Here we review GC Capital Ideas stories on the impact of insurance market cycles on insurers’ reserves.
1. Reserving Risks: “Dark matter” can be lurking on an insurer’s balance sheets in the form of a casualty catastrophe or an emerging and not as yet fully understood risk such as cyber. While there have been significant advances in quantifying the uncertainty pertaining to these risks, it is worth considering how they may manifest themselves in the future and what can be done about them now to protect from the “dark matter” downside.
2. Impact on Results: To consider the impact that these cycles may have on the financial statements and solvency positions of insurers there has to be an understanding of the magnitude of any change in ultimate loss and the likely timing of the recognition of that change. The profit or loss in any financial year is a combination of the profit and loss from that accident year and also any recognized changes in the reserves from prior years.
3. Cycle Mitigation: Part I: So what can be done to mitigate such cyclical effects? The first steps are to acknowledge them and to try to quantify their impact. The latter is more of a challenge than the former. Most internal capital models are not truly multiyear and arguably fail to adequately capture both the correlation between lines of business and in particular across accident years. Cycle (and recognition pattern) scenario testing is a good way to achieve this. This provides a neat and practical way to correlate between years and lines of business.
4. Cycle Mitigation: Part II: Incorporating reserve value added (RVA) into reinsurance decision making for long-tail lines is a step in the right direction. However, it is not the full story, as the decision is still typically made in the context of a single accident year and usually for a single line of business in isolation. The cycle correlations clearly show that this is sub-optimal. We are encouraging our clients a step further along the sophistication and hence simplicity/complexity spectrum.