Description: Technology is transforming the retirement space and more changes are expected in the future. Join a panel of experts to discuss what are the opportunities, trends and challenges associated with new technologies in the retirement landscape and how it is expected to impact consumers, if we can enable their successful integration.

Description: Data is an essential component of financial analysis. In this session, the presenters will discuss data governance/management framework and how it can be applied to US GAAP LDTI and VM-51 regulations. This session will also discuss the important relationship between actuaries and IT and how they can work together towards best practices for extracting, managing and using data needed for various actuarial models. Real life case studies relevant for valuation actuaries (e.g. data needs for LDTI and VM-51) will also be presented and examined, highlighting best practices as well as challenges and pitfalls for setting up and governing data processes along with areas for where good communication and strong relationships are important to success.

Description: Predictive modeling continues to gain traction in the life insurance industry with the rapid growth of available data and maturity of open source tools. New methods and technology in predictive analytics have enabled the evaluation of extremely large data more quickly and allow us to incorporate features previously not considered. The presenters will provide background on predictive modeling tools and algorithms utilized by actuaries and data scientists for life insurance, highlighting applications from marketing to underwriting.

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: 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: This second session in the series examines responses to the changing workplace landscape from outside the insurance industry. Using a question-and-answer approach with our panelists, this session focuses on practical approaches to identifying new opportunities, and ways in which traditional products and sales channels are changing to meet emerging needs. Compared with other vertical financial services, the life insurance industry has a very low level of 'touch' with its customers. Communication with customers is often limited to the annual mailing of premium invoices. Wellness platforms offer life insurers a means to increase customer engagement, building stronger brand affinity and improving persistency. Life insurers can also leverage customer data collected through the wellness platform to streamline the underwriting process for cross-sales, increasing volume and efficiency.

Description: The SOA launched the Actuarial Innovation & Technology Strategic Research Program earlier this year, focusing on projects in which technology is being used in actuarial work. The presenters will highlight reports from the program including a review of the Top Actuarial Technologies of 2019, the growing use of cloud computing and its impact on furthering and deepening actuarial analyses, and the growing innovative approaches using non-traditional data sources for risk selection and segmentation and its intersection with industry regulation. An overview of this new SOA research initiative and key findings from recently released reports will be covered.

Description: Digital is the main reason over half of the companies on the Fortune 500 have disappeared since 2000." (CEO Accenture). We cannot be sure how global technology megatrends will disrupt the life insurance industry, but we can be certain that the future will not look like today. As large quantities of available data are no longer owned by insurance companies and statistical techniques become more accessible to non-statisticians, the pressure to keep up with technological advancement increases. Life actuaries must think critically about and be prepared for the coming changes and position themselves as leaders in an industry lagging behind in new technology adoption.