risk2value. simulation

is the simulation component of risk2value. You can use this integrated tool to perform statistical calculations such as the renowned Monte Carlo method (i.e. stochastic scenario analysis) within risk2value.  

Get to know risk2value.simulation in our demo video! You can see some specific application examples live in the tool.
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Risk quantification made easy

For many, quantification comes across as too complex or challenging. The idea of spending days or even weeks delving into simulations, probability, distribution and random numbers often poses an obstacle. Perhaps you have also considered taking the first steps toward risk quantification, but changed your mind because the work involved didn’t seem to justify results that still lack the necessary transparency.  

With risk2value.simulation, the Monte Carlo simulation software from avedos, you can easily extend your risk management with quantitative methods. See for yourself!

Would you like to view risk2value.simulation in action? We’d be happy to show you the tool in an exclusive live demo or send you a white paper outlining real-world use cases and technical details for risk2value.simulation. Should you have any further questions, simply contact Daniel Szamosvari for assistance: 

Marco Moretti avedos Mitarbeiter

Wollen Sie risk2value.simulation besser kennenlernen?

Sehr gerne zeigen wir Ihnen das Tool im Rahmen einer exklusiven Live-Demo oder senden Ihnen das riskvalue.simulation Whitepaper zu. Bei weiteren Fragen wenden Sie sich bitte an Marco Moretti:

Marco Moretti

Sales & New Business

What is a Monte Carlo simulation?

Calculations of expected values are often full of errors. The Monte Carlo method, in contrast, is a stochastic model that conducts a large number of random experiments to produce reliable results based on risk quantification. Risks are evaluated based on their probability of occurrence, distribution functions and extent of damage (e.g. three-point estimation). Simulations are used to determine the aggregate risk (i.e. risk aggregation). Dependencies among individual risks can be taken into account. Results are then presented in various quantiles instead of absolute values. risk2value.simulation delivers a fully integrated Monte Carlo simulation. Your organization profits from: 

Your advantage with risk2value.simulation

We understand your challenges:

Critical need for companies to take action

We have observed that purely qualitative evaluations no longer suffice for many companies. The trend is moving toward quantitative evaluations – mostly in preparation for using simulation methods. A recent Gartner study confirms this trend and emphasizes the growing significance of quantitative methods.

IDW PS 340 n.F., the new auditing standard of the German Institute for Public Auditors which will go into effect in 2021, also requires quantitative methods for publicly traded companies. As in the past, this standard will quickly trickle down to smaller companies as well.

At the heart of the new auditing standard is a legally binding examination of the early warning system by the auditor. IDW PS 340 incorporates the following topics: 

The emphasis here lies in the points regarding risk-bearing ability, risk aggregation and the analysis of net risk. These requirements force companies to view risks in a quantitative manner. Calculating the aggregate risk and its effects on risk-bearing capacity are only feasible with quantitative methods such as the Monte Carlo simulation.  

Gear up your risk management and fulfill the latest IDW PS 340 requirements with a risk2value custom solution and risk2value.simulation. Read our whitepaper for more information on risk2value.simulation.

Daniel Szamosvari avedos Mitarbeiter

Any questions?
We'd be happy to assist!

Daniel Szamosvari