Description: Certain valuation assumptions are difficult to set with a high degree of accuracy, whether because the underlying experience is in different economic or interest rate environments, in addition to other reasons. Examples include assumptions for long-term care insurance, annuity options, lapsation and premium persistency on ULSG. This session will share how the actuary can use predictive analytics to augment the assumption-setting process. Some of the benefits to the actuary (along with the company and the regulator) include more accurate assumptions with lower margins for adverse deviations. Of possible interest as well is that applications go beyond valuation and include acquisitions, reinsurance and pricing.

Description: While it is now almost universally accepted that data can bring value to the insurance industry, there is little guidance on exactly how to make that value tangible. This session goes beyond advances in computing and storage technologies and is aimed directly at business leaders. This session will define what a data strategy is, discuss the main components, describe how to get started creating one, and will outline how to translate a strategy into execution.

Description: Maintaining solid financial performance is a KPI for senior management. With the advancement of technology, the management can leverage new techniques to improve their decision making and focus on higher value activities in a timely manner. This presentation sets out the use of 1. correlation analysis to draw relationship between financial metrics and 2. smart analytics techniques, including text mining and analytics, to identify trends and drivers that impact the valuation of a company. We will also assess how the results of a comprehensive financial analysis could influence risk management considerations, including business steering and risk strategy.