Videos marked with an (*) contain discussion of new content in ICRFS-Plus™ 12.
If for any reason you are unable to view the training or demonstration videos, please contact our support staff at email@example.com and we will arrange to send you a copy of the videos on CD-ROM. You will be able to run the videos from the CD.
The training videos should be used for hands on training. We suggest you run the videos on a separate computer using a data projector, and train as a group.
The only way you will learn all the new concepts and be able to exploit all the immense benefits is by using the system. Experiential learning is imperative.
It is important that you study the videos in sequential order as set out below.
- 3.1 Introduction to the Probabilistic Trend Family modelling framework, the three directions, and trends
- 3.2 Modelling M3IR5 in the PTF Framework
3. Introduction to the Probabilistic Trend Family modelling framework
3.1 Introduction to the Probabilistic Trend Family modelling framework, the three directions, and trends
The Probabilistic Trend Family (PTF) modelling framework is presented. This is not a method, there is not one model applied to all data, rather a model is identified which is appropriate for the data. That is, the model describes the trend structure by development period, accident period, and calendar period along with the quality of the volatility about the trend structure. The volatility about the trend structure is called process variability. It is an integral part of the model (see this video for why volatility is important).
The PTF modelling framework relates all the cells in the triangle in respect of trends. By contrast, in the LRT and ELRF frameworks, each accident period and development period are treated as a separate problem. However, trends do not only occur in accident and development time, they also occur in calendar time. The most important direction for projection in a loss development array is the calendar direction.
The properties of calendar trends and their projection into accident and calendar time are discussed. These properties are true for every real triangle.
3.2 Modelling M3IR5 in the PTF Framework
In this video, the TG M3IR5 is modelled. The data in the triangle was simulated according to the trend structure shown in the previous video. That is, one development period trend and three calendar period trends.
The default model in PTF estimates one calendar period trend. Residuals represent the trend in the data minus the trend estimated by the method. Accordingly, the residuals of the default model will indicate three trends in the data.
The diagnostic tools, model display, forecast scenario options, and forecast output are discussed.
Forecast results include:
- Forecast distributions for every cell in the triangle
- Forecast distributions for the aggregate of the cells including the total reserve distribution
- Calendar payment stream (critical for Enterprise Risk Management)