Wer nutzt diese Software?
@RISK is used to analyze risk and uncertainty in a wide variety of industries. From the financial to the scientific, anyone who faces uncertainty in their quantitative analyses can benefit from @RISK.
Durchschnittliche Bewertung7 Bewertungen
- Gesamt 4.5 / 5
- Benutzerfreundlichkeit 4.5 / 5
- Kundenservice 4 / 5
- Funktionen 5 / 5
- Preis-Leistungs-Verhältnis 4.5 / 5
- Kostenlose Version Nein
- Kostenlose Testversion Ja
Installiert - Windows
Support während der Geschäftszeiten
Angaben zum Hersteller
- Gegründet 1984
@RISK performs risk analysis using Monte Carlo simulation to show you many possible outcomes in your spreadsheet model and how likely each are to occur. It mathematically and objectively computes and tracks many different possible future scenarios, then tells you the probabilities and risks associated with each different one. This means you can judge which risks to take and which ones to avoid, allowing for the best decision making under uncertainty.
- Compliance Management
- Für Hedge Fonds
- Alarmfunktion / Benachrichtigungen
- Compliance Management
- Internes Kontrollmanagement
- Korrekturmaßnahmen (CAPA)
- Management by Exception
- Mobiler Zugriff
- Prädiktive Analytik
- Rechtliches Risikomanagement
Die hilfreichsten Reviews für @RISK
Bewertet am 12.4.2017
Using Monte Carlo Simulation
Monte Carlo simulation is a very useful tool that allows the user to incorporate variability to what otherwise would be a simple spreadsheet model that uses average values. It is possible that if you use average values a project you are analysing will be profitable according to your analysis. When you incorporate variability while the expected profit is positive, can find that there is a high probability of the profit being really a loss.
@risk is a software you can use to create this type of models. It is basically an Excel add-in that will allow you to transform your Excel model into a much more versatile one. When you run your model you obtain not only a point estimate but can look the spread of the estimates. Can also identify which input variables are critical and you can also do some sensitivity analysis to look into the potential effect of one or more of the inputs changing (for example, what could happen if interest rates change).
The software is easy to use and it has an excellent manual as well as excellent online support. The company also organises on a regular basis very interesting conferences where case studies are presented by companies and these conferences are an opportunity to meet like minded people.
I have been using the software mostly for teaching but past students are using them at their workplace with great success.
Vorteile: Two things: documentation and the easiness to do networking which is very important for anybody who is interested on working in the area.
Nachteile: Would like to see more practical examples of BIG projects but I suppose many of them are property of the company that developed them.
Antwort des Softwareanbieters
von Palisade an 25.4.2019
Thank you, Alicia, for taking the time to write this glowing review of our software! We are so appreciative of customers, like yourself, that spread the word about @RISK and Monte Carlo simulation. Your description of Monte Carlo simulation is perfect and helps to demystify it for those that aren't familiar with why Monte Carlo simulation can often times be a better option.
We have over 80,000 students a year using our software, some of which are probably your students! These students will typically enter the workforce being able to make better decisions using @RISK and Monte Carlo simulation.
Thank you, again, for your kind words and for being one of our valued users!
Bewertet am 12.11.2018
Feature rich software for Monte Carlo Simulation
Works within Excel as an add-in
Easy to setup and use
Distribution library is large, also like the distribution fitting option
Nachteile: There is no viewer available. User must have the @Risk license to interact with the results. You can always take screen shots but you cant interact iwth the data.