Description: The speaker will discuss the training of neural networks to compute future Greeks of liabilities (or options) without the use of nested stochastics.

Description: The speakers will discuss the replication of long-term options, including a discussion of issues such as liquidity, transaction costs, slippage, impact of policyholder behavior, and machine learning algorithms to improve hedge effectiveness.

Description: Representing a large indexed annuity writer, the speakers will discuss the growth and evolution of the market for index annuity products. Moreover, the challenges that growth has introduced and how those challenges are being met. While much of the market consists of simple, accumulation-oriented S&P 500 based strategies with 0% return floors, a significant portion of industry sales come from more complex products with highly customized index strategies and other features, such as living benefit guarantees. Attendees will gain a broad understanding of the indexed annuity market, product and features, operational difficulties in risk management arising from product design, and how actuarial and hedge professionals are managing these issues.

Description: Large claims have always been a major source of volatility in health care claims experience. In this session, the presenters will discuss techniques for analyzing large claims, predicting large claims and measuring the associated risk. The presenters will also discuss the early results of the SOA 5/50 research project which will examine the 5% of the population that accounts for 50% of the health care costs.

Description: 1) Vision of the applications and development of data analytics in life insurance industry in Asia; 2) How big is the pie and what are the current obstacles insurers are facing; 3) Utilization of data and analytics target operating models as a competitive advantage, with focus on future readiness, controls, efficiency and effectiveness; 4) Potential roadmap ahead: a) Assessment of the current state of maturity levels of data and analytics initiatives; b) Identification of technology and competency gaps; c) Establishment of data integration and management process within BUs, alignment of advanced analytics tools across departments, with centralized data governance, technology structure and decision making framework; d) Definition of criteria and metrics to measure key outcomes and business value added. 5) Case study on agency behavior management: a practical example on how data analytics is being used in practice: (a) key business objectives: improve agent behaviors and maximize productivity with the lowest possible compensation costs; (b) data collection and current state assessment; (c) detailed predictive modeling process, modeling outcomes, and business implications; (d) implementation and monitoring process.

Description: This session will explain how, by applying his or her educational background and business experience, an actuary can quickly learn the basics of data science and perform the important modeling work of insurance.

Description: We will determine the role of risk function in evaluating operational risks associated with the implementation of LDTI and any system conversions. Are all models validated by the risk function before they are productionalized and results used by management to make business decisions? Does the risk function play a part in to assist finance, actuarial and investor relations in communicating changes and volatility resulting from LDTI? If not, should it? We will articulate the role that risk functions play in being part of large transformation from the start as a stakeholder/input provider to subsequently being an independent reviewer (i.e., second Line of defense).

Description: The arrival of ASU 2018-12 (a.k.a Targeted Improvements to the Accounting for Long-Duration Contracts or GAAP Targeted Improvements) presents insurers with augmented financial reporting risk across all areas of the valuation process. Naturally, the internal control frameworks that serve to mitigate these risks must evolve and expand. Valuation actuaries should view this transformative event as an opportunity to take an active role in developing new and improved controls that are both effective and sustainable.

Description: The speaker of this session will discuss some common difficulties one encounters when dealing with exotic equity linked derivatives. In particular, a study of a Monthly Sum Cap (MSC) will be presented. Pricing issues, along with dynamic hedging, as well as projections of MSC into the future will also be discussed. Time permitting, some aspects of historical performance will also be addressed

Description: This report describes and demonstrates a method to understand reputational risk that an insurance company can apply to the unique circumstances of the insurance firm. This method applies a policy-capturing survey with scenario analysis to generate insight into reputational risk from the perspective of a variety of stakeholders. Also included is instruction for spreadsheet-based query and reporting to facilitate the use of the information in the risk management function.