The article I chose to discuss is SIRA’s Reducing Ignorance by Marcin Antkiewicz. Antkiewicz delivers several interesting viewpoints on what risk in and how to predict it, as well as common misconceptions of risk analysis. In Antkiewicz’s experience, he often encounters fellow risk analyzers in his profession who have inconsistent definitions of risk analysis; this is fascinating due to the familiar ‘cookie-cutter’ definitions of several of the significant terms in risk. The article truly captured my interest with a simple question regarding how to predict risk effectively, “Suppose I go into a casino with $100,000, what am I going to come out with (Antkiewicz, 2012)?

While it is indeed impossible to accurately predict such a case in a mathematical format, one can undoubtedly use past/current real-world data on gamblers and the systems and algorithms the typical casino utilize in ensuring they are victorious in the ongoing battle between those who think they will get rich quick, and the policies, procedures, hardware, and software of those who merely want to profit on the often lack of luck with their consumers. While many of the images the article provides were unable to display, I could still piece together several methods of both gathering and presenting my predictions of this scenario’s outcome.

In risk management within an organization, the scenario mentioned in this article is what we do on a daily basis. For example, let’s translate the gambling scenario into a business-oriented setting. If a company goes into the next fiscal year with $1,000,000, what are they going to have remaining at the end of the year? To predict this figure to be best on your abilities, you would envision various scenarios and events occurring. For example, what is the possibility of a security breach that costs the organization legal fees or loss of business? What departments are predicted to ask for more funding, or require less? Are there any plans for expansion? If so, what are their risks?

Antikiewicz’s article offers a unique viewpoint on risk analysis in the modern world by using one of the riskiest scenarios: a gambler with a heavy pocket, looking to score his way into the American dream. Using the article’s data, one could effectively obtain all of the available metrics and data and input them into an equation that predicts the dollar amount that the gambler would either win or most likely lose. Similar to the battle tactics of both gamblers and casinos, each has their methods of ensuring their risk of loss is reduced as much as possible. If we, as risk analysts, apply the same lessons that enable casinos to be profitable while literally letting multiple sources of risk into their doors willingly, we would certainly be more in-tune with how to successfully protect our organizations.

References:

Antkiewicz, M. (2012, March 4). Reducing Ignorance. Retrieved October 06, 2020, from https://societyinforisk.org/Blog-Posts/4355793.