Description: Presented at October 1985 Annual Meeting. Discusses: Measures which should be used in setting objectives and in evaluating performance for insurance companies and product lines, Variations that are appropriate for stock and mutual companies and United States and Canadian companies, Qualitative considerations in interpreting and evaluating information by the management reporting system.

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.

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: 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: "Visual storytelling is frequently used to effectively convey complex actuarial concepts to our clients and other audiences. When talking about data visualization, we often focus on the explanatory aspect. But data visualization is also a crucial tool in developing insights from large and complex data sets at every stage of data analytics spectrum: • descriptive (what happened?), • diagnostic (why it happened?), • predictive (what will happen?), • and prescriptive (how do I influence what will happen?). In exploratory and modeling stages of data analytics’ project, we let the data tell the story or explore our intuition and hypothesis through data pictures. We demonstrate the power of visual display in healthcare data analytics through vivid examples from the healthcare case studies. These illustrations of data visualization exploratory power range from assessing the quality of data or examining outliers, to exploring variables’ relationships and trends, to hypothesis testing, to guiding in feature selection and models’ comparison and evaluation, to model validation. Throughout these illustrations, we will discuss principles of graphical effectiveness, excellence and integrity."

Description: Many new and innovative companies are leveraging technology to improve the effectiveness of the care provided to patients. They are employing better tools to identify patients who can benefit from specific programs that best meet the patient's need. They are also dramatically increasing the use of these programs by guiding plan members through the maze of offerings to match them with the programs that will be most beneficial to them. Employers are making these third party programs available to their members and Medicare Plans are using these new tools to identify emerging health risks for early intervention and more accurate risk scoring. This session will explore some examples of these programs, how they are being effectively integrated into the operations of health plans and how the results of these programs are being measured.The speakers will be:Raj Behal, MD, MPH,Chief Quality Officer, One Medical. Raj leads the quality and safety, value and innovation, and data science teams at One Medical. One Medical is changing the way primary care is delivered with a concierge approach with technology seamlessly woven into their offering. This includes booking appointments on line, virtual face to face care, accessible medical records and health reminders.Mylea Charval,Ph.D., CEO and Founder, Savonix. Savonix is a next generation cognitive assessment platform that brings clinical, evidence-based, and all mobile digital assessment of cognitive and emotional function. These capabilities are critical for early identification of the onset of dementia and for the proper risk assessment of seniors enrolled in Medicare Advantage Plans.Ed Cymerys, FSA, Advisor. Ed will serve as moderator. Over the last six years Ed has served as an advisor to a number of early stage technology companies looking to improve the way health benefits are being delivered.Dave Sotelo, FSA, MAAA, Actuarial Manager, Collective Health, Inc. Collective Health is an integrated solution that allows self-funded employers to administer their health plans, control costs, and take care of their people -- all in one place. They have effectively integrated more than 70 distinct third party solutions for self-funded employers and are rigorously assessing the impact of these programs