In the last two editions, we improved how loss ratios are understood - first by testing whether they are credible, and then by identifying what is driving them. It provided a clearer view of internal performance.  But capital is not assessing internal performance. Capital providers are asking what risk they are backing - and whether it justifies the capital. The way most portfolios are presented does not answer that question. The Decision Question Is the portfolio attractive

The Decision Question Week 1 answered: Are we performing above or below expectation? The next natural question is: What is driving the change in loss ratios? Loss ratios can move because of: claim frequency claim severity large losses Without separating these drivers, pricing decisions risk targeting the wrong lever . A loss ratio of 75% can mean very different things: Stable, credible portfolio Large exposure base, predictable development, stable frequency → 75% is informa

How underwriting performance is typically presented The Decision Question Is the portfolio performing in line with the priced expectation, and is the signal credible enough to act on? Underwriting committees usually want to know: Are we above or below target? Is it material enough to matter? Is the signal reliable or noise? Default Practice The most common chart (shown per product / line):  Single line of ultimate loss ratio over time vs a target or benchmark. Why this works:

The Decision Question In edition 3 we concluded that the scatter signals when a question should be asked but does not answer it. This edition addresses one of those unanswered questions: how did each accident year evolve? The Dumbbell View of Revision Behaviour This visual gives a view of ultimate estimates by accident year, showing the initial view, the current view, and the movement between them. What This Makes Visible Direction of Revision by Accident Year For each accide