Support initiatives to identify and protect sensitive data, such as PCI, PII and PHI, and designated privacy regulations, including GDPR (EU) and Gramm Leach Bliley (US)

Recent studies have suggested that the Financial Services industry has the third highest per-capita cost for a data violation. Therefore, protecting sensitive information is the right thing to do for your customers, is expensive to recover from if it happens and is a legal requirement enforced by many Governments and industry regulators as well as many country specific data privacy authorities.

Cyber security and network surveillance solutions are used to protect the perimeter but many Insurance institutions still carry the risk of a data violation due to the lack of proper protection of sensitive data in both production and development environments. With so much data flowing between systems and the proliferation of this data to often ungoverned systems, identifying and keeping track of where sensitive data is across the enterprise is challenging and often impossible to do effectively and efficiently. The problem is an ongoing one and requires Insurance institutions to be constantly aware of the potential for a violation.

Many Insurance organizations do not have a clear understanding of where their sensitive data is, especially as it proliferates internally and externally with partners. Not all Insurance organizations understand the risk associated with the use of sensitive data and the impact of proliferation.

The Informatica Intelligent Data Platform (IDP) supports initiatives in Insurance institutions to find, classify, track and risk score sensitive data in both production and non-production systems. Once sensitive data has been identified, our solution can mask that data to ensure it is used for the purposes defined by the data privacy policy. As part of data protection and data privacy initiatives, our solution supports Insurance institutions to:

• Find and classify sensitive data across the enterprise, providing insights and data security intelligence that protects sensitive data and helps comply with data privacy legislation.
• Understand data proliferation across an Insurance institution, as well as when it leaves an institution, to better under how to profile data risks for prioritization of action
• Risk score sensitive data to generate insights into what strategies and priorities must be applied to different types of data and that come from different sources
• Mask sensitive data and provide data security and privacy controls to prevent unauthorized access to, and disclosure of, it.
• Securely provision test and development data by automating data masking, data sub-setting, and test data-generation capabilities.