Paradigm Shift and ICRFS™

Paradigm Shift and ICRFS™

A paradigm is a model, a theory, a set of assumptions or a frame of reference. It is the way we see, perceive, understand and interpret.

Thomas Khun in "The Structure of Scientific Revolutions" argued that every scientific breakthrough is first a break with tradition, a break from the usual way of seeing and perceiving things. You view things in a new and different way. A paradigm shift means that suddenly everything takes on a new different interpretation.

As soon as germ theory was invented it made dramatic improvements in medicine possible.


 

"In the Middle Ages, the Western world viewed bloodletting as one of the best means of healing the sick.
Because physicians believed that illnesses existed in "bad blood", they systematically bled people to rid them of illness.
If the patient's condition didn't improve, the logic of bloodletting simple dictated that they should do more - they just had to do it better this time.
This way of thinking persisted even into the early twentieth century".

"Thankfully, empirical science lead to the germ theory. ... A new revolutionary paradigm shifted their thinking.
The age of bloodletting was forever gone, and a new, life-saving paradigm of science replaced the old paradigm".

Stephen R Covey


 

ICRFS™, a long tail liability Enterprise Risk Management system, is simply the key to a new innovative paradigm for measuring and managing long tail liability risks in a unique integrated relational database.

The Extended Link Ratio Family (ELRF) modeling framework includes most regression-based extensions of the standard actuarial ratio techniques, such as the Mack and Murphy methods. It also provides the diagnostic tools for finding out whether the traditional link ratio methodology quantifies the volatility in the data and has any predictive power.

According to Fred Cripe, Chairman of the Policy Management Committee of the CAS, the ELRF modeling framework provides a "road map" from the Link Ratios Techniques (LRT) module to the PTF modeling framework. See Fred Cripes review of the paper "Best Estimates for Reserves".

The Probabilistic Trend Family (PTF) modeling framework is used to identify (build or design) a model for an incremental loss development array. The volatility in the data is summarized by the identified model that is represented by four easily interpretable pictures.

The Multiple Probabilistic Trend Family (MPTF) modeling framework is used to build a composite model for mutltiple lines of business (layers or segments) that measures the volatility within each line of business (layer or segment) and the two types of correlations between them.

The new paradigm affords numerous benefits and applications. Moreover, the tour de force of interactive user interface and computational speed coupled with COM technology hide astonishing engineering with features unlike any other long tail liability software product.

For details on unique applications and benefits view the online video demonstrations.

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