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How Continuous Control Monitoring Software Transforms Cyber Risk Operations

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In a world where automation is taking over fast food, driving, package delivery, and practically every other industry, why isn’t it more prevalent in cybersecurity? Risk and compliance management has somehow fallen to the wayside for a sector inundated with cutting-edge technology in almost every other aspect. In response to this cybersecurity pain point, continuous control monitoring has entered the market as a method for automating the monitoring of cybersecurity controls’ effectiveness and relevant information gathering in near real-time. 

Cyber professionals are under more pressure than ever to support a new set of technologies in digital transformation, all while still maintaining the previous systems. With new responsibilities constantly being foisted upon them, it becomes even more impractical to expect cybersecurity leaders to manually assess internal controls and risk management.

According to Gartner, Continuous control monitoring (CCM) is a set of technologies to reduce business losses through continuous monitoring and reducing the cost of audits through continuous auditing of the controls in financial and other transactional applications.

Immense Time-Savings with Continuous Control Monitoring Software

A reactive approach in the ever-changing digital landscape of cybersecurity is no longer enough. Manually sifting through spreadsheets to determine compliance when the result may no longer be relevant when the assessment is through wastes thousands of hours of resources that could be spent elsewhere.

There is a simple solution: automation. Specifically, AI-assisted automation gives business leaders insight into real-time risk monitoring and assessments.  This approach mitigates control gaps and reduces the overall cost of audits. 

Teams that monitor risk must become aware of the changes that can happen minute to minute in an agile environment. Everything needs to be supervised and evaluated, whether that environment is product releases, financial information, or sensitive client information. This constant assessment isn’t practical for companies to manage with manpower alone. Humans are fallible, and it becomes much easier to have gaps in security without a continuous auditing process that leverages automation to achieve its goals. 

It doesn’t help that this data is often modular or siloed, existing in several different places that don’t communicate with one another. This makes it difficult when a breach does happen because it doesn’t allow CISOs or higher-level executives to make decisions based on aggregated data and insights. When data breaches happen in seconds, manual monitoring can make or break a situation when it takes hours to decide. It also highlights a critical weakness in business processes and internal auditing procedures. 

It will always be a consistent struggle to maintain control monitoring with legacy approaches and legacy IT GRC systems. 

AI-fueled Automation

AI is a buzzword that’s thrown around a lot, especially in cyberspaces. When we discuss AI here, we’re not talking about a system that sends emails when controls are out of date or texts when compliance hasn’t been met. Instead, we’re talking about real-time monitoring that continuously updates. 

At an operational level, automated control monitoring addresses risk in a way that allows executives to allocate resources in a way that will yield the greatest return on security investment. Siloed data only cripples control monitoring strategy and doesn’t allow for the transparency necessary to address security from a risk-first approach

Automation Creates Space For Innovation

Modular systems and siloed data encourage fractured thinking and, thus, fractured teams. If business leaders could focus less on manual risk operations, it would leave room to allocate more resources and personpower to other projects to further company goals and objectives. Investing in other areas of the business and other departments becomes easier with resources freed up. 

Automation reduces costs, saving members of the Fortune 500 million annually with options to reduce business losses in case of a breach. The use case for AI is clear for modern enterprises. Embracing the need for AI operationalization will shift the focus to continuous automated monitoring. Business leaders must focus on technologies like CyberStrong that bridge the gap between siloed systems and augment existing systems.

Conclusion 

Continuous control automation is for the future of cyber. By 2023, Gartner predicts that 30% of large enterprises will be using artificial intelligence for IT operations technology exclusively to monitor the nonlegacy segments of their IT estates, up from 2% in 2018.

To bring continuous control automation to your organization, request a demo.

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