A gambler who risks their life savings on a game of roulette and wins might describe their decisions as correct, or even wise, even though their choice was arguably foolish. Read any account of a contest, be it a famous battle or a sporting event, and it is usually the victor whose tactics and strategy are held up as superior, even if chance events played a big part in the victory. The effect also occurs in many other aspects of life. This is known as self-attribution bias, and has been well-studied in financial trading, where skill and luck can be difficult to separate¹. It is also human nature to attribute success to skill or good judgment, even if the situation was largely one of chance. A pub brawl might result in a charge of assault or affray, for example, but the same fight might result in a manslaughter charge if somebody falls the wrong way and is fatally injured. This principle is even a part of our criminal justice system, where the same human failing might attract a very different sentence depending on an outcome which was largely driven by chance. It is in our nature to focus on the outcome of a particular event, rather than the factors that determined it. There are several main ways in which we can struggle to comprehend risk, and they are worthy of deeper consideration. ![]() Just like a novice pilot flying in cloud, human intuitive perceptions of probability, risk and reward are surprisingly poor, and very hard to overcome, which is why RiskFlag advocates a structured, disciplined approach to assessing and managing risk. The attitude indicator, central in the top row, is the most important instrument, and trainee pilots spend a great deal of time learning to trust this instrument over their own sensory perception. This sometimes requires a large amount of effort, because the mismatch between belief and reality can be extremely unpleasant and very disorientating.Ī typical set of basic aircraft instruments. The solution is to learn to trust the aircraft’s instruments, over and above one’s own senses. This phenomenon has, unsurprisingly, been the cause of many accidents. Denied of our normal senses, it is entirely possible to believe that an aircraft is in a gentle climbing turn to the left, when in fact it is in a steep, descending turn to the right. A typical first instrument flying lesson involves showing the trainee how the human sensory organs, perfectly optimised for life on the surface of our planet, are terrible at determining orientation without a discernible horizon and a constant, reliable perception of gravity acting straight down. Land, sea and sky are replaced with a blanket of solid cloud, and it is essential that they learn how to use the aircraft’s instruments safely. When learning to fly in poor weather, trainee pilots are denied their usual visual references. This is the foundation of the risk matrix, which we will explore in greater detail later in this series.Ī typical risk matrix. Despite the usually negative average expected payoff of an insurance policy, we eliminate the small chance of a catastrophic loss.įor this reason, risks are better thought of as vector quantities, defined by two parameters rather than just one risk ‘score’. This is the main reason for the purchase of insurance products. This is especially important if the loss is so great, either financially or physically, that it is impossible to recover and ‘play’ again. However, from the perspective of unlucky investors who have lost, the probability becomes irrelevant, and all that matters is the loss - particularly painful in the case of the second example here. ![]() A product with a 0.1% chance of losing the investor £10,000īoth investments have an average loss of £10 per ‘play’.A product with a 10% chance of losing the investor £100.Consider two different investment opportunities: Whilst this method is valid, it is important to understand its shortcomings. This might be days of lost production in a factory, for example, or perhaps less precise and subjective measures of negative outcomes such as injury or reputational damage. This is typically a monetary value, although other kinds of impact are often measured in the same way. The result of this calculation is then the average loss per event for the risk in question. This can be expressed as a probability multiplied by some numerical quantity describing the impact of the negative event. Most attempts to define and quantify risk involve two component parts: the chance that something bad will happen, and the magnitude of the negative effect should it do so. Risk: the effect of uncertainty on objectives - ISO 31000
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