As the world continues to be more interconnected, the role of risk analysts and corporate security becomes even more important. There is always a need to be one step ahead of the latest threats. To do this, security teams rely on Risk Intelligence and the Risk Analysts who sit at the tip of the spear with vital information. Risk intelligence is information that helps organizations identify, assess, and manage risks. There are two main types of risk intelligence: traditional risk intelligence (T-R-I) and artificial risk intelligence (A-R-I). Both have their strengths and weaknesses, but when used together in a Critical Event Management platform, they can create a dominant tool for identifying and managing risks.
Global Security Operations and Traditional Risk Intelligence
Traditional risk intelligence (T-R-I) is information that is gathered manually by human analysts. It includes things like open-source intelligence (OSINT), human intelligence (HUMINT), media analysis, geo-political and financial analysis. It has been used for years and a carryover of government tradecraft and is often seen as the more reliable of the two types of risk intelligence because it comes from humans rather than machines. We can call this a legacy collection methodology but let’s not equate legacy with faulty.
There are several benefits to using (T-R-I). First, human analysts can understand context and intentions in a way that machines cannot. This allows them to see past surface-level information and identify potential risks that might be disguised. Second, because traditional risk intelligence relies on publicly available information, it is less likely to contain errors (pending source verification) or false positives than Artificial Risk Intelligence. Finally, human analysts can often act faster than machines (surprised, don’t be) because they don’t need time to process data before making decisions.
Despite these advantages, there are also some limitations to Traditional Risk Intelligence. First, it can be time-consuming and expensive to gather manually. Large corporate security teams are a luxury that most organizations can’t justify financially. Second, because it relies on public information, it might not contain everything you need to know about a particular risk. In addition, we can’t eliminate human bias, make no mistake, it factors in. Even with the best operating procedures we are all subject to opinions. And finally, human analysts might not be able to keep up with the volume of data that needs to be processed for it to be useful.
Artificial Risk Intelligence
Artificial Risk Intelligence (A-R-I) is information that is gathered automatically by machines using algorithms. It includes things like social media monitoring, web scraping, and machine learning. It has become increasingly popular in recent years as technology leaders like Google, Apple, and Amazon have opened their neural networks. This complements risk & business continuity leaders as they are always looking for ways to accelerate the risk identification process.
There are several benefits to using (A-R-I). First, it can gather large amounts of data quickly and cheaply. Second, because it uses algorithms rather than humans to process data, it can identify patterns that would be missed by human analysts. Third, machine learning gets better over time at identifying risks if properly dispositioned. Finally, (A-R-I) can complement traditional intelligence by providing another source of information for analysts to use in their decision-making process.
Machines don’t have all the advantages, there are also some limitations to Artificial Risk Intelligence. First, because it relies on algorithms rather than humans, it can sometimes produce false positives or miss important details about a particular risk. Second, (A-R-I) point solutions can be expensive to set up and maintain and often rely on pre-trained data sources that overtime can become obsolete. Take the recent example of Twitter as a data point. Can we rely on manufactured accounts that are bots to serve as reliable sources of intelligence? I’m not here to answer that question, but I am here to get us all thinking in analogous terms. And finally, because they are powered by machines rather than humans, they can be slow to respond to changes in the environment or new types of risks.
Combining Traditional Risk Intelligence and Artificial Risk Intelligence in a Critical Event Management Platform
One way to overcome the limitations of both intelligence-gathering methodologies is to use them together in a Critical Event Management Platform (C-E-M). That’s right, use the best of what each as to offer. You need the right platform that is designed specifically to effectuate results and quash the limitations. With the ever-increasing need for rapid response in a variety of situations such as crisis, emergency, and medical needs, an organization benefits from a comprehensive Critical Event Management Platform, like Kinetic Global. We believe that to be the leader of actionable intelligence we need to not only be accurate but timely.
Global corporate security organizations must be proactive with their approach to risk intelligence. A critical event management platform that uses a combination of risk intelligence collection methods and multiple data sources is the best approach to unifying data collection. The benefits are significant:
- Better protection for employees, property, and brand assets
- Reduced frequency and severity of critical incidents
- Better cost management of response, recovery, and liability.
- Improved business continuity and organizational resilience.
By combining the best of human intuition with the best of artificial risk intelligence, The Kinetic Global Critical Event Management platform enables global security and business continuity officials to take charge of any situation that may impact the safety of your company’s most valuable assets.
Kinetic’s approach to critical event management and integration results in reduced cost of ownership, lower implementation time, and smarter management of incidents.
