Tag Archives: cat model

Integrating Catastrophe Models Under Solvency II

In terms of natural catastrophe risk, ensuring capital adequacy and managing an effective risk management framework under Solvency II, requires the use of an internal model and the implementation of sophisticated nat cat models into the process. But what are the benefits of using an internal model and how can integrated cat models help a (re)insurer assess cat risk under the new regulatory regime?

Internal Model Versus the Standard Formula

Under Pillar I of the Directive, insurers are required to calculate their Solvency Capital Requirement (SCR), which is used to demonstrate to supervisors, policyholders, and shareholders that they have an adequate level of financial resources to absorb significant losses.

Companies have a choice between using the Standard Formula or an internal model (or partial internal model) when calculating their SCR, with many favoring the use of internal models, despite requiring significant resources and regulatory approval. Internal models are more risk-sensitive and can closely capture the true risk profile of a business by taking risks into account that are not always appropriately covered by the Standard Formula, therefore resulting in reduced capital requirements.

Catastrophe Risk is a Key Driver for Capital Under Solvency II

Rising insured losses from global natural catastrophes, driven by factors such as economic growth, increasing property values, rising population density, and insurance penetration—often in high risk regions, all demonstrate the value of embedding a cat model into the internal model process.

Due to significant variances in data granularity between the Standard Formula and an internal model, a magnitude of difference can exist between the two approaches when calculating solvency capital, with potentially lower SCR calculations for the cat component when using an internal model.

The application of Solvency II is, however, not all about capital estimation, but also relates to effective risk management processes embedded throughout an organization. Implementing cat models fully into the internal model process, as opposed to just relying only on cat model loss output, can introduce significant improvements to risk management processes. Cat models provide an opportunity to improve exposure data quality and allow model users to fully understand the benefits of complex risk mitigation structures and diversification. By providing a better reflection of a company’s risk profile, this can help reveal a company’s potential exposure to cat risk and support companies in making better governance and strategic management decisions.

Managing Cat Risk Using Cat Models

A challenging aspect of bringing cat models in-house and integrating them into the internal model process is the selection of the ”right” model and the “right” method to evaluate a company’s cat exposure. Catastrophe model vendors are therefore obliged to help users understand underlying assumptions and their inherent uncertainties, and provide them with the means of justifying model selection and appropriateness.

Insurers have benefited from RMS support to fulfil these requirements, offering model users deep insight into the underlying data, assumptions, and model validation, to ensure they have complete confidence in model strengths and limitations. With the knowledge that RMS provides, insurers can understand, take ownership, and implement a company’s own view of risk, and then demonstrate this to make more informed strategic decisions as required by the Own Risk and Solvency Assessment (ORSA), which lies at the heart of Solvency II.

Disaster Risk Reduction: Catastrophe Modeling Takes the Stage at the United Nations

The UN meeting room at the Palais de Nations in Geneva is oval shaped and more than 100 feet long with curved desks arranged in a series of “U”-shaped configurations. Behind each desk, delegates sit with their placards. On the long desk at the front, from left to right the placards read “IIASA” (a systems research institute based in Austria), “Mexico,” “Japan,” “Netherlands,” and “Risk Management Solutions.”

What was RMS doing on the podium at the UN?

Last month I presented on investing in disaster risk reduction, giving the modeler’s point of view on how risk modeling can be linked with incentivizing actions to reduce the impacts of disasters.
This was a key meeting of what was called “PrepComm,” aimed at coordinating national action for disaster risk reduction. The first such agreement, known as the Hyogo Framework for Action (the HFA), initiated in 2005, is up for renewal in 2015. The plan is to create a tougher and more tangible set of goals and procedures with demonstrable outcomes to reduce the loss of lives, livelihoods, and wealth in disasters.

In some form, catastrophe risk models or modeled outputs are required for setting and monitoring progress in disaster risk reduction. I often use the story of Haiti to make the point: fewer than ten people were killed in earthquakes in Haiti between 1900 and 2009; then in one afternoon in early 2010, an estimated 200,000 people were killed. You cannot use previous disaster data to measure future disaster risk; the underlying distribution of impacts is so skewed, so fat-tailed, and so unknown, that a decade of disaster outcomes reveals nothing about the mean risk.

The UNISDR—the influential UN agency that focuses on disaster risk—recognized the power of probabilistic modeling five years ago. However, it remains hard to communicate that to monitor progress on disaster risk reduction you will have to find some proxies for impacts, or use a model. That was the subject of my address to this session. Borrowing a quote from Michael Bloomberg, sponsor of the Risky Business study for which RMS was the modeler of all the future coastal and hurricane risks: “if you can’t measure it, you can’t manage it.”

The delegate from Algeria was skeptical about how to get the private sector involved in disaster risk reduction. I told the story of Istanbul, where the government makes deals with developers to demolish and reconstruct the most dangerous apartment buildings, rehousing the original occupants while the developer profits from selling extra apartments.

The Philippines wanted to know about empowering local authorities. My answer: get the future risk-based costs of disasters on their balance sheet.

Austria wanted to spread the idea of labeling the risk on every house. The Democratic Republic of Congo wanted to know why conflict is not considered a natural hazard. There were many questions and points of discussion over the course of the meeting.

When the next iteration of HFA arrives in a few weeks time, we will see how all the advice, debate, and consultation from the UN meeting has been digested. Regardless, when governments sign off on the new protocol in Sendai, Japan next March, catastrophe risk modeling is likely to become a core component of the global disaster risk reduction agenda.

Because as Michael Bloomberg said, “If you can’t measure it, you can’t manage it.”