Data Loss Prevention in Compliance Driven Industries

Data Loss Prevention in Compliance Driven Industries
The Siliconreview
09 January, 2020

The news today is filled with cases of high-profile breaches of datasets and such news has continued to make headlines over the years. Recent surveys show that the first and foremost reason for compliance supervision of communications is the data loss.

Every business is a data business, sharing and using information of all kinds via the internet. The explosion in the methods of mass communication with platforms like video calling and collaborative chats through which multimedia files, documents, images and audio content can be easily shared. It has given users more effective and richer ways to collaborate with people around the world. It has also exposed businesses and people to increased risks of data disclosure from identity theft to property theft.  Proper assessment and mitigation of these risks is essential for these enterprises.  

Risk Reduction Practice:

A data loss prevention plan must exit for all high risk interaction channels present in an organization starting with a detailed risk assessment that assesses the chances for accidental or intentional loss of data. Appropriate response based on the assessment could include auditing samples recording to be categorised interactions by degree of risk.

For heavily-compliance driven industries, tools like Theta Lake can be integrated into Webex, RingCentral, zoom, GoToMeeting and similar platforms to review 100% of the communications. Combinations of pre-built custom detection policies ensure that most unsafe interactions are flagged to supervisors for manual review.

All enterprises need richly engaging communication platforms and collaboration tools in order to conduct their businesses in an orderly fashion. The fast and uniform auditing by AI solutions like Theta Lake and the discretion of human insight and appropriate juncture is a pragmatic answer to face the challenges of data loss in the omni-channel digital world.