After all, cyber-crime is a big-ticket item. The average cost of a data breach in the U.S. has soared to nearly $8.6 million. At the heart of this cybercrime pandemic is ransomware. Since 2018, cyber insurance carriers report that incident-related claims increased by an astonishing 486%, the majority being ransomware-related. These trends are predicted to continue through 2021.
That’s the big picture. But every business is unique and senior executives and board members need to quantify risk as it pertains to their organization – in a non-technical way. Only then can they make informed decisions about risk management, risk mitigation, and risk transfer.
Cyber security risk modeling can help with this complex task by reshaping the conversation around cyber risk in business terms.
Let’s look at what cyber security risk modeling is, how you can utilize it, and the game-changing insights it provides.
Cyber security risk modeling is the task of creating a variety of risk scenarios, assessing the severity of each, and quantifying the potential outcome if any scenario is realized – in a language that makes sense to your business.
Cyber risk modeling should not be confused with threat modeling. Threat model frameworks help identify cyber threats and vulnerabilities and inform and prioritize mitigation efforts. On the other hand, cyber risk modeling is an efficient and repeatable means of quantifying the likelihood of a cyber-attack. With this insight, your business can make robust decisions about where to focus investment for the greatest ROI.
One of the most impactful examples of cyber security risk modeling is the quantification of cyber risk in financial terms as opposed to business terms. By establishing a universal understanding of cyber risk across your organization you can develop a more mature cybersecurity program and lead meaningful conversations on the business impact of different cyber scenarios and investments.
This analysis is not too different from the process of quantifying risk in a financial portfolio. For example, traders and portfolio managers use risk models to analyze and anticipate the impact of future events on performance so they can make preemptive decisions about where to invest funds.
Of course, any model is only as good as the data inputs and assumptions that go into it. The data must be current and accurately reflect the entire risk landscape. It’s an overwhelming task for any security team. Digital ecosystems are expanding into the cloud and across business units and subsidiaries. It would take an army of resources to identify each digital asset, assess risk exposure, and calculate what a breach would mean financially.
That’s where BitSight comes in. BitSight’s cyber security risk modeling technology doesn’t require outside consultants or long data collection processes. Your organization can develop these insights with the resources you currently have, without requiring significant data input from users or engaging external risk analysts.
Developed with Kovrr, a data-driven cyber risk modeling leader, BitSight uses data derived from real-world cyber events. We blend this data with information about the security posture of your organization’s digital assets to quantify financial risk.
The combined set of metrics delivers actionable analysis of cyber risk exposure across your business units, subsidiaries, and even M&A targets. And because no two risk scenarios are the same, you can simulate hundreds of thousands of events – ransomware, supply chain attacks, and more – and view the financial impact of each. You can also use these insights to diagnose the underlying vulnerabilities that impact financial exposure and inform what actions will deliver the greatest cyber risk reduction.
Because risk is constantly evolving, the financial quantification analysis is available on-demand and is easily repeatable so that you can measure risk exposure over time.
BitSight’s cyber security financial quantification models also change the conversation about cyber security at an organizational level by analyzing different loss scenarios – bridging the gap between the SOC and business leaders.
By transforming the technical side of cyber security into financial language, you can guide discussions around cyber risk management and prioritize and justify new technology investments. You can also measure the ROI of those investments over time by measuring how your financial exposure changes as you improve areas of your organization's security posture.
Ultimately, a greater understanding of cyber risk strengthens your board of directors and organizational leadership’s ability to deliver better and more secure business outcomes for your investors, business partners, and customers.
Interested in learning more about how Financial Quantification with BitSight empowers you to streamline your process for quantifying risk, provide game-changing insights to business leaders, and make more informed decisions? Check out our ebook: Establishing a Universal Understanding of Cyber Risk With Financial Quantification.
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