Digital fraud and security risks are a constant concern for businesses, especially as criminals find new ways to exploit vulnerabilities in emerging technologies and channels. Data breaches, in particular, pose a significant threat, with millions of customer records being breached each year. Even password managers, once seen as a secure solution, have become vulnerable targets. The rise in fraud and identity theft has resulted in billions of dollars in losses, a trend that continues to increase year after year.
To compound the issue, businesses are facing new challenges brought about by hybrid work policies, automation and IoT implementation, social and metaverse commerce, and other emerging trends. These trends are adding complexity to the technology and channel attack surface, making it even more crucial for businesses to prioritize their cybersecurity efforts. However, organizations often face a shortage of cybersecurity talent while also re-evaluating their spending in the face of global economic growth slowing down. This makes it imperative for security and risk management leaders to identify the specific risks their companies face and effectively communicate those risks to justify investments in technology and talent.
To address these challenges, security executives are increasingly turning to cyber-risk quantification (CRQ) as a way to gain a better understanding of their holistic risk profile. CRQ helps in planning security improvements, preventing data breaches, mitigating compliance penalties, combating fraud, and protecting customer trust. It also provides the metrics necessary to demonstrate the risks associated with underinvestment in security to board members and the C-suite.
Gartner describes CRQ as any risk assessment that measures risk exposure and expresses it in financial or business-relevant units. The level of complexity involved in CRQ can vary, from a simple scale that ranks the likelihood and potential cost impact of specific risks to AI-enabled statistical modeling and continuous risk analysis. By 2024, 68% of security decision-makers plan to implement CRQ that incorporates artificial intelligence (AI) and machine learning (ML), according to a report.
The biggest advantage of CRQ is that it helps bridge the gap in understanding between security leaders and the C-suite. In 2021, only half of IT leaders believed that their organization’s executives “completely understand cyber risks.” By quantifying risk in financial terms and using benchmarks and key performance indicators (KPIs), CRQ enables IT leaders to demonstrate the value of security investments and frame them as measures to protect and even drive growth. It becomes an essential part of delivering business outcomes, as stated in Deloitte’s Global Future of Cyber Survey.
When implementing CRQ, leaders have several frameworks to choose from. The Factor Analysis of Information Risk (FAIR) is the best-known option, expressing risk in financial terms to provide all stakeholders with a common understanding of risk. On the other hand, the NIST Cybersecurity Framework (CSF) is a federally sponsored evaluation tool for assessing risk across organizations. It has been adopted voluntarily by organizations in critical infrastructure and manufacturing. Other frameworks, such as those published by ISACA and MITRE, can also aid in comprehensive risk identification but do not express it in monetary terms.
Implementing CRQ using existing frameworks can be time-consuming and data-intensive. To overcome these challenges, new CRQ vendors offer automation and analytics tools, which expedite data collection and analysis. These solutions provide faster risk insights, quantify existing risk, describe the return on investment (ROI) of current security investments, prioritize risk remediation, and build cases for new investment.
As the CRQ space continues to evolve, Forrester advises selecting solutions that support specific use cases rather than relying on one-size-fits-all providers. Proof-of-concept should focus on a single use case to prove value related to a specific decision that needs to be made. This approach allows for flexibility and the ability to choose different vendors or expand the use of CRQ tools as needed.
Each quantitative analysis conducted using CRQ can establish benchmarks for progress in terms of risk reduction and ROI. This enables IT teams to track and report on progress, providing tangible evidence of the value and effectiveness of security investments. As CRQ solutions become more mature and comprehensive, security leaders will have even more options to evaluate and describe risks, make plans to reduce those risks, and advocate for investments that protect their organization.
In conclusion, CRQ offers a new way for organizations to understand their cybersecurity risks and communicate them effectively to stakeholders. By quantifying risk in financial terms, IT leaders can demonstrate the value of security investments, drive growth, and prioritize investments to protect their organization effectively. With the help of automated CRQ solutions, businesses can gain risk insights faster and make informed decisions to mitigate risks and safeguard their operations in an increasingly digital and interconnected world.