 Managing risk is an ongoing process in the business sector. This involves identifying, analyzing, prioritizing, implementing, and monitoring both internal and external risks that can potentially threaten business operations. Mitigating these risks starts with having the right documentation. How can you properly identify or assess any business risk let alone provide solutions if you have insufficient documents? Today, we will discuss the characteristics of effective risk management documentation your business should have. Show What Are the Characteristics of Risk Management Documentation?Readability – Risk management documents, whether strategies, risk reports, contingency, or mitigation plans, all documents must be in plain language, so it’s easy to understand for all audiences. Relevant – The entire framework of the risk management process must be based on information, technical, and other elements that are up to date. Organizations cannot make accurate assessments of different types of risk without relevant data. Accessibility – Well-organized documents are easily accessible and stored in documentation systems that allow employees the access to make the necessary changes if given authorization. Compliance – All documents must meet industry and regulatory standards so an organization can always remain compliant. Collaborative – Stakeholders, Employees, and other internal audiences establish good workflows amongst each other. Therefore, this ensures the best solutions for each department. Also, emphasize the importance of risk awareness. Trained staff members to identify and manage risks in their respective departments. Conciseness – Risk management documentation should be concise. So, it conveys the needs of the organization as well as other audiences of the company. ConclusionTo effectively manage any type of risk, businesses must first have well-organized risk management documents to begin any assessment process. Without the right information, you can leave your business open to all kinds of negative risks. However, professionally written documents will ensure everyone across the organization is ready and prepared to face any known and unknown threats that may come. Whether you need a team of consultants to produce a complete line of documentation or a single technical writer for a brief project, Essential Data’s Engagement Manager will lead the project from start to finish. At Essential Data Corporation, the quality of our work is guaranteed. Contact us today to get started. (800) 221-0093 or Written by Kimberly Jones Get full access to Principles of Risk Management and Insurance, 13th Edition and 60K+ other titles, with free 10-day trial of O'Reilly. There's also live online events, interactive content, certification prep materials, and more.
Private insurers generally insure only pure risks. However, some pure risks are not privately insurable. From the viewpoint of a private insurer, an insurable risk ideally should have certain characteristics. There are ideally six characteristics of an insurable risk:
The first requirement of an insurable risk is a large number of exposure units. Ideally, there should be a large group of roughly similar, but not ... Get Principles of Risk Management and Insurance, 13th Edition now with the O’Reilly learning platform. O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.
Get Mark Richards’s Software Architecture Patterns ebook to better understand how to design components—and how they should interact. It’s yours, free.Get it nowThe IPCC (2020) makes a clear distinction between hazard and risk. In this chapter, the term “risk” always involves some kind of consequence and does not only describe the physical hazard. Risk is frequently defined as being the probability of losses or damages. In some economic applications, risk is defined as the future uncertainty of the deviation from an expected outcome. This is in line with the ISO 310000 standard on risk management, where risk is defined, independent of positive or negative impact, as the effect of uncertainty on objectives (International Standards Organization (ISO) 2018). In IPCC (2012), risk is defined as the product of probability and consequence. IPCC (2020) specifically defines risk as “the potential for adverse consequences”. In the natural hazard context, risk is often considered as being the product of probability and consequence or the severity of the consequence. Consequence in this case is the consequence of an impact, e.g., a physical damage, a monetary loss, or an interruption of services. The consequence is usually a combination of exposure and vulnerability for a particular hazard intensity. Risk can therefore be considered a combination of hazard, exposure, and vulnerability, similar to the definition of weather and climate risks used by the IPCC (2012). The concept used by the IPCC (2012) can therefore be applied to any kind of disaster risk, not only to weather and climate events (Fig. 2.1). Fig. 2.1Illustration of the concept of disaster risk, based on the illustration by IPCC (2012) The notion of risk being the product of probability and consequence does not necessarily mean that it is a single probability multiplied with a single consequence. Such a single product of probability and consequence can be a reasonable approach for risks which only have a single probability, and in case of the event, a single consequence. Such risks are usually of technical nature with a failure probability and an associated consequence. This could e.g., be a power line, which is either fully functional or not functional at all. In the case of natural hazards, the entire range of consequences and their probabilities usually has to be considered. From frequent to rare events, from small to large consequences (Fig. 2.2). Frequently occurring weak storms only cause minor damage. Increasing intensity of storms leads to increasing damage. When using a single probability and consequence or a very limited number of values of probabilities and consequences to determine the risk, the users have to be aware that the risk might not be properly characterized. It is therefore important to estimate the entire range of probabilities and consequences. This constitutes a damage curve, also called a loss curve, loss frequency curve, or damage exceedance probability curve (see e.g., Mitchell-Wallace et al. 2017 or Aznar-Siguan and Bresch 2019). The term loss frequency curve will be used in the remaining text. The loss frequency curve is explained in more detail in the following section. Fig. 2.2Illustration of risk defined by a single point of probability and consequences or losses (red point and red surface) compared to using an entire loss frequency curve (blue curve and blue surface) Return periods are frequently used in the natural hazard context, especially in communicating with stakeholders. Return periods are usually used to characterize a particular event: “The wind speed of a certain storm at this location had a return period of 1 in 100 years”. This is also called a “100-year event”. Return periods are the inverse of exceedance probability and hence also linked to non-exceedance probabilities. $$ Return\ Period=\frac{1}{Exceedance\ Prob ability}=\frac{1}{1- Non\hbox{-} Exceedance\ Prob}. $$ These probabilities and the corresponding return periods usually denote yearly probabilities in natural hazard applications. This needs to be made clear when communicating return periods to a non-technical audience. The unit of years gives the impression that return periods are easier to understand by stakeholders. Return periods are another way of describing yearly exceedance or non-exceedance probabilities. Especially for longer return periods, the probability is commonly underestimated as it is believed that such an event can only happen once within this time-period. A 100-year event is not comparable to a 100-year-old person. This is frequently assumed by lay people in practical applications and therefore, they believe they’re not affected. It is often easier to communicate the probability of an event over a longer period of time rather than using return periods. The probability for a selected time period (Nyrs) given a return period (RetPer) can be easily calculated via the probability of the event not occurring: $$ P=1-{\left(1-\frac{1}{RetPer}\right)}^{Nyrs} $$ The resulting probabilities for several return periods and time periods (e.g., lifetimes of buildings) are shown in Fig. 2.3. Fig. 2.3Probability of different return period events over different lifetimes or time periods. If probabilities are considered over a longer period of time (e.g., the average lifetime of a building or infrastructure) of 50 years, even a 100-year return period event has a probability of occurrence of about 40% and a 300-year return period event of about 16%. This thought concept is commonly used in earthquake engineering, where the 475-year and 975-year return periods are used as they represent 10% and 5% of probability in 50 years (see Fig. 2.3). In communicating return periods to stakeholders, it is often favorable to convert these to probabilities over a longer period of time. Otherwise, the probabilities of higher return periods are easily underestimated. For the conversion to probabilities over longer time periods, the hazard probability is assumed to be constant over the entire time period being considered. Current estimates of return periods are usually based on past and current probabilities. Applying these probabilities to longer time periods might give the impression that they will stay constant in the future. This is usually not the case. Especially for hazards driven by meteorological events, probabilities are assumed to change with climate change. 2.2.2 Loss Frequency CurveComparing different risks is much easier if entire loss frequency curves are available for the risks to be compared. The loss frequency curve needs to represent losses or damages for a whole range of return periods or probabilities. It doesn’t matter, whether the loss frequency curve is defined and shown by exceedance probabilities or non-exceedance probabilities (see Fig. 2.4). The term of exceedance and non-exceedance probability highlights that it is the probability for a certain value (of loss or damage in this case) to be either exceeded or not reached, not the probability of exactly the value. Fig. 2.4Illustration of loss frequency curves with exceedance probabilities (left) and non-exceedance probabilities (right) as x-axis. Return periods corresponding to exceedance and non-exceedance probabilities are added at the top of the panels Loss frequency curves based on exceedance probabilities are commonly used in insurance applications with the associated risk metrics. When communicating to diverse stakeholders, loss frequency curves based on non-exceedance probabilities have revealed to be easier to communicate. Practical applications in Switzerland have shown that stakeholders are using return periods as they are commonly used in hazard mapping. Increasing return periods along the x-axis, together with increasing consequences, are therefore favorable. Loss frequency curves do not necessarily need to have a monetary scale for the consequences. The consequences can also be provided in terms of indices or any other metrics, e.g., people affected. Other examples might be the interruption of certain services (e.g., fresh water supply) or the intangible value of cultural heritage sites. The detail needed in determining loss frequency curves depends on the impact of having more or less detail on the use of the curve and/or the decision to be taken based on the risk assessment. Note that loss frequency curves represent a snapshot in time of the risk. Risk is changing over time for various reasons. These changes will be covered in a later section of this chapter. Page 2Illustration of several characteristics of risk: Shape of the curve is denoted by lines. Loss levels at reference return periods (30-, 100-, 300-, and 1’000-year) are highlighted by blue points and probabilities of first loss by black diamonds. The surface underneath the curve is illustrated by light color, it is identical for all three examples. The top-left panel could be an example for a metropolitan area with rare natural hazard events which cause large losses, the top-right panel a region with very low population density experiencing regular natural hazard events and a very limited maximum loss. The bottom panel could be a case, where a certain degree of protection is provided up to a certain intensity and therefore probability and losses increasing rapidly thereafter |
What are the 4 characteristics of risk?
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