Description: This research report that provides a literature survey of methodologies applying machine learning to insurance claim modeling.

Description: Insurance is a technically demanding, risk-based, capital intensive business. It is therefore not surprising that the industry is fertile ground for the development of technical models used to measure and price risk and manage capital. This session presents the forces which have significantly influenced the evolution of risk and capital management techniques and organization in the insurance industry, including regulatory changes, financial market instability, enlightened self-interest and ultimately a focus on shareholder value creation. Combining over 20 years in the industry in risk and finance roles with a rigorous academic approach, the presenter will provide insights into the most important business questions which insurers face today and the technical tools and frameworks used to answer them.

Description: A critical step in valuing a company for the purpose of financial reporting is the computation of the market value of economic surplus (MVES). This article provides a novel approach to the valuation of MVES that is stable and reasonably immune to “market noise.” Current approaches to the calculation of economic surplus of an insurance company generally define such surplus as the market value of the assets (MVA) supporting the liabilities less the market value of liabilities (MVL). While MVA is observable in the market, MVL is typically computed directly, without regard to the underlying supporting assets. Subtracting MVL from any value of assets that changes with market movements results in an unstable surplus. Consequently, a surplus that is not fully reflective of market sentiment has been rejected by many. This same approach is further used in the calculation of market consistent embedded value (MCEV) when a balance sheet approach is used .

Description: There is no “industry standard” approach to managing the vega (volatility) risk inherent in Variable Annuity Guarantees, Fixed Indexed Annuities and other equity-linked obligations. In this session, we will introduce and analyze a range of reinsurance solutions, including full vega risk retention, full vega risk transfer and more sophisticated or custom structures that split the vega risk between the insurer and the reinsurer in various ways. We will also explore other approaches in bespoke risk coverage and show the impact of different assumptions on a generic “VA Guarantee Cost Estimate” that has been developed by Munich Re.

Description: Article provides a brief summary of the highlights from a survey completed in fall 2018 covering Emerging Risks. This is the 12th iteration of the survey and provides trends and qualitative comments from respondents on a variety of ER and ERM topics. Climate change and cyber risks continue to lead the responses.

Description: Article provides a brief summary of the highlights from a survey completed in fall 2018 covering Emerging Risks. This is the 12th iteration of the survey and provides trends and qualitative comments from respondents on a variety of ER and ERM topics. Climate change and cyber risks continue to lead the responses.

Description: This article, Spreadsheet Controls Add Risk Resilience, spotlights why spreadsheets have stood the test of time and how they help contribute to an actuary’s success. It also discusses common causes of data integrity issues relative to spreadsheets. And, offers insight into controls that can be utilized to helps actuaries solve these issues and ensure the accuracy and consistency of the data on which they base their analysis.

Description: This research report that provides a literature survey of methodologies applying machine learning to insurance claim modeling.

Description: Analysis tool associated with the research report that models the impact on the U.S. insurance market resulting from a post-Brexit economy in the UK. keywords: European Union;Brexit;Insurance industry

Description: This research report that provides a literature survey of methodologies applying machine learning to insurance claim modeling.