IT Compliance Analytics and Automation using AI.

Aug 11, 2021. By Aleena Mathew

Tweet Share Share

IT Compliance Analytics and Automation using AI

The digital era and the transformation towards digitized organizations are moving like high tide. The majority of IT organizations are opting for the adoption of digital age, clearly seeing the benefits it holds. The base architecture changed to adapt to the digital transformation. That is, traditional monolithic architecture got shifted to the distributed microservice architecture. This distributed architecture called in for more advanced governance, risk management, and compliance policies to be enforced for the smooth operation of the system. The reason for this change was that it became difficult to manage and monitor the data flow among these services. And there are many situations in which, several policy or rule violations can take place in these services. Thus making it difficult for IT operators. In such a situation, IT operators manually enforce the compliance actions with the help of traditional enforcement tools. But in the long run, holding onto these traditional tools will not benefit any longer. That is, these mechanisms will result in manual errors to occur as well as wastage of time. A new report by the IT Policy Compliance Group finds that the vast majority of businesses do not meet data-handling regulations, increasing the risk of a data breach. Also, a research study shows that the average compliance cost for organizations across all industries worldwide is $5.47 million.

In this era of automation, where every IT operation is automated with the help of artificial intelligence, the process of analyzing any compliance violation and enforcing compliance can now be automated. That's where AI-based compliance analytics and automation come into the picture. With this automation, the above-mentioned risk of a data breach or compliance cost can be drastically reduced. Let us start with AI-compliance analytics and see how it helps organizations.

AI Compliance Analytics:

The term analytics holds great value in IT organizations. With the implementation of distributed microservice architecture, the IT team had to widen their perspective of monitoring. They needed to analyze every service and understand the transaction among them. Apart from that, they needed to know, is any data breaches or any security violations have taken place. Manually carrying this process across 1000+ services is a challenging task. That's where the process of AI-based compliance analytics became implemented in the organization. With AI-based analytics, any compliance violation will be captured by the AI models. For example, if the data privacy compliance law, such as General data protection regulation(GDPR) is seen to be violated due to data breach or any other instance, the issue will be automatically be captured, and a proactive alert will be generated. The identification is carried out by AI-based anomaly detection or AI-based incident recognition. Apart from that, AI-based analytics dashboards are implemented, which enables compliance operators to create multiple tabs to monitor and see if the compliance set adheres. KPI and log-based analytics is also implemented to foresee if any violations are taking place. Further to that, we can also analyze and see if there is any industry compliance not followed, government policy violations, and so on. With this, we saw how AI compliance analytics can be implemented. The subsequent process is enforcing compliance.

AI Compliance Automation:

With the help of AI-based compliance analytics, we were able to capture any compliance violation. AI compliance automation helps in the process of automatically remediating the non-compliance risks captured. Compliance automation is an artificial intelligence technology, which is capable of identifying compliance issues and executing workflows to remediate them. For example, an IT compliance operators notice that a security breach or violation has taken place. The AI compliance analytics capture this scenario and understand that it is a security compliance violation and execute a workflow to automatically to capture the user's IP or user name and blocks the user from further accessing the application. Therefore, with compliance automation, any compliance based workflows can be generated, and upon the break of compliance these workflows will be executed. Thus intelligently ensuring the systems are adhering to the policies. Apart from that, with compliance automation we can get compliance status and audit information within a single AI-based dashboard. Also, based on compliance analytics risk management decisions can be made based on real-time data. Thus enables in the implantation of compliance policies uniform across computing platforms such as physical servers, public and private clouds.

Chief Compliance Officers are responsible for ensuring that complaints are addressed promptly as well as communicated to the board and senior management. The implementation of AI-based compliance analytics and automation enables CCO's to handle out this process smoothly. This enables to save time and operational costs. To know more about, how to enforce AI compliance analytics and automation, visit our AI dashboard page.

Share this blog.

Tweet Share Share