Help Needed: Probability Problem in Risk Management Calculcations

In summary: R(S, W, C, E, \dots) = \frac{S + W + C + E + \dots}{S_{max} + W_{max} + C_{max} + E_{max} \dots}$$In summary, Stephen Tashi's idea is to create a function that takes in multiple input values (e.g. speed, weather, road conditions, driver experience) and calculates the resulting risk. This risk is then represented on a 0-1 scale. His first disclaimer is that he is not a math professional, so this idea may need to be extensively modified.
  • #1
Moose Winooski
2
0
TL;DR Summary
How to figure out the probability of multiple outcomes from a single event
Hello all!

I hope I have come to the right place, and I appreciate any help! My first disclaimer is that I am not a math professional of any sort, I am not bad at it but I just wanted to start with that so if I ask a stupid question, it's because I am ignorant mostly. What I work in is risk management, specifically health and safety.

My problem is this, I don't like and have never really felt comfortable with communicating risk from a 2-dimensional point of view (e.g. likelihood is between 1-2 years, and the consequence is a permanent disability). For those that are familiar with risk, your typical 5x5 heat map.

My issue with this is a "Risk Event" can have a range of possible outcomes. If you think of a car accident, the outcomes can range from minor bumps and bruises to death... and I would like to, in a visual way, represent the probability of many outcomes. (e.g. Bumps and bruises 22% chance, Hospitalisation 48% chance, Permanent disability 20%, Death 10%).

To add to my problem in many cases I probably won't have good external or internal data to already represent this... but I may have multiple "Risk Inputs" so if I go back to my car accident example there would be the inputs of speed, weather, road conditions, driver experience etc... that I could use as "dials" to shift the probability of the outcomes. I also assume that I would have to "weight" these inputs and that would add some subjectivity but I don't think I could be any more accurate?

So in a nutshell, is there a way I can visualise a Risk Event that shows a bunch of grouped outcomes and their probabilities while also having the ability to highlight that "if we increase the speed" then it shifts the numbers?

Cheers, M
 
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  • #2
Moose Winooski said:
My issue with this is a "Risk Event" can have a range of possible outcomes. If you think of a car accident, the outcomes can range from minor bumps and bruises to death... and I would like to, in a visual way, represent the probability of many outcomes. (e.g. Bumps and bruises 22% chance, Hospitalisation 48% chance, Permanent disability 20%, Death 10%).
I see things in terms of a function with several input parameters and a single output in the range of 0 through 1.

Moose Winooski said:
To add to my problem in many cases I probably won't have good external or internal data to already represent this... but I may have multiple "Risk Inputs" so if I go back to my car accident example there would be the inputs of speed, weather, road conditions, driver experience etc... that I could use as "dials" to shift the probability of the outcomes. I also assume that I would have to "weight" these inputs and that would add some subjectivity but I don't think I could be any more accurate?
What I have in mind is something like this:
$$R(S, W, C, E, \dots) = \frac{S + W + C + E + \dots}{S_{max} + W_{max} + C_{max} + E_{max} \dots}$$
Here R = Risk, S = Speed, W = Weather, C= (road)Condition, E = (driver)Experience.

The max numbers are there so that the resulting output value is in the range 0 ... 1. This is just a first cut at a possible solution, so might need to be extensively modified. Also, one might need to take into account that some risk factor levels could virtually guarantee a serious accident, if not outright fatalities. If I were doing this I would try to set something up in a spreadsheet and play with it.
 
  • #3
Moose Winooski said:
My first disclaimer is that I am not a math professional of any sort, I am not bad at it but I just wanted to start with that so if I ask a stupid question, it's because I am ignorant mostly. What I work in is risk management, specifically health and safety.
You should be aware that risk management is a very complicated mathematical problem. Insurance companies hire and support actuaries to do the calculations that they need. There are several levels of Actuary certification that require you to pass tests that are heavily mathematical and become very hard. I have read that in all of India there is only one person who has passed them all and is certified at the highest level.
 
  • #4
Moose Winooski said:
(e.g. Bumps and bruises 22% chance, Hospitalisation 48% chance, Permanent disability 20%, Death 10%).

It isn't clear whether you intend those outcomes to be mutually exclusive. For an example, a person who suffers permanent disability might also suffer bumps-and-bruises unless you intend bumps-and-bruises to mean " only bumps-and-bruises and not one of the other listed outcomes".
 
  • #5
Thanks all,

@Stephen Tashi - For the most part, when dealing with risks it's like passing through gates... so if we were talking about $$$ you might have an algorithmic scale of like Loss $0-10k... Loss $10k-100k... Loss $100k-$1M etc... With the most likely being perhaps the 10-100k... but that doesnt mean that the other "bands" have a 0% probability

@FactChecker - Yes very aware, I am looking for something in between subjective 5x5 risk matrix likelihood/consequence comparison to full-blown actuary level analysis as I don't have the time/resources to make that a practical option

@Mark44 - With your formula would all of the variables need to have consistent value ranges? Like would it break if I made speed a range of options from 0-300 and road condition 0.0-1.0 to represent a percentage?
 
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FAQ: Help Needed: Probability Problem in Risk Management Calculcations

What is the basic concept of probability in risk management calculations?

Probability in risk management calculations refers to the likelihood of a specific event occurring. It helps in quantifying the uncertainty and potential impact of various risks, enabling organizations to make informed decisions by assessing the chances of different outcomes.

How do you calculate the probability of an event in risk management?

The probability of an event in risk management is calculated by dividing the number of favorable outcomes by the total number of possible outcomes. For more complex scenarios, statistical methods and models, such as Bayesian analysis or Monte Carlo simulations, may be used to estimate probabilities more accurately.

What is the role of probability distributions in risk management?

Probability distributions play a crucial role in risk management by describing how the probabilities of different outcomes are spread out. Common distributions like normal, binomial, and Poisson distributions help in modeling and predicting the behavior of risks, allowing for better risk assessment and mitigation strategies.

How can probability help in decision-making under uncertainty?

Probability helps in decision-making under uncertainty by providing a quantitative basis for evaluating the potential outcomes of different decisions. By understanding the likelihood and impact of various risks, decision-makers can prioritize actions, allocate resources more effectively, and develop contingency plans to manage potential adverse events.

What are some common tools and techniques used in probability-based risk management?

Common tools and techniques used in probability-based risk management include risk matrices, fault tree analysis, event tree analysis, Monte Carlo simulations, and Bayesian networks. These tools help in identifying, assessing, and quantifying risks, as well as in developing strategies to mitigate or transfer those risks.

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