Uses Of Efficient Frontier Analysis In SRM assignment Help

Uses Of Efficient Frontier Analysis In SRM

Discussion1

Explaining the results of Efficient Frontier Analysis to non-technical decision-makers

The implementation of Efficient Frontier Analysis in an organization helps the process of strategic risk management to encompass and advanced analytical technique. The outcomes derived from it can easily be acknowledged and utilised by the non-technical decision-makers of the organisation as well. With the private utilization of Efficient Frontier Analysis, the decision-maker can easily consider identifying Complex property and developing casualty risk profiles. It has been observed in the considered case study that the most convincing organizational decision-making practices to determine efficient risk management need extensive acknowledgement of the governance structure followed by the processes and the varieties of tools used in it. In addition to it, they are also subjected to be developed on the basis of the guidance and principles of ISO 31000 followed by the guidance of implementation empowered by Australian and New Zealand handbook HB 436 (Fraser, Simkins & Narvaez, 2014). The consideration of Efficient Frontier Analysis emphasizes the hierarchical roles within an internal audit function as well as the organization and risk management function.

The results of implementing Efficient Frontier Analysis depend in-depth assessment of the risk portfolio volatility followed by the pricing structure acknowledged through decision-making. Furthermore, the considered case study also explains that the implementation of Efficient Frontier Analysis also needs to analyze the insurance layering efficiency to determine the risk portfolio application in order to ensure the catastrophic loss potential within the decision-making practices of strategic risk management (Rezaeiani & Foroughi, 2018). Additionally, a business organization implementing it can also become capable of analyzing and resolving the control break down easily with the identification of risk origins, actors, causes and consequences precisely. With the help of proper strategic management, the non-technical decision-making practices can be functional through a risk appetite framework that influences risk control framework. both these further impact on the emergence of the dynamic risks followed by integrated enterprise risk profile and scenario and stress testing by enabling untapped opportunities.

Recommendations assuming the risk appetite

The notion of risk appetite is strongly aligned with risk tolerance to influence the scenario and stress testing abilities to develop an analytical framework. The fundamental purpose of this Framework is to drive multiple sets of discussions based on analytical information to help the decision-makers in determining the risk profile and lead the organization to constitute competitive opportunities. It has been observed that the risk appetite in association with the risk tolerance helps them in categorizing the risks and further reframe them as opportunities (Zhou & Xu, 2016). The decision-makers are recommended to acknowledge this concern in order to determine the position control framework.

Identifying risk appetite also enables control actions for the decision-makers considering the components of market share, product or service provision, market profit, social impact, stakeholder levels and other benefits (Hillson & Murray-Webster, 2017). The decision-makers are also recommended to acknowledge SRM over the traditional risk assessment in order to two distinct advantages risk profiles from the exploitable with a profile in order to determine sustainable efficiency and preventing competitively noisy environment by foreseeing the risk dynamics categorically through risk appetite.

 

Discussion2

For an organization to access risk versus return of each proposed project, their project lead should use the concept of efficient frontier analysis. If the frontier analysis is used efficiently, a company can easily understand and find the high profitable project to invest in. In addition, the information, which is gathered during this process, can be used to develop decision structure, which is eventually used by the project managers to assess a project. As per (Fraser, 2014), the idea of using the idea of using the concept of efficient frontier analysis is to help investors to invest in a project that gives high returns against risks. This process is usually represented by a graph. The value on the X-Axis of the graph is risk and the value on the Y-Axis of the graph is investment returns.  A line is drawn to connect the highest portfolio return that a project can give with the existing risks factors.  This line is the efficient frontier line and the analysis.

I would prefer using a simple graph, so that a non-technical person can easily understand the point. Additionally, this is a simple approach too, not all the points that fall under the efficient frontier line is optimal, therefore making it a not-a-good-idea-to-implement kind of project. Further, dumping a bunch of statics and random facts is going to be less fascinating to a non-techie.

The first and foremost recommendation from my end is, making sure the information is well recorded in the graph, so that we can obtain accurate information. If not, the main purpose of the analysis will never be achieved.

 

Discussion3

Most investment choices involve the trade-off between risk and reward. The “Efficient frontier” is a modern portfolio theory tool that shows investors the best possible return they can expect from their portfolio, given the level of volatility they are willing to accept. The chart here demonstrates the influence of concept. The vertical axis represents the expected rate of return. The horizontal axis signifies the investors’ risk tolerance. The frontier is a line curve, which shows the potential yield of portfolio given a degree of risk. Optimal portfolios should lie on this curve. In addition, the portfolios that fall below the frontier curve represent the less ideal mix of investment because with the same risk one could achieve a greater return. Any portfolio above this curve is impossible.

Take Chris who owns portfolio A. Currently, his investment generates the combined yield of 8%. Based on the efficient frontier, however, Chris can be achieving the same level of return with a considerably safer mix of investments with portfolio B. Both portfolio offer the same level of return but portfolio B has less risk. The job of investment advisor who uses modern portfolio theory is to identify the basket of securities that get as close as possible to the frontier. Investors should realize there is no preferred point on the frontier. A young professional probably is willing to accept a high level of risk and will therefore want to be somewhere near to the right of the curve. For an older adult, nearing retirement, a portfolio further to the left maybe ideal.

What is important is to get as close as possible to the efficient frontier whatever your risk profile may be. The effort to take advantage of complex data techniques was, in part, stimulated by the evolving risk management framework integration into what is now being modestly referred to as enterprise risk management (ERM) or strategic risk management (SRM).

Within the 2013 Risk and Insurance Management Society (RIMS) SRM Implementation Guide, the concept of strategic risk management is defined as a “business discipline that drives the deliberations and actions surrounding business- related uncertainties, while uncovering untapped opportunities reflected in an organization’s strategy and execution.”

What distinguishes this definition from previous descriptions of enterprise wide risk management (ERM) approaches is the effort to sustainably deliver a robust fact-based strategic dialogue across the entire organization. This new strategic dialogue requires an analytical framework that is dynamic and encompasses all areas of an enterprise. In this chapter, we demonstrate how the use of efficient frontier analysis (EFA), and many of its derivative techniques, provides a robust portfolio approach to hazard, operational, market, and reputational risk domains.

 

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