Blog Post
May 30, 2023
The B2B landscape has seen a rapid shift towards digitalization, which makes cyber exposure management increasingly critical for companies in every sector and across all geographies. A pivotal aspect of managing cyber exposure is the ability to quantify the impact of cyber risks, which is traditionally a laborious task. This article describes how data integration is the key to unlocking quick and accurate cyber risk financial quantification.
It is a common misconception to perceive the process of cyber risk financial quantification as tedious, long, and very expensive from both time and money perspectives. This perception stems from the fact that many cyber risk quantification solutions work by necessitating that users manually input all relevant data by answering a comprehensive and lengthy questionnaire.
Requiring such an extensive questionnaire makes sense given the need to intimately understand an organization and its processes in order to accurately assess the potential financial damage of a cyber event. However, in recent years there has been an increase in tools that protect, map, monitor, and manage organizational networks. SIEM, EDR, and vulnerability management solutions are three familiar examples.
These tools, and others like them, present an opportunity for speeding up cyber risk quantification because the data that the tools produce is exactly the data needed to understand an organization’s network and assess its risk. Integrated data is automatically validated given that it comes straight from a tool rather than being manually inputted, where the CISO or other stakeholders can make a mistake. Integrating with the output of these tools facilitates cyber risk financial quantification risk assessments without relying on manual user input.
Using vulnerability tools as an example can clarify how exactly data integration streamlines cyber risk quantification. Vulnerability management tools map all the existing vulnerabilities that exist in a network alongside the possible mitigation steps to eliminate the vulnerability.
To get accurate calculations, cyber risk quantification needs two types of data:
The vulnerability data from a vulnerability management tool easily translates into a more general exposure parameter. An integration-based cyber risk quantification platform can then infer a probability parameter from this exposure parameter to calculate the probability of an attack. Obtaining severity data starts by using the specific vulnerabilities that the vulnerability management tool provides and then deducing which specific events the company is in danger of being hit by (e.g. outage events vs data leak events).
Here are some more specific benefits of data integration in managing and quantifying cyber risk exposure.
When performing a cyber risk quantification without using any integration, calculations depend on data that is provided by users (usually members of the risk team) filling in questionnaires. A problem with this approach is the subjective nature of questionnaires. Thus subjectivity arises for two reasons:
In an integration-based approach to cyber risk quantification, the data is free of any subjectivity. Inputs to the model get strictly based on automatically collected data from various security and network tools. This approach provides the most opinion-free and solid ground for financial risk quantification.
Integrations with different cyber security platforms, such as asset management and attack surface management solutions improve visibility by creating an accurate and up-to-date view of a company’s technological structure as well as its current security posture. Each integration allows a different view of the organization, which is critical for understanding a company’s cyber risk posture.
Kovrr’s model maps out the asset grouping structure of an organization and analyzes how cyber events might start and propagate within the organization. The platform uses the latest cyber security data like potential vulnerabilities and threats to adjust the frequency and severity of different types of cyber attacks in the model. Examples in the platform include:
Integrating data from various sources can significantly streamline business workflows by automating data synchronization and reducing the need for manual data entry. This efficiency boost enables companies to save time and resources while also minimizing the risk of human error that could lead to data breaches or other security issues. By automating data exchange between systems, businesses can focus on their core operations, thereby enhancing overall productivity and reducing cyber exposure.
Users can leverage Kovrr’s integration wizard to enable an easy data onboarding process that requires only read-only permissions. This seamless integration with other data sources provides on-demand financial quantification of your cyber risk exposure.
Data integration also strengthens data security. By consolidating disparate data sources into a single platform, companies can more effectively monitor and control access to sensitive information. This unified approach reduces the risk of data breaches and unauthorized access, ultimately helping businesses minimize their cyber exposure.
Being proactive and taking advantage of such a modern solution to improve the organization's cybersecurity posture also helps CISOs to enhance their company's reputation for security. This reputation for using the most innovative approaches to strengthening data security helps build trust among customers and partners.
Kovrr’s system-wide approach to data through integrations allows additional capabilities that utilize the richness of partner data. You then get additional insights and indicators via secondary data points relating to vulnerabilities and security scores that are associated with each asset through your chosen integration tool.
Data integration eliminates data silos, which allows companies to maintain up-to-date, accurate, and consistent information across multiple systems. As a result, businesses can make more informed decisions based on reliable data, thereby reducing the risk of errors and potential security vulnerabilities that could lead to cyber exposure.
CISOs in particular have a lot of dashboards and data they need to fill and collect. Once you are using existing data you are helping to consolidate and remove data silos. This consolidation reduces clutter, cuts costs, and improves efficiency.
The solution has the capability to refresh the data integration as often as you wish and re-run the financial quantification based on updated inputs. This makes it easier to track the evolution of your cyber risks over time at a cadence that matches your internal requirements. Furthermore, the ability to refresh as often as daily gives you highly relevant results.
Furthermore, as regulations around data protection and privacy continue to evolve, companies need to stay compliant to avoid costly fines and reputational damage. By removing data silos, data integration helps organizations better adhere to regulatory requirements. Centralized data management provides a single source of truth, while simpler tracking and reporting are key to helping you maintain compliance.
By implementing a robust data integration strategy, businesses can enhance data security, improve data quality, streamline workflows, maintain regulatory compliance, and gain valuable insights. In today's data-driven world, data integration is no longer a luxury—it's a necessity for B2B companies looking to safeguard their valuable information and maintain a competitive edge in the digital marketplace.
The majority of our clients opt to use integration capabilities, with the most popular integration partner being Microsoft (through integration with Microsoft Defender). However, we support a whole range of integrations including Tanium, Axonius, and ServiceNow to name a few, with even more coming soon.
To get started with the data integration process, contact our cyber risk experts today.
Kovrr financially quantifies cyber risk on demand. Our technology enables decision makers to seamlessly drive actionable cyber risk management decisions.
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