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Gambling as a risk management strategy ?

Software principles : gambling theory and statistics

Our software products mainly rely on two mathematical models : 

  • the theory of games, used in many decision making softwares
  • Statistical models that can explain current behaviors

The theory of games is used in our softwares to enforce business models and compute business functions. Statistical models are used to build models in order to compute figures.

The software estimates every risk as figures measuring probability of the risk to occur and consequences of its occurrence in concrete terms. The evaluation of the risks is computed according to answers to a questionnaire. The evaluation of the consequences is computed as mathematical expectancies. Computations lean on probability algebra, and are stored with the questionnaires in what we call a "knowledge base".

Probability algebra is the frame and strength of the solution :
  • we can use actual statistical data within the knowledge base,
  • risks can be easily computed as figures with statistics
  • we can put all parameters outside the software product
  • it can evolve as "Scoring" models will never be able to
Moreover, each response, each declared incident becomes a statistical information : we can therefore feed the model with figures provided from the model and improve accuracy of the data.
Have a clear vision of what can happen

In practice : learn with no risks

It may look funny to view risks as in a Casino, imagine the chief officer of a company, a project leader or a product manager "betting" on risks : however, there is a clear link between risks and choices we make within our environment.

In fact, many executive has very few visibility on the impact of choices they make : this is why our products provide comprehensive figures on risks and their consequences, therefore helping to understand the stakes.

One of the side effects of our software is to allow decision makers to estimate " at no risk " their choices and decisions: the product computes and feedbacks the consequences of these choices before they become real. A study on the behaviour of users of "SelfScore Créateur d'entreprise" (french product for "new business" analyses)  shows that the user begins by answering all the questions " without arising any " and starts to take care of risks only when they get alerted by the results of the analysis.

Competing with experts

Competing with experts

Our software is regularly confronted with experts in risk management in the various domains in which we build products : these confrontations always showed the capability of our solution to compete with experts.

In many cases, the results of our analyses seems very similar to results produced by human experts. But the main difference it that our software produces figures, while experts are very reluctant to produce any, and it never forgets any of the subjects to analyse.

However, various studies show that decision makers require simple results : it is why we also produce color codes which notify directly on the priorities. We can also produce specific quotation depending on the subject our software are managing.
 

SAS Accompagnement Informatique RCS Epinal 482 329 455 ©