Efficient Risk Management Through Simulation: The antares House Distribution Simulation for antares RiMIS®
Jürgen Günther | July 15, 2026
Simulations are a suitable tool for aggregating quantified risks and opportunities. In this process, individual risks are assigned probability distributions (usually based on expert estimates). The practicality of the distributions used here is based on their ease of understanding and flexibility. Depending on the distribution, the quality and accuracy of the results may also vary.
House Distribution
antares RiMIS® now offers the option to simulate risks and opportunities not only using the standard probability distributions but also with a special distribution adapted to practical considerations, which we call the “house distribution” due to its characteristic shape.
Specifically, it offers the following advantages:
- Significantly greater flexibility than the standard triangular distribution.
- Extremely realistic due to weighting factors.
- Optimally adaptable to the specific risk.
The approach here is that, in contrast to the triangular distribution—which defines the minimum and maximum values as zero—the best-case and worst-case scenarios can be represented using so-called weighting factors that correspond to the relative (scenario) probabilities entered. Unlike the triangular distribution, the house distribution can have a positive density at the minimum and maximum. This is evident in the example diagrams (on the right).
Risk Aggregation and Quantification According to IDW PS 981 & PS 340
In addition, the probability of occurrence of the risks can also be specified (global probability of occurrence). If this probability of occurrence is, for example, 10%, then on average the risk is calculated to occur only in every 10th simulation run using the house distribution, while in all other simulation runs the simulated value is 0.
We offer a hands-on workshop on this topic titled “Risk Aggregation and Quantification According to IDW PS 981 & PS 340” for risk managers and controllers. During the workshop, you will learn how to:
- quantitatively describe your risks using appropriate probability distributions,
- measure them using appropriate metrics,
- describe interdependencies between risks,
- aggregate them using Monte Carlo simulation, and
- visualize the results.
Dr. Heiko Frings
Dr. Heiko Frings is our expert in the fields of business intelligence, business analytics, quantitative risk analysis, and the optimization of (re)insurance underwriting. His focus is on simulations and mathematical methods in the GRC domain.