Research Paper

Running head: THE RISK MODELING CONCEPT

THE RISK MODELING CONCEPT 6

The risk modeling concept

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Risk modeling concept

Risk modeling is increasingly becoming prevalent in many industries, especially energy and financial services, since taking calculated risks is integral to business operations. Organizations throughout the private and public sectors have started adopting a broad array of risk models to address operational, strategic, geopolitical, and compliance risks (Haimes, 2016). With vast volumes of data and advanced analysis capabilities, risk modeling is becoming more practical for these organizations. Secondly, the need to deal with increasingly tricky environments is making risk modeling more valued.

A risk model can be defined as a mathematical representation of a system, usually encompassing probability distributions. It involves modeling and quantifying risks (Haimes, 2016). Models use appropriate historical data and expert elicitation from individuals versed in risk modeling to understand the likelihood of a risk event occurring and its potential severity. Risk models are applicable in evaluating and assessing many types of risks (Haimes, 2016). A company may want to study and understand the risk of achieving its strategic objectives or respond to specific questions. The company may also want to study and understand the threats to its supply chain, how an adaptive adversary or a hacker may attack its assets, or assess the geopolitical risks of expanding into an emerging market. The company can develop risk models to assess how their system behaves under normal operating conditions and hypothetical "what if" scenarios (Koller, 2019). This would enable the company to determine its risk tolerance level and assess how it will build resiliency into its systems to be in a position to withstand different impacts.

There is a common misconception that developing risk models is very expensive and time-consuming that it would take years (Koller, 2019). This is not true because there are numerous new tools and accelerators to help companies create less complicated risk models within shorter periods.

Importance of risk models

All projects, irrespective of how they are meticulously planned, are exposed to impacts of risks. Since it is difficult for a person or a team to predict a project's future with total certainty, risk models can help them mollify the risks and nasty surprises they might face during their projects (Hopkin, 2018). Risk modeling enables companies to identify, analyze, and mitigate risks that a company is prepared to handle should they occur.

Risk modeling enables companies to identify any risks they may experience in their operations or projects. It prevents them from going into projects blindfolded. Risk identification refers to the continuous process of differentiating events that would positively or negatively impact or results throughout the life cycle of a project (Hopkin, 2018). Developing a risk register is part of the risk modeling framework that helps companies lay all potential scenarios to ensure that they are well informed and prepared to deal with these eventualities. Companies need to be practical and upfront about the risks they may face at the early stages (Haimes, 2016). All organizational issues that may affect the project should be documented in the risk register irrespective of whether they affect the company's senior management.

Risk modeling ensures that the project team, company executives, and all project stakeholders know the project's potential risks from the outset. Risk models are essential tools in defending the decision you make in the risk management process (Aven, 2016). Trying to mitigate the adverse effects of a risk reactively gives the stakeholders that you are damaging the business relationship, reputation, and integrity. Risk models help companies mitigate the adverse impacts of risks proactively hence blocking it from damaging the project and the entire company.

Risk modeling also helps companies to increase their organizational risk maturity and assign clear responsibilities to team members. Companies can have a better risk of maturity (Hopkin, 2018). In a market with risk-immature organizations, having a substantial risk modeling culture can set a company apart. An essential part of this maturity originates from defining clear roles and then assigning responsibilities in the risk modeling phase. This prevents companies from paying dreaded blame games when risks materialize (Mun, 2010). Risk models help companies to remediate the negative impacts of risks rather than pointing fingers when risks occur.

Risk modeling increases the probability of companies to meet their expectations. Companies with effective risk models are at increased chances of delivering their projects on their set budgets and deadlines. This is because these companies start by carefully assessing all risks, enabling them to make more accurate project estimates in terms of budget and scope (Koller, 2019). If your risk model shows that your project will come up against probable and impactful risks, you should inform the project stakeholders and set the project's scope expectations.

Approach to modeling risks

There are a variety of approaches that can be used in risk modeling. One of them is the risk simulation approach. Simulation can be defined as looking at how models behave under particular conditions or assumptions (Mun, 2010). Risk simulations guide companies in decision-making and help them gain insights into the underlying process or system to make it more stable, secure, resilient, and useful. Risk simulation enables companies to measure risks, direct decisions, and actions based on the risks, develop steps to reduce risks, and monitor them over time (Mun, 2010). Risk simulation helps organizations reduce the complexity of risks and alleviate making informed business decisions.

When deciding the techniques to model, measure, and aggregate risks by organizations, it is essential first to consider the risks or threats they are facing. Threats arise from internal or external environments in a company (Koller, 2019). There is no defined approach to combat risks. As a result, a company’s measures are based on the types of risks being faced. Using independent experts enables risk management teams to perform their duties systematically to handle all underlying risks. Companies should also apply aggregate risk management techniques to understand the impact and risk models in all angels (Haimes, 2016). This enables the companies to understand risk management; they need to ensure that they succeed in their risk management practices.

Conclusion

Risk modeling is an essential and evolving environment in most industries. Risk modeling creates a vast network of opportunities for scenario analysis, forecasting, analytics, and risk mitigation for optimal integration of risk management practices in business and decision-making. Companies should use new tools and accelerations to develop effective risk models to help them manage risk management practices. Companies that have effective risk models enjoy accurate results based on their set project expectations. With robust risk models, companies can identify risks effectively, analyze risks, rank or assess the risks, and mitigate the risks.

References

Aven, T. (2016). Risk assessments and risk management: Review of recent advance on their foundation. Europeans Journal of Operational Research, 253(1), 1-13. Haimes, Y. Y. (2016). Risk modeling, assessment, and management. Hoboken, NJ: John Wiley & Sons. Hopkin, P. (2018). Fundamental risk management: understanding, evaluating, and implementing effective risk management. Kogan Page Publishers. Koller, G. (2019). Risk modeling of determining value and decision making. CRC Press. Mun, J. (2010). Modeling Risk: Applying Monte Carlo Simulation, Real Options Analysis, Forecasting, and Optimization Techniques. Hoboken, NJ: John Wiley & Sons.