Models are used throughout the insurance industry to help predict risk, and the financial side of the business is no different. But these complex tools aren't just plug-and-play. Over the years, Conning has observed that many insurers ask similar questions about these models. Following are six of the most common queries that we answer:
1. How are sophisticated Economic Scenario Generators (ESGs) helping insurers make sound investment decisions in a continued uncertain interest rate environment?
There are a few things one needs to know about an ESG. An ESG provides critical insight into all the integrated moving parts of both the macro economy and the financial marketplace in which insurance companies operate. A comprehensive ESG appropriately represents economic and capital market events that could happen within an economy and, critically, across economies. Importantly, an ESG will depict not only possible economic scenarios and events, but also their relative likelihood of occurring.
So how does an ESG fit into the overall company risk modeling strategy? Well, an economic scenario generator is a key component of an enterprise risk management (ERM) approach that integrates all aspects of a company's functions in order to identify and manage internal and external risks and thus promote the overall financial stability and success of a company. An ESG feeds into the broader ERM framework and informs risk-based decision-making. Companies need ESGs to systematically capture the variability in the economic environment in which they operate and to identify and manage the risks that could threaten or undermine their businesses. It is a basic building block of systems used for asset-liability modeling, risk capital estimation, regulatory capital, and embedded value calculations.
2. What are some common misperceptions that you have heard in the market about financial risk modeling?
- They are decision making tools: Even the best possible models cannot take the place of effective business decision making that takes into consideration the holistic needs of the enterprise, its numerous operations and multiple stakeholders. Financial risk modeling does however provide valuable insights that inform a well structure decision making framework.
- They provide management with a false sense of security: It is important to recognize that the best models are based on assumptions, but a robust, comprehensive model that aligns with a company's basic assumptions offers significant help in aligning risk and reward. While even the best models cannot capture every possible risk, they do tend to alert management to many risks that otherwise might not be considered.
- Management can become slaves to the models: The models need to be part of a comprehensive risk management governance structure. Dependencies will tend to be a function of usefulness and the amount of insight a model can provide. A good model can and should be an important part of the financial risk management process within an insurance company.
- They are only useful for satisfying regulatory and rating agency compliance requirements: Initial studies have shown that good risk management correlates to increased values and lower financial volatility. Regulatory and rating agencies understand that good risk management is not simply a compliance exercise and will look favorably on companies that demonstrate that their capital modeling is a standard component of their internal risk management process.
3. As insurers prepare for 2014 and beyond, what key functionalities do they expect of state-of-the-art risk management technology? How do you expect risk management software to evolve over the next five years?
Enterprise risk management is becoming increasingly complex, absorbing more and more information about a company's risk exposures into its domain. This is requiring many companies to step back and reconsider the overall design of their risk management framework. Companies are concerned with how their various risk management models fit together, including computational requirements, documentation, assumption setting, data management, validation and back-end management reporting. There is a growing demand for risk management systems to be able to address all of these requirements in an efficient and user-friendly manner. We expect systems to continue to evolve in ways that will address these requirements.
What we are seeing is that more and more small and mid-sized companies are using risk modeling as part of their developing risk management programs. Naturally, as small and mid-size companies expand their risk management capabilities, they require pre-built functionality and flexibility, so the models can be used effectively with less staff. Geographically, we are seeing a significant surge in demand for ESGs in Asia, on a full ALM basis, both for investment optimization and economic capital modeling.