Description: The presenters will cover the variation in risk adjustment approaches used across state Medicaid programs and compare them to other Federal programs. Additionally, recent developments, such as the use of OCR to extract data from medical charts for risk adjustment, will be discussed.

Description: This third session in the Munich Re series continues with an exploration of responses to the changing workplace landscape from those inside the industry. The presenters will focus on practical approaches to identifying new opportunities, and on ways in which traditional products and sales channels are changing to meet emerging needs. Are voluntary benefits still relevant? Yes, but they are changing. While the first session provided an overview of the future workplace, this session will provide an overview of the current and evolving voluntary benefits market. Sales processes and products will be challenged to change to keep up with the new workplace dynamic. The presenters share strategies for developing products and sales channels that are robust and flexible enough to address evolving customer needs.

Description: This presentation describes the Technology Enhanced Learning (TEL) Project for Actuarial Science Education, which aims to help budding actuaries solve actuarial examination questions and master classroom material.

Description: Natural Language Process (NLP) techniques can be used to find insights in large unstructured data sets and Word Embeddings are pervasive on a wide spectrum of NLP applications. These word representations improve downstream tasks such as Sentiment Analysis, Recommender System, and Topic Modeling. Learn how NLP transforms the Insurance Industry; and how word embeddings and pre-trained models improve the effectiveness and performance of NLP applications. NLP is increasing in importance for insurance companies. Additional application examples are available in session 36.

Description: Simple mathematical equations often outperform very complex ones in predictive analytics (PA) situations. This session will cover "why" and "how" to guard against overfitting and other potential pitfalls that might not be intuitive.

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: Interest rates steadily declining ever since the Volcker Fed tackled inflation in the early eighties. Ten years of stimulating monetary policy brought new lows. We should have braced ourselves for a return to neutrality, but that concept remains elusive. We will explore structural issues that have brought rates to these low levels and the potential impacts on the insurance business.

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: 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: With advancement of computing technology and innovative product design, creating dependent and nested stochastic scenarios to accurately predict insurance business has become more feasible and affordable than it used to be. However, can technology and research be accessible, applicable and beneficial to all the stakeholders? Sharing research findings and its validation tools has been our interest and focus, and even a resource-saving strategy. The presenters will share a case study on a segregated fund with hedging strategy. We investigate the reserve calculation for its GMMB in an extensive but simplified stochastic model so that our method is adoptable, applicable and extendable to real-word segregated fund/separate account model. The segregated fund model theory and implementation will be presented and its cash flows will be simulated and analyzed for reserve calculation. Varying parameter assumptions will be tested and to be modified for real-world segregated fund with hedging risk for guaranteed benefits. At the conclusion of the session, attendees will gain basic understanding of and access to: - The option pricing model and its application to the segregated fund (variable annuity's separate account) guarantee - Stochastic scenario generators for the interest rates and equity returns - R-code to program from the scenarios simulations to cash flows of hedging errors - Reserve calculations and its sensitivity to various parameter values and - Comparison of methods to increasing efficiency level and the accuracy