Tech Target defines risk management as the process of identifying, assessing and controlling threats to an organization’s capital, earnings and business operations. Under the risk management umbrella one will find several tactics to mitigating and overcoming threats and risk including: risk avoidance, risk mitigation, risk acceptance, and risk transference. Let’s start with risk reduction.
Risk reduction entails actions a company takes to identify probable risks and measures to minimize the negative impact from those risks. Businesses of all sizes, including large organizations and government agencies, should be prioritizing threat detection and risk reduction to protect business assets, finances, operations, and employees. The more complex an organization, the more diverse its threats will be, ranging from cyber threats to external economic disruptions.
Security teams are leveraging analytics to help create their risk mitigation and reduction strategies. Data analytics can identify previously undetected patterns and trends, which can help forecast future disruptions. Data analytics is extremely effective in identifying, assessing, and effectively mitigating risks; it is essential for modern risk management strategies.
Understanding the Risk Landscape
To succeed in risk reduction, one must first understand the various risks at hand, which include operational, financial, reputational, and strategic.
- Operational risks – The security industry considers the following four types of risks to be the most common operational risks: human risks, process risks, systems risk, external factors, and legal and compliance risks. The process organizations and government entities undertake to manage operational risk is called operational risk management.
- Financial risks – This risk category typically encompasses market risk, credit risk, and liquidity risk, and operational risk. Market risk is an effect of changes in the marketplace in which an organization competes, credit risk involves lending funds or giving a line of credit to a customer, liquidity risk is in relation to daily cash flow.
- Reputational risks – These pose a threat to a brand’s name, trustworthiness, and market standing, often arising from malicious activity or operational failures.
- Strategic risks – These risks arise from decisions made by leaders and stakeholders that fail to succeed or are less successful than anticipated.
While it is impossible to avoid all risks at all times, it is possible to leverage dynamic risk reduction strategies to minimize impacts. If the proper strategies are in place, they will not only help mitigate the risks, but will give organizations the foresight to create avoidance strategies as well.
The Power of Analytics in Risk Reduction
A key to successful mitigation strategies is the use of emerging technologies. Tools such as artificial intelligence (AI) and IoT are all reshaping the risk management business – offering speed, efficiency, and automation benefits. However, they also create new vulnerabilities. It is critical for security teams to be diligent in their understanding of technologies and remain vigilantly involved in their use.
Analytics can sift through vast amounts of data to identify potential risks before they materialize. Data-driven methods allow organizations to assess the probability and potential impact of risks, enabling more accurate and informed decision-making. For example, predictive analytics provides early warnings about known threats and helps organizations allocate resources effectively.
Manually monitoring for disruptive events presents significant challenges for teams, as the sheer volume of information can lead to critical details being overlooked or resources being diverted to other priorities. Technology, on the other hand, operates continuously and at a speed far beyond human capability. By leveraging the right technological solutions, security teams can effectively anticipate and prepare for risks before they escalate. Fortunately, organizations have access to a range of technology vendors, including Seerist, to support their analytical and operational needs.
Building a Robust Risk Analytics Framework
If an organization wants to succeed with risk reduction, they need to follow a framework.
Key components of a risk analytics framework include:
- Data collection: Gathering historical data from internal and external sources, current events, and expert insights to identify potential risks..
- Data cleaning: The action to fix incorrect, incomplete, or duplicate data.
- Data modeling: Ensuring accurate data representation within the database.
- Visualization: Sharing complex findings in easy to understand visuals.
While it’s impossible to avoid all risks at all times, adopting a proactive approach ensures that impacts are minimized. Effective strategies can also help organizations anticipate future challenges and avoid unnecessary risks.
Case Study: Risk Reduction with Seerist and Sapura Energy
Sapura Energy operations globally as an integrated energy services and solutions provider. From exploration to rejuvenation, Sapura covers the entire upstream value chain, including renewables. The Sapura Energy security team is responsible for managing country risks, ensuring travel security, and conducting investigations for all its employees. However, the extensive level of travel being done by so many employees made it difficult for the security team to stay up to date on activities, events, and political landscapes across all countries of interest. This challenge was particularly pronounced in regions with unstable conditions, such as Congo, Myanmar, Papua New Guinea, and Ivory Coast. The team was relying on Google searches and local contacts as main information sources, which hindered their ability to attain a consistent, robust and reliable level of intelligence.
Sapura Energy partnered with Seerist to enhance the protection of its personnel by reducing the reliance on manual searches and delivering timely, robust, and accurate intelligence. Now, with the Seerist platform, the Sapura Energy security team is accessing extensive analysis, leveraging the open-source intelligence data from reliable sources, as well as benefiting from maritime content. Thanks to Seerist’s AI-generated event alerts, Sapura Energy receives timely updates on political stability, such as potential successors in areas with political unrest, such as Angola, or local crimes like oil theft in African countries. People are now protected and informed before they travel and are alerted to potential threats well in advance.
Making Risk Reduction a Priority
Risk reduction is a critical component of any security team’s work. Having access to reliable data and analysis is imperative for any large organization or government entity facing complex risks.
Organizations need to cultivate a data-driven culture and ensure that all relevant stakeholders understand the benefits of leveraging analytics to illuminate trends and patterns, detect anomalies, and drive informed decision-making.
Organizations must also be ready to tackle common challenges such as data silos, resistance to change, and the need for specialized skills. Fortunately, these are all relatively simple problems to overcome. Leaders should spend time getting all departments and leaders involved and working towards a shared goal. Partnering with a security intelligence expert such as Seerist can immediately help teams with bandwidth and supplement missing skills. To explore the potential of analytics for your own risk reduction efforts, contact Seerist today to learn more or schedule a free demo.
