Business and government leaders face an increasingly delicate balance between protecting customer privacy and using data to create innovative products and services.
Vast amounts of data are used by businesses across the world to understand customers’ wants and needs. Data is a source of insight for businesses to innovate their operations, products and services.
However, with increased regulations and consumer concerns at an all-time high, data sharing governance is a must. With the latest technology it’s possible to match datasets without exchanging PII, offering businesses accurate insights and protecting customer privacy.
Customers’ expectations of the privacy of their personal data are higher than ever following Facebook’s Cambridge Analytica scandal and other highly publicized data leaks. Consumer privacy laws have also become more onerous. The impact of the European Union’s General Data Protection Regulation (GDPR) is being felt across the globe. The California Consumer Privacy Act may have a similar effect.
In particular, privacy laws commonly require organizations to protect customers’ personally identifiable information (PII), such as names, contact details, and dates of birth.
Businesses have to find a balancing act: businesses need to access and analyze data to boost innovation. Protecting customer privacy and PII is also an imperative to ensure compliance with law and regulation and maintain consumer trust.
When data is exchanged between two organizations, data matching can determine if the database’s records refer to the same person.
Of course, to comply with many privacy laws—and maintain your customers’ trust—PII must be protected when matching datasets. There are several solutions designed to do this, such as do-it-yourself encryption techniques and centralized data-exchange services.
However, these techniques and services generally involve some risk, such as PII reidentification. They often require sensitive data to be kept in a central ‘honeypot’, providing a tempting target for hackers. Furthermore, businesses lose visibility of their data after it’s shared, unable to determine the use or misuse of datasets once they are exchanged with another entity. These solutions also typically require some type of compromise, such as having to choose between data security and data utility.
Data Matching with a Difference
Data Republic addresses the shortfalls of other data-matching techniques and services. It differs from other solutions in the following important ways:
- The organization contributing a dataset for exchange always has full control over its data.
- PII is never shared—in fact, the raw PII never leaves the organization that owns the data through the unique Contributor Node technology.
- PII is protected and datasets are anonymized using the proven techniques of tokenization, salting, and hashing. But Data Republic goes further by ‘slicing’ the hashed PII, and encrypting and distributing tokens on different ‘nodes.’ So, unlike most data-exchange services and techniques, Data Republic’s architecture is decentralized, ensuring there’s no honeypot.
- Datasets are accurately matched using tokenized individual records, so data analysts can be confident in the quality of the matching and the data itself. The hashed and sliced PII is never revealed.
- Data Republic’s platform includes several data-governance controls, such as data auditing. This allows businesses to better manage risk while maximizing the utility of the shared data asset.
Furthermore, Data Republic’s platform provides a unique suite of tools to help organizations discover new sources of data, scale their analytics capabilities, and become data-driven businesses—while ensuring their customers’ PII is not compromised.
Innovating with data-driven insights
Once you are assured that you are protecting customer privacy, the possibilities for boosting innovation are almost endless. Everyone knows about Airbnb, Amazon, Facebook, Google, Netflix, and Uber—all innovative businesses built on mountains of data. But there are many other lesser-known disruptors. Geografia, for example, taps into detailed (but anonymized) bank transaction data to help businesses and government agencies make planning, policy, investment, and economic development decisions.
Discover new ways your organization can boost innovation through data collaboration.