How Do Analytic Tools Help Operators Understand Risk?
Analytic solutions are being used to determine and manage risk in many different sectors of business, including supply chain management, e-commerce, regulatory and compliance concerns, and much more. These analytic tools can give deeper data-driven insights and give more accurate risk management suggestions and assessments than ever before.
What is GRC (Governance, Risk, and Compliance)?
According to Amazon Web Services:
“Governance, Risk, and Compliance (GRC) is a structured way to align IT with business goals while managing risks and meeting all industry and government regulations. It includes tools and processes to unify an organization’s governance and risk management with its technological innovation and adoption. Companies use GRC to achieve organizational goals reliably, remove uncertainty, and meet compliance requirements.”
Companies are far better equipped to understand and work on their GRC when they use advanced analytic tools to disseminate key performance indicators, determine key risk factors, and establish emerging risks and what kind of lines of defense to establish to remove those risks.
How Can Analytic Capabilities Help Managed Threat Detection?
- 3rd Party Apps Provide Extra Exposure to Threats, and Analytic Tools Mitigate the Threats
Since the widespread adoption of hybrid work arrangements after the global reaction to the spread of Covid-19, the adoption of 3rd party apps introduced an entirely new level of threat. The use of these thousands of apps, mixed with the current technologies that organizations were already using, created the perfect opportunity for malicious actors to make a move. Analytic tools provided threat detection that led to protocols to mitigate and remove the threats, as well as safeguard the networks.
According to a recent study by NTT
“Through machine learning, security systems can learn from data over time to become better at pattern recognition and identify threats more accurately. This can take the form of machine learning in analytics engines that are used to identify threats (so, learning from the system’s own experience) or machine learning from threat hunting by humans who look for and analyze anomalies missed by security software.”
- Applied Analytics to Third-Party Risk Management for Supply Chain Protects Against Threats
The interconnected world of global trade means that supply chains have companies connected to other companies in all sorts of industries and sectors, in different countries, all over the world. Analytic tools can help companies determine the potential risk of the supply chains they are working with (or considering working with) and the potential level of threat they may pose.
- Integrating Data is Important to Discover and Manage Potential Threats
Different data streams are being integrated to bring to light new insights that were previously undiscovered. This integration of data allows these security processes to run their course, analyzing these large streams of real-time and stored data, showcasing existing threats, and discovering new ones.
- Data Analytics Can be Displayed on Dashboards to Streamline the Threat Detection Process
Visualization tools like dashboards give security personnel better insights into the state of their security systems. Managed threat detection is aided by these types of tools and while the majority of threat hunting is done with automated systems, these dashboards aid the human analysts to see where the issues are and how to fix them if necessary.
- Machine Learning Helps to Defend Against Cyber Threats
Everything from regulatory compliance data to long-term enterprise resource planning procedures can be compromised by cyber threats. With all the endpoints in a given network, there are thousands of avenues of attack. Machine learning programs help to examine the threat surface and defend against these cyber threats.