Join us next week in London and Frankfurt.

In the last few months, nearly 1,000 professionals from around the world have gathered to push the boundaries of risk analysis through the Palisade Risk Conference series. Since March, Palisade Risk Conferences have been held in Santiago, Chile; São Paulo, Brazil; Johannesburg, South Africa; Tokyo, Japan; and Shanghai, China. Decision makers from industry and academia have presented dozens of real-life case studies, applying sophisticated quantitative techniques in new and exciting ways. These innovative approaches use Monte Carlo simulation, optimization, decision trees, and other techniques found in Palisade’s @RISK and DecisionTools Suite software to solve a wide range of pressing problems.

Some examples include:

• Using stochastic modeling for financial analysis in the mining industry
  Presented by Collahuasi Mining Co
• Assessing the financial viability of new projects
  Presented by the Brazil National Development Bank
• Risk assessment of capital projects in the power industry
  Presented by PricewaterhouseCoopers
• Achieving optimal inventory levels to minimize cost
  Presented by Mitsubishi Chemical Company
• Risk assessment of food safety imports
  Presented by the Shanghai Food and Drug Administration
• Probabilistic risk analysis of cross-border oil projects
  Presented by Sinopec

Join us next week in London and Frankfurt! Upcoming dates:

• London – June 11th
• Frankfurt – June 13th
• Las Vegas – November 20th-21st

 » 2013 Palisade Risk Conference Series

Rafael Hartke's column in the April issue of Oil & Gas Monitor covers "Application and Benefits of Risk Analysis for Decision Making in the Oil Industry."

"Contrary to what may seem obvious on the surface, the driving force behind risk analysis is not statistics, simulation or intricate mathematical models – it is actually much simpler than that. To put it in basic terms, risk analysis is the acknowledgement that there is uncertainty over the assumptions of the project. Statistics and simulation are only tools that help model this uncertainty, and only when we recognize uncertainty over the assumptions of a project can we begin to consider appropriate actions and mitigation strategies."

» Read "Application and Benefits of Risk Analysis for Decision Making in the Oil Industry" in Oil & Gas Monitor.

Rafael Hartke is an Oil and Energy Industry Consultant at Palisade Corporation, where he assists in the development and strategy of quantitative risk analysis methods geared towards the energy industry. He also served as a Financial Engineer in Risk Management at Brazilian-based energy corporation, Petrobras, where he created risk models for complex investment projects and assessed project risks for medium and large projects, including Brazilian Pre-Salt giant fields, projects in the Gulf of Mexico, and offshore infrastructure projects. Palisade Corporation is the provider of the world’s leading risk and decision analysis software, @RISK and the DecisionTools Suite.

Palisade February 2013 Academic Enews
In This Issue

» Pepperdine’s Graziadio School of Business Leverages Palisade
   DecisionTools Software to Teach Students the “Why” Behind
   Decision Analysis

"Using [DecisionTools] software applications allows me to focus on teaching problem solving (what analysis to run, what assumptions to make, what inputs to use, and how to interpret the results), rather than the computational aspects, which would otherwise take up most of the class time. This is especially important in the fast-paced half-semester courses we now use."
     Dr. Joe Hahn, Pepperdine University

» Recent School Adoptions

» Licensing Options

» Teaching Tips & Examples
   Tollgates and Bank Tellers

» Tech Tip
   Artist Command

» Textbook of the Month
   Principles of Risk Analysis: Decision Making Under Uncertainty

» Featured White Paper
   Examination of Pig Farm Technology by Computer Simulation

» Academic Live Webcasts
   • @RISK for Engineers
   • The use of @RISK with an Online Investment Portal

» Worldwide Training Schedule

» About Palisade and the DecisionTools Suite

» Story to Share?

 

PricewaterhouseCoopers put together a beautiful video about the Corridor Budgeting program, developed by Tobias Flath and Michael Hofmann. Corridor Budgeting is a methodology combining planning, business management, and risk management in order to prepare for a range of possible outcomes, and thereby generate a more realistic picture of the future.

Palisade's DecisionTools Suite is an integral part of this program. As explained in the video: "We identify the factors underlying variables and ranges that impact on financial results. The Corridor is regularly analyzed and validated, giving visibility into any gaps or delta between target bandwidths and actual figures. Specially designed software then aggregates these bandwidths and event risks to paint an accurate picture of possible scenarios."

The video depicts modeling with Monte Carlo simulation: "A simulation models the total risk exposure. The width of the curve indicates the level of uncertainty. The height shows the likelihood that an event will occur, giving senior executives insights into the full spectrum of future possibilities, and making it easier to make the right decisions."

The video concludes, "Corridor Budgeting allows businesses to forecast more realistically, and prepare more effectively for what's to come, equipping them to face the future, however it turns out." It's a simple and beautiful explanation of how risk and decision analysis are a central part of business decisions today.

See PwC's Corridor Budgeting video here:

@RISK (risk analysis software using Monte Carlo simulation) is now a truly cross-platform tool, enabling risk modeling of your Microsoft Project schedules using the same @RISK you use for risk analysis modeling in Microsoft Excel!  You can now do your project risk modeling in Excel rather than Microsoft Project, providing a new world of flexibility. A new interface layer reproduces your schedule in Excel, enabling you to use all Excel formulas and @RISK functions. When you make changes to your model in either Project or Excel, those changes are reflected in the other with @RISK’s Sync feature. (Note that all @RISK modeling takes place in Excel, so @RISK functions do not appear in Microsoft Project.) Then simulate your Project schedules in Project itself, using Project's scheduling and calculation engine.

The benefits of using Excel for your Project risk modeling are many.  You can easily build risk registers in Excel for your Project model using new “RiskProject” functions.  You can integrate your cost and schedule analyses. You can standardize on a single tool – @RISK – to meet the needs of your project managers, cost estimators, finance analysts – everyone who deals with risk and decision making under uncertainty in your company. Plus, a single interface means a shorter learning curve for everybody.

@RISK is part of The DecisionTools Suite -- an integrated set of programs for risk analysis and decision making under uncertainty that runs in Microsoft Excel.

» Watch a demonstration of project risk modeling with @RISK
» See What's New in the DecisionTools Suite 6

 

The ongoing debate about the feasibility of offshore windfarms as a renewable energy source continues to generate discussion and headlines.

A key issue for potential operators is that offshore windfarms face more adverse weather conditions, such as higher wind speeds and the increased risk of being struck by lightning, than their onshore counterparts. In addition, a failed offshore turbine may take several months to repair, rather than a few days. The financial implications of repair and downtime must therefore be factored in to any calculations related to the feasibility of the operation.

This is made more difficult due to the inherent level of uncertainty involved. For example, the nascent nature of the industry means there is a shortage of historical data on the failure frequencies of the turbines. Even information that is available is subject to uncertainties – such as the prices of crane ships and access vessels (which may vary per season and even from day-to-day), the cost of spare parts, and the electricity price, as well as the lead times of spares and vessels.

However, using @RISK (Palisade's Microsoft Excel software add-in for risk analysis using Monte Carlo simulation) for probabilistic analysis, the Energy Research Centre of the Netherlands has developed an innovative approach to determine whether offshore wind farms are financially viable from an operations and maintenance perspective. The @RISK risk simulation software model produces a distribution that determines the uncertainty associated with the downtime and maintenance costs of an offshore wind farm. This enables a project developer to make an informed decision, firstly as to whether to proceed with the project and then, if this is affirmative, the best way to do so.  

Measuring the uncertainty also helps to make the project more viable in terms of financing. With the help of @RISK, wind farm developers – and their potential investors – can make informed decisions about whether an offshore operation will offer a good return on investment.

Beta 2 of Palisade’s new DecisionTools Suite 6.0 risk and decision analysis software is now available for download. Beta 2 includes the new time series simulation feature in @RISK 6.0, which allows you to model and simulate values that change over time. This is particularly useful in financial modeling and portfolio simulation.

» Download the DecisionTools Suite 6.0 Beta 2

Other key features of @RISK 6.0 include:

• Crystal Ball model converter
• Integration with Microsoft Project for simulation of Project schedules
• Easier-to-understand double-sided tornado
• Better distribution fitting

The DecisionTools Suite 6.0 is offers new versions of all products in the Suite: @RISK, PrecisionTree, TopRank, NeuralTools, StatTools, RISKOptimizer and Evolver.

» Complete list of new features
 

I attended e-learning micro-event event last week! It’s a great concept being used by Smarter Solutions. The concept is to provide short one hour training classes (“micro-events”) via the web for a very low cost. The micro event I attended was titled, Truly Understanding Hypothesis Testing Concepts: Making a Complex Topic Simple.  It truly lived up to its name; ~67% of the participants went away with a better understanding of Hypothesis testing after the hour.

The micro training event was led by Rick Haynes of Smarter Solutions. Rick is an excellent Lean Six Sigma Instructor, Statistical Consultant, Coach and mentor to process improvement practitioners. Rick did an excellent job using the tools at his disposal (even Monte Carlo Simulation using the @RISK software) to make this truly complex topic “simple”.

In case you don’t know, Hypothesis testing is a concept that is taught in Lean Six Sigma and statistics courses. During the event, he walked through the concepts of alpha and beta risk along with power and confidence choices using a completely different method than you would have been taught in a class. Through the use of diagrams and simulations, he made the hypothesis concepts real and understandable. Mr. Haynes, used @RISK was to test the Hypothesis test theory (a t-test), showing how the risk of each hypothesis test decision changed as the initial conditions of the test were changed where most classes just provide graphics and equations.  It was a powerful method to teach statistics.

If you are interested in viewing the recording of the micro training event it can be done so for a micro-charge of less the $25! If you do, please let me know your thoughts.

Join us this Thursday, February 16, 2012, for a free live webcast entitled, "How Capable are Your Capability Metrics? Using @RISK to Demonstrate Their Limitations," to be presented by Rick Haynes.

In the field of Six Sigma, there is a lot of discussion about the applicability of the traditional capability metrics. Cp, Cpk, Pp, and Ppk are very popular in some areas, but not all truly understand what the metric is trying to communicate about the process. In this free live webcast we will take a look at a typical data set to see how the capability index (Cpk) is reported based on different assumptions and calculation methods using risk analysis and Monte Carlo simulation software @RISK.

At the end of this webcast you will fully understand the usage of Cpk in regards to:

• Normal vs. non-normal data
• Stable vs. unstable data
• The uncertainty of capability estimates (confidence intervals)

Join us for this webcast, and you will never be confused or lied to by Cpk!

Rick Haynes has more than 20 years' experience in project management, training, applied statistics, engineering, and customer support. He has taught and certified professionals in all Lean Six Sigma areas. His consulting work has included all facets of business; building corporate performance dash boards, developing the Integrated Enterprise Excellence (IEE) system at a manufacturing firm, development of a process management and control system in a manufacturing firm, quality auditing of construction projects, developing reliability models for equipment failures, facilitating executive strategy development efforts, executive leadership coaching, modeling business performance for predictive analysis, improvement practitioner coach. Professional positions include; manufacturing site engineering manager, US Naval Officer (Submarines), corporate process improvement director, DOE research statistician, chemical process engineer, nuclear engineer.

» Register now (FREE)
» View archived webcasts

Creating a feasible budget is never easy, but it’s even more challenging during questionable economic times. That was the case for the Arc of Yates, an amazing organization in New York State that provides a wide array of services for individuals with developmental disabilities in Yates County.  For many non-profit organizations, funding often comes from local, state and federal sources. Given the current economic climate, Arc of Yates was faced with the prospect of slashed budgets on every governmental level, effectively leaving the organization with a fraction of the funding they have enjoyed previously.

With uncertainties as to where that funding would originate, Arc of Yates utilized risk analysis software @RISK to explore which areas of funding were most likely to be affected. Using probability distributions, Arc of Yates could forecast what portion of the current budget stream may not be available over the next three years. Subsequently, the organization could develop strategies to explore alternative means of funding. Now Arc of Yates has a clear plan of action to meet upcoming budgets for the foreseeable future.

We think Arc of Yates’ use of @RISK is a great example of how Monte Carlo Simulation can empower organizations and lessen the concerns and uncertainties that accompany a struggling economy. Knowing where potential shortfalls may occur offers decision-makers the foresight and flexibility to stay in front of budgetary gaps. On a personal level, it’s great to know that we were able---in some small way---to further the effort of a truly fantastic organization.

» Arc of Yates case study
» Take a look at the great work Arc of Yates is doing.

Randy Heffernan
VP, Palisade Corporation

Join us this Thursday, November 10, 2011, for a free live webcast entitled, "Petroleum Resource Evaluation Using @RISK" to be presented by Dr. Ronald Brimhall.

This free live webcast contains instructions and demonstrations for using @RISK risk simulation software to examine net present value economic analyses for a petroleum resource. In this case, the asset is a low pressure gas reservoir. The main applications of @RISK cover in detail the spectrum of petroleum engineering analyses – rock and fluid properties, reservoir volumetrics, material balance, analogy, decline curve, and net present value. Microsoft Excel statistics spreadsheets with @RISK are the primary analysis tools. Basic principles are emphasized with the understanding that fundamentals may be applied to the entire spectrum of reservoir oil and natural gas assets in cases where variability and uncertainty in all relevant parameters are important.

Variability in rock properties are demonstrated by analysis of electric logs, Variability in original gas is place in demonstrated by comparing volumetric analysis and material balance for generalized reservoir (includes water influx and water production). Application of decline curve analysis with uncertainty in decline rate is applied to NPV analysis. A result of reserves determinations and NPV is compared with an alternative investment opportunity.

Dr. Brimhall’s experience covers 50 years in industry and in academia. He was part of the Petroleum Engineering Faculty at Texas A&M University, and maintained a professional practice related to formation evaluations, resource evaluations, log and pressure transient analyses, production operations for oil, natural gas and groundwater, as well as environmental and resource assessments for subsurface operations in energy and groundwater resources. His past project management experience includes business development as well as proper utilization of environment & natural resources.

» Register now (FREE)
» View archived webcasts

Understanding how to use Monte Carlo simulation to account for risk in decision-making is quickly becoming a required skill for today’s business leaders, says Asher Drory, Adjunct Professor of Finance at University of Toronto’s Rotman School of Management.

“Many leading corporations are now using Monte Carlo simulation in their business cases,” Professor Drory says. “Students who want a leg up with such corporations should seek out all opportunities to get experience in working with Monte Carlo simulation.”

In his Financial Management course, Drory uses @RISK to teach some 200 graduate students each year how to use Monte Carlo simulation in analyzing working capital and capital budgeting decisions. Monte Carlo simulation furnishes the decision-maker with a range of possible outcomes and the probabilities that will occur for any choice of action.

For example, Drory's classes use @RISK and Monte Carlo simulation to look at:

• How forecasts of financial statements are needed to determine future funding requirements in working capital decisions.
• How forecasts of future free cash flows are required and risk must be assessed in capital budgeting analysis.

Separately, Drory and his students use Palisade’s PrecisionTree software in modeling decision tree analysis for new product development. The students have access to the entire DecisionTools Suite which is loaded on all of the computers in the Rotman Finance Laboratory.

“All key financial decisions such as investing, operating and financing decisions can benefit from Monte Carlo simulation,” says Prof. Drory, who has taught at the University of Toronto for 21 years. “I ran across @RISK about 5 years ago when I was looking for PC-based Monte Carlo simulation tools. @RISK has a straightforward and easy-to-use interface.”

» More about Professor Asher Drory
» More about @RISK

For their capstone design projects, undergraduate mining engineering students at Missouri University of Science and Technology develop “real-world” solutions. So, Dr. Samuel Frimpong provides his students with real-world tools, including Palisade’s @RISK software.

Similarly, he uses @RISK to help graduate students undertake research projects in geology and geological engineering, mining and petroleum engineering.

Dr. Frimpong says the risk analysis software helps students with risk modeling for everything from investment to production. Projects might include production forecasting, reserve estimation, exponential decline, and other key areas. @RISK also helps students understand stochastic processes – how random events can affect engineering phenomena over time.

“@RISK offers a comprehensive package for simulating stochastic processes defined by parametric probability and statistics,” says Dr. Frimpong, who has been teaching at the Rolla, Mo.-based university for more than 6 years. “The Excel environment also makes @RISK user-friendly.”

He also praised the software’s “efficient pre-simulation definition of input variables and post-simulation results.”

Dr. Frimpong says he has been using @RISK since his time at University of Alberta, Edmonton, Canada, where he completed his PhD in 1992 and later served as an associate professor of mining engineering.

A native of Ghana, Dr. Frimpong holds several patents in the area of oil sands extraction and is a noted expert in mine design, mineral economics, modeling methods and operations research.

» More about Dr. Samuel Frimpong
» More about @RISK

What do banks, bond-rating agencies and homeowners in places like Las Vegas have in common? They all grossly misjudged risk and, as a result, made bad decisions during the recent housing bubble.

That’s why Dr. Arnoldo Camacho, a professor at the highly regarded INCAE Business School in Alajuela, Costa Rica, incorporates Palisade’s @RISK software in his MBA courses – Finance I, and Financial Institutions and Capital Markets.

“The Finance course focuses on the creation of value through efficient decision making, which involves risk analysis,” says Dr. Camacho, who has taught at INCAE for 22 years. “In the Financial Institutions and Capital Markets courses, an in depth analysis of credit risk requires the estimation of the probability of default of issuers of debt.

“In both courses, @RISK is used for simulation and sensitivity analysis.”

Camacho was introduced to @RISK through INCAE, where his courses attract typically attract 60 to 65 students.

When asked why it is important to expose his students to @RISK, Camacho says, “It is easy to handle, and it allows students to move from uncertainty to risk analysis, which requires critical thinking.”

» More about Dr. Arnoldo Camacho
» More about @RISK

@RISK risk analyis software gives you multiple options for saving Monte Carlo simulations you have run and comparing them with other simulations.

These include:

• Storing simulations in your Excel workbook
• Saving simulations as a separate .RSK5 file outside the workbook
• Using the @RISK Library for storing and comparing different simulations.

When you want to store simulation results and graphs, @RISK allows you to keep all data in your Excel workbook. This makes it easy for you to give simulations to others, without worrying about sharing a separate simulation file. However, if you want to store the simulation results in a separate .RSK5 file in order to reduce the file size of the Excel workbook, you have that option, too.



When a simulation is saved in your workbook, all data and graphs are stored and will be automatically opened the next time you open the workbook in Excel with @RISK running.

You can also use the Application Settings command in the @RISK Utilities menu to specify the default location where you wish to store your @RISK data. These options make it easy to manage your risk analysis models.

» Read more about Saving Simulations

Today a moderately powerful earthquake rattled Washington, D.C. and was felt as far north as Massachusetts. Sitting here, feeling the earthquake shake my desk and water glass in central New York State, hundreds of miles from the epicenter, I was reminded that we are never far from the risk of natural disaster.

The Washington Post’s Jason Samenow wrote today that aftershocks are a significant concern. Although the 5.9 magnitude quake did not appear to cause significant damage, earthquakes are rare in the region and people are ill-prepared for them. According to the Post: “McNutt, director of USGS expressed a concern that the earlier quake will precede something more powerful: ‘What the concern is, of course, is that this is a foreshock. If it’s a foreshock, then the worse is yet to come.’ If not a foreshock, Mike Blanpied, associate coordinator for the USGS earthquakes hazards program cautioned aftershocks are possible: ‘Aftershocks could go on for days, weeks, or even months. They’re most likely to be felt under the next three or four days.’”

It got me thinking to ways that risk and data analysis techniques that we use every day in business applications could be applied in this situation. After all, the use of Monte Carlo simulation and and decision trees in DecisionTools Suite software has been used to cope with natural disasters – from volcanoes to hurricanes.

A few years ago the US Geological Survey asked the same question in an interesting study on the use of Monte Carlo simulation for the prediction of aftershocks in California. The paper, published in 2008, notes the typical absence of data specific to a particular earthquake site and examines the usefulness of Monte Carlo simulation for “assessing recurrence from limited paleoearthquake records.” In the absence of data, Monte Carlo simulation can be quite effective.

In a similar situation, the use of neural networks was examined by researchers in China to get a handle on the risk of aftershocks from the enormous 2009 Sichuan province quake. In their paper, published by the Journal of Sustainable Energy and the Environment in 2009, data from initial aftershocks was provided to a neural network so that it could “learn” any patterns in the aftershocks. These patterns were then used to predict future tremors. The concentration and trend of the aftershocks was predicted “precisely,” according to researchers.

In science as well as business, quantitative risk and decision analysis techniques produce tangible benefits that directly impact many of us.

Randy Heffernan
VP, Palisade Corporation

Join us on Thursday, August 25, 2011, for a free live webcast delivered by Tim Robinson and David Wilson, entitled "Use of Simulation Models in Pricing Health Insurance and Reinsurance Risk."

While healthcare claim costs are fairly predictable for large populations, existing pricing models often prove inadequate for that portion of the risk that is the most variable: large or “excess loss” claims typically covered by employer stop loss and other forms of reinsurance for high-cost claims. Even when rating and underwriting applications are able to accurately forecast expected claim costs, they are typically not structured to measure the variability in such claim costs from year to year. This is problematic when conducting detailed enterprise risk assessment studies or estimating capital and surplus requirements for health insurance programs. This webcast will illustrate some applications of @RISK risk modeling software to solving these problems. Examples will include Monte Carlo simulation models designed to quantify capital and surplus requirements for a health reinsurance captive; simulation models designed to price aggregate employer stop loss insurance; and simulation models designed to price aggregating specific or “inner aggregate” corridors in employer stop loss insurance.


Tim Robinson has over 20 years of experience as a healthcare actuary. He has a broad range of actuarial, underwriting and management experience working with diverse organizations including reinsurers, insurance companies, disease management firms, health plans and employer groups.  Tim has worked most recently on developing innovative healthcare rating and underwriting models; strategic and analytic support for a variety of start-up health insurance programs; and underwriting applications of predictive modeling and large claims analysis.  He also has extensive experience with product development, pricing, underwriting and valuation work for insurers and plan sponsors.  Tim is a Partner with Windsor Strategy Partners, LLC.  He works with clients in the healthcare industry, directing actuarial and strategic analysis in support of their risk management goals and initiatives.

David Wilson is the founder and President of Windsor Strategy Partners. Windsor Strategy Partners is a specialized healthcare strategy firm helping clients develop and implement strategic growth and risk management initiatives. WSP’s clients include leading reinsurers, insurers, captive insurers, provider organizations, technology companies, employee benefit consulting firms, reinsurance intermediaries and investment groups. David leads the firm’s marketing and research effort and acting as a senior advisor to our clients and partners. David has been active in the health insurance arena for over 30 years. He is recognized as a leading expert in healthcare insurance and reinsurance pricing and underwriting. He is a strategic advisor to start-up and established companies in the health insurance field.

» Register now (FREE)
» View archived webcasts

Presented by Scott Mongeau of Biomatica at the
Palisade Risk Conference in Amsterdam, March 29, 2011

An energy development ‘risk / reward parity’ level is growing between new petroleum exploration and sustainable energy initiatives. This case uses a biofuel plant case study as an example of how a profitable business case can be made for a sustainable energy project using techniques commonly applied in petroleum exploration and engineering initiatives. The toolkit includes risk analysis using Monte Carlo simulation, sensitivity analysis, optimization, correlation, econometrics, decision trees, and real options.

The biofuel industry is expected to multiply its production by a factor of 50 by 2020. The uncertainties of government subsidy, tax credits, and loan guarantees are crucial to meeting biofuel profit margins. Stochastic analysis greatly improves the ability to pinpoint risk and to identify mitigation strategies. The case study uses @RISK to model biofuel project NPV, Evolver to suggest plant optimisation strategies, and PrecisionTree to guide strategic decision making. All of these software tools are part of the DecisionTools Suite.

The approaches presented have promise as a due-diligence tool for prospective sustainability entrepreneurs, investors, project managers, and firms.

» Read the full presentation

Most of Professor Luciano Arantes Rezende Costa’s students at the Brazilian Petroleum Institute work in the local oil industry.

So, when he teaches his 20-hour course on evaluation of petroleum exploration opportunities, he has to provide hands-on lessons his students can immediately apply in their own careers.

That’s where Palisade’s @RISK software comes into play.

"To illustrate the classes, I've created a very simple model in Excel for evaluating exploration opportunities and bidding on them," Prof. Costa says. "Using the flexibility of @RISK, I've included in this model uncertainty about how much petroleum could be found (recoverable volume); how much could be produced by year (production curve); and how much cash flow could be expected from the estimated production."

Prof. Costa speaks from experience. In addition to teaching at the Institute, he works full time for Petrobras, one of the world’s largest integrated energy companies. The Rio de Janeiro-based company currently produces about 2.6 million barrels of oil and natural-gas equivalent a day.

Prof. Costa first encountered @RISK while earning his master’s degree at Colorado School of Mines in 1997. He says @RISK continues to be one of the easiest ways to teach Monte Carlo Simulation, a computerized mathematical technique to account for risk in quantitative analysis and decision-making. "Students can visualize what is going on just by pressing a single button," he says.

"My classes are very practical because students can grasp the concepts easily and use @RISK to create new models for their own real-life problems," Prof. Costa says.

» Learn more about how Petrobras has integrated @RISK into their operations

A recent issue of the journal Insurance Markets and Companies: Analyses and Actuarial Computations featured the paper “Using Simulation to Support the Reinsurance Decision of a Medical Stop-Loss Provider.” The article, by Lina S. Chan of CP Risk Solutions and Dr. Domingo Joaquin of Illinois State University, uses @RISK to illustrate how Monte Carlo simulation risk modeling can help to guide the reinsurance strategy for medical insurers by evaluating different alternatives.

@RISK risk modeling software is widely used in insurance and reinsurance for premium pricing and loss reserves modeling. A 2006 survey identified @RISK as the third most widely-used software by actuaries, after Microsoft Office and in-house actuarial tools.

@RISK is used in insurance models that must account for frequency and severity of claims, for stress testing claims, for calculating event and operational risks, for modeling claims payouts, and many other types of risk assessments.

» Read the full paper
» @RISK in Insurance and Reinsurance example models