do we balance data utility with privacy when monetizing data?


Balancing data utility with privacy when monetizing data involves carefully selecting differential privacy parameters to ensure data is sufficiently anonymized while retaining its value for analysis and insights. This requires iterative testing to find the optimal level of noise that protects individual privacy without significantly degrading the data's utility for decision-making and monetization opportunities.

What are the legal implications of using differential privacy for data monetization?


Implementing differential privacy for data monetization aligns with data protection laws like GDPR, mitigating legal risks. It offers a framework to ensure that data sharing and analysis practices meet regulatory requirements for privacy protection, potentially mitigating legal risks associated with the misuse of personal data. However, organizations must remain vigilant in their application of differential privacy to ensure they do not inadvertently violate privacy laws.

Unleash the power and value of your data.