Description: This paper develops a new technique, which allows the analyst to maximally use all thte historical interest rate information available in forecasting interest rates. Interest rates' daily change do not follow a stationary random process over long time periods. Instead, the process is comprised of stationary periods, each a few years long, with relatively short transitional periods between different stationary periods.

Description: People naturally observe risk in the form of the range of experienced gains and losses which is usually represented in statistical terms by standard deviation. In most cases, there are not enough observed values to reliably discern the true amount of losses that are possible in extreme situations. Statistical techniques that have long been applied to insurance company risks are being used to extrapolate from observed risk to extreme tails of the distribution of gains and losses. These processes are essentially an extrapolation from the “known” risk of volatility near the mean to “unknown” risk of extreme losses. “Fat tails” is a term often applied to risks where the likely losses in rare situations significantly exceeds the predictions of a Gaussian (“thin tailed”) distribution. This paper will look at the relationship between the observed risk and the extreme risk in statistical insurance r isk models and discuss how we might create a discussion among model users about the appropriateness of that relationship for specific types of risks.

Description: The costly, time-consuming and complicated process of enterprise risk management (ERM) can be improved in many companies and made less tedious for managers by using reasonable data and templates obtained from peer group entities. The models used to calculate economic capital (EC) often underestimate its value because they do not consider decision-maker perception about risk. We assume here that managers, as the decision-makers, have appropriate business understanding and they can provide substantial information about risk characteristics regarding all business processes. Therefore we are focused, in this paper, on collecting data from managers across the different businesses to derive the appropriate knowledge about risky events, the importance of particular types of risk, the relationship between the risk outcomes and the level of risk control in a particular industry. We conclude that the collected data has a high potential for use as a benc hmarking reference and analysis for improving ERM models for individual businesses.

Description: The U.K. Pension Protection Fund (PPF) was established in April 2005 to protect the pensions of members of U.K. private sector defined benefit pension schemes that have insufficient assets and whose corporate sponsor fails. The Fund takes over the pension scheme assets and assumes responsibility for the payment of compensation to the former members of the scheme. The PPF is funded by a levy on the population of eligible schemes. To improve its ERM framework, the PPF has undertaken a reverse stress testing exercise. This analysis provided the organization with new insights into its risk profile, the scenarios leading to the PPF’s potential “failure,” and interactions between these scenarios. This paper discusses the principles and objectives of reverse stress testing in the special case of the PPF and then illustrates the application of complex system science techniques for the purpose of reverse stress testing.

Description: This research report is on the incorporation of flood and other catastrophe model results into pricing and underwriting.

Description: While intended to assist health plan actuaries responsible for stress testing and ORSA filings, this session will also be informative for actuaries interested in communicating the impact of potential catastrophic events for health plans to their management and board. It will begin with a discussion of event thresholds for stress tests and their impact on capital and financial statements. Presenters will take a detailed look at several catastrophic event case studies (historical and hypothetical) in the following areas: healthcare specific (e.g. pandemic, specialty Rx), financial institution/credit market, operational/business, strategic and multi-event scenarios.</

Description: This research report models the impact on the U.S. insurance market resulting from a post-Brexit economy in the UK.

Description: Summary of the July, 2013 newsletter with an executive overview of each article.

Description: The academy generator is widely applied in actuarial practice. Initially confined to regulatory reserving, companies are increasingly using the AAA/SOA generator over an ever widening range of applications testing the limits of the academy generator's intended function. The session will give a brief overview of the academy generator and the asset classes it can be used to model. It will also analyze the statistical properties of the academy scenarios and discuss the scenarios relative to standard validation criterion. Some of the challenges that actuaries face in using this framework will be reviewed and options for addressing these challenges will be offered.

Description: Enterprise risk management ERM is for the measurement and the management of all significant risks of the business holistically irrespective of types and sources. The study offers significant advances in the current debate on the performance of enterprise risk management, in particular, minimizing the existing gap between the academic understanding and practitioners’ experience on the topic.