Today, many organizations continue to follow a traditional approach to risk management by imbedding the responsibility for managing risks within each business unit where it is considered a function required to run the business unit. This traditional approach tends to monitor risks in a reactive mode by tracking, analyzing, and reporting loss or near loss events after occurrence accompanied by a remediation plan to prevent recurrence. The reactive approach to risk management draws heavily on backward looking lagging risk indicators and postmortem analysis. Reliance on this traditional approach alone can handicap an organization because it fails to keep pace with the increasing scope of emerging risks and inhibits the speed at which the organization needs to take action to counter or mitigate those risks.
The addition of Predictive Intelligence (“PI”) offers a more effective means of managing risk because it provides for the use of advanced analytics methods that apply forward looking leading risk indicators to identify and track emerging risks in their early stage. This allows for the organization to get out in front of those risks to manage or mitigate before they fully develop:[1]
- Operational Failures: PI can provide actionable risk information on critical infrastructure components that could result in operational failures.
- Employee Misconduct: PI can lead management to potential conduct lapses, changes in employee sentiment, and policy breaches resulting from employee misconduct.
- Outsourced Operations: PI can draw on internal and external data sources to provide visibility into outsourced operations that may lack transparency.
Predictive intelligence uses risk characteristics to produce insights into the development of risk mitigation actions. A prerequisite to implementation of predictive intelligence requires a thorough understanding of the sources and types of risks. From this level, the organization can then develop characteristics of various risks and ultimately work to identify leading indicators that precede the occurrence of these risks. [2]
- Identify risk characteristics (source and type) to develop baseline data for analysis and predictive modeling.
- Identify incidents that precede risk events and provide reliable indication of the occurrence of such an event.
- Develop predictive analytics algorithms that predict or detect the heightened occurrence and probability of a risk event.
- Adopt risk governance functions that track data elements for each type of risk and apply risk predictive algorithms that trigger alerts and notifications for continuous evaluation.
PI doesn’t have to be complex to be effective. The most critical element in developing a PI capability is the full and complete understanding of the factors that fuel the most significant risks facing the organization. A risk program that runs PI in tandem with a traditional risk management approach provides a solid platform where the organization can learn from the past and apply to the future.
[1] Deloitte. (n.d.). Identify emerging threats with predictive intelligence. Retrieved from Deloitte: https://www2.deloitte.com/us/en/pages/advisory/articles/identify-emerging-threats-with-predictive-intelligence.html
[2] ibid