Presentations
- Best Estimates: the ELRF and PTF models
- Modeling of Multiple lines of busines, segments and layers with applications to capital allocation and optimal reinsurance
- Loss Reserve Upgrades - A Pervasive Myth
Best Estimates: the ELRF and PTF models
The Extended Link Ratio Family (ELRF) and the Probabilistic Trend Family (PTF) modeling frameworks are described in the paper "Best Estimates for Reserves" (PCAS, 2000, included in CAS Syllabus of Examinations). In ELRF, average weighted link ratios (development factors) are formalized as regression estimators (Mack method), and extended to include other modeling components of interest (eg. intercepts, Murphy method). Resulting benefits include forecast standard error and testing that assumptions made by the model are supported by the data. In the PTF framework a model is built that captures the variation in the incremental loss development array, which is described using trends in the three directions: development period, accident period and calendar period and the variability of the data about the trend structure. The identified model fits (and projects for the future) lognormal distributions to each cell in the development array, conditional on certain explicit assumptions related to the historical experience, which can be amended as desired.
Click here to download the presentation.
Modeling of Multiple lines of busines, segments and layers with applications to capital allocation and optimal reinsurance
The MPTF modeling framework is used to design a composite model for multiple incremental loss development arrays. The identified model describes the variability in each array and the relationships between them (a la PTF models).This has applications to modeling multiple lines of business, segments, layers and credibility modeling. Relationships between arrays involve both process correlation and parameter correlation. Clusters of lines of business are designed where correlations between any lines of business in different clusters are zero. An optimal composite model forecasts lognormal distributions for each cell in each loss development array, including the correlations between cells within in an array and between arrays. These induce correlations between forecasts for each pair of accident years, calendar years and aggregates. (This talk assumes the attendees are familiar with the material in the talk "Best Estimates: the ELRF and PTF models" or the paper "Best Estimates for Reserves," PCAS, 2000).
Click here to download the presentation.
Loss Reserve Upgrades - A Pervasive Myth
Major misconceptions about the loss reserving process are widespread. We debunk a critical loss reserving myth involving loss reserve upgrades that is pervasive in the insurance industry.
The powerpoint presentation is available here, alternatively, an online discussion can be found here.
