Deloitte AIS Helps Client Avoid Overfunded Position of Several Billion Rands, using 

In This Issue
What's New
» Deloitte AIS Helps Client
  Avoid Overfunded Position
  of Several Billion
  Rands, using @RISK

Case Study
» School of Mining Engineering
   at the U of Witwatersrand
   uses @RISK for Financial
   Analysis Modelling

@RISK Modeling Tips
» Insurance Claims with
   RiskCompound Cell

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Deloitte AIS Helps Client Avoid Overfunded Position of Several Billion Rands, using @RISK

Deloitte Actuarial and Insurance Solutions (AIS) is a specialist insurance and actuarial consulting team, based in South Africa, which operates in more than 40 countries worldwide. Their remit is to provide advanced analytical solutions that enable the financial well-being and solvency of their clients, who include many life and short-term insurers across the African continent, as well as energy and resource companies.

Deloitte AIS had a long-standing client in the energy and resource sector, with significant interest across a number of large mining operations in South Africa. They looked to the Deloitte AIS team to help them plan for necessary environmental rehabilitation requirements such that they would reduce the risk of funding shortfalls – as well as the risk of overfunding and inefficient use of capital – while maintaining regulatory compliance and facilitating proper and responsible environmental care and sustainability.

According to Jaco van der Merwe, Director of Short-Term Insurance for Deloitte AIS, the challenge with formulating these strategies is, ”both the financial liabilities and backing assets for the rehabilitation may exhibit volatility and random fluctuations, so it's important for companies to select financial strategies which minimize the risk of a funding shortfall while avoiding inefficient use of funds.”

Palisade’s @RISK software enabled Deloitte AIS to quickly and efficiently construct the financial models they needed to capture the nature and profile of the risks for both the company’s liabilities and the assets. In the past, the team would construct models manually in Excel. These models took significantly more time and effort and often cost more, as they required extensive error checking. The @RISK software enabled them to quickly build, set-up and populate their models, and provided elegant visualizations of their Monte Carlo simulations which ultimately allowed them to focus on the risks, instead of worrying about the modelling.

”@RISK speeds up and significantly simplifies the stochastic model-building aspects of our work. We can focus more on the strategies and advice and less on model building, debugging and error tracing,” said van der Merwe.

”With @RISK, we were able to construct a projection model which reflected the risk of 'mis-funding' throughout the life of the mines and the subsequent rehabilitation periods,” explained van der Merwe. ”As a result, we were able to highlight the appropriate funding options and strategies for our client which met their risk appetite and requirements.”

By modelling the risks with Palisade’s @RISK, Deloitte AIS was able to help their client avoid an eventual overfunded position of several billion rands. ”In addition, we were able to reduce the amount of contributions required by almost half, simply by applying a sensible investment strategy,” added van der Merwe.

» Read the complete case study

Case Study
School of Mining Engineering at the U of Witwatersrand uses @RISK for Financial Analysis Modelling
The School of Mining Engineering at Johannesburg's University of Witwatersrand in South Africa is recognized as one of the top mining engineering schools in the world. Mining engineers play a key role in the planning, exploitation, and excavation of mineral resources that are plentiful in South Africa.

Graduates of the mining engineering courses develop careers in the higher echelons of mine management as consultant engineers, specialists and senior executives of mining houses. The School is using @RISK to give students training in and knowledge of Monte Carlo simulation.

It's very important to give students a real-world feel of how mining operations are managed financially – before they head out into the professional world,” explains Professor RCA Minnitt. ”An understanding of Monte Carlo simulation is absolutely essential. Without this discipline's knowledge and use, robust and credible financial analysis is not possible. @RISK is an essential tool for both our undergraduate and post graduate programmes. In any one year, we have anywhere between 700 – 900 students in the School of Mining Engineering. All our students are exposed to Monte Carlo simulation via @RISK.”

”@RISK is very well suited for Monte Carlo simulation in academia,” says Clinton Birch, Senior Lecturer, who runs the Mine Financial Evaluation at the University. ”We value it greatly as a modelling training tool to give our students a head start in their professional careers. But we are also using it for broader mining industry related research, which is an important activity for the department.”

» See the complete case study

Product Spotlight
Insurance Claims with RiskCompound Cell Referencing
The RiskCompound function allows for the sampling of frequency-severity distributions. A powerful feature of the function is that the argument that corresponds to the severity can be a reference to a cell containing a formula, rather than just a single distribution function. This is often required in insurance modelling, as well as in some operations management situations. For example, to determine the total insurance claims payout, you must account for the uncertainty in both the total number of claims (frequency) and the dollar amount of each claim made (severity). This model contains a portfolio of potential claims of different types. Each claim has different parameters for the distributions of frequency, severity, and duration.

» Download the example model
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