Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

‍Cyber risk quantification (CRQ) is the process of translating cyber intelligence, both organization-specific and external, into measurable business terms. Typical high-level outputs include Average Annual Loss (AAL), or a business's expected financial loss from cyber events, and the Annual Events Likelihood. With CRQ, cyber governance, risk, and compliance (GRC) leaders can also drill down into more granular metrics for additional, scenario-specific context.

Financial institutions face a harsh reality. As cyberattacks have become more sophisticated and move with greater velocity, a single incident can ripple across IT systems, payment networks, and customer accounts long before the organization can respond. The problem? Most security, fraud, IT operations, and risk teams still operate in silos. Each team monitors their own consoles, works from its own data, and follows its own playbooks.

In our recent webinar featuring Enterprise Strategy Group Principal Analyst, Tyler Shields, we discussed the widening gap between vulnerabilities organizations know about and what they can realistically fix. Most teams are swamped. Too much data, too many tools, and not enough people. Naturally, automation and AI come up as potential solutions. One comment from Tyler has stuck with me since watching and subsequently reviewing the webinar recording.

Today, businesses must rethink GRC (Governance, Risk, and Compliance) to stay ahead of the game. With a proactive approach, GRC isn’t a cost center; it’s a strategy to streamline innovation at scale. We’ll discuss how to build your foundation for GRC with a proactive stance, helping you grow and protect your business.

A new era in third-party cyber risk and exposure management is underway, one that operates in real time, informed by intelligence and scaled by automation. This shift wasn’t feasible even a few years ago. The scale, speed, and complexity of today’s threat landscape—spanning thousands of vendors, assets, and attack vectors—demand more than human capacity can manage. Artificial Intelligence is the catalyst making this new model possible.

Here at Riscosity, we believe in making our users’ lives as easy as possible when using our product. Whether users are running scans, triaging results, or viewing reports, the workflows must be intuitive and a seamless part of users’ own environments. To that end, we have finished rounding out our comprehensive support for ticketing system integrations by adding Asana and Linear into the fold.

PwC recently did an AI agent survey where they found the following: This all sounds great, right? For many reasons it is, but agentic AI creates a challenge of visibility for organizations into how AI agents are communicating with each other and external third-party vendors. Imagine a multitude of AI agents autonomously exchanging data across a complex mesh of third-party vendors and applications.

‍ ‍With the continuously expanding influence that cybersecurity has in determining an organization's financial and operational resilience, cyber risk quantification (CRQ) has steadily become a foundational component of any robust cyber governance, risk, and compliance (GRC) program.