Description: Digital Long-Term Care Insurer for the Post-Coronavirus World.

Description: Principal Analyst Laurie M. Orlov of the Aging in Place Technology Watch will present a roadmap for the technology and ITSS marketplace. She will explore where it has been, what it does best, where it is going, and the challenges it faces. She has been a leading researcher and independent analyst in this field for more than 20 years.

Description: Actuaries today have unique opportunities to analyze, understand and use data for strategic decision making. With nearly unlimited computing power and a broad spectrum of data sources at our fingertips, we are enabled to support our actuarial judgment with comprehensive findings backed up by deep data analyses.

Description: ReFocus is an annual global conference for senior-level life insurance and reinsurance executives hosted jointly by ACLI and the Society of Actuaries (SOA). This event features top-notch speakers, thought-provoking sessions, and superior networking opportunities.

Description: 1994 SOA Spring Meeting, Orlando. This session is about re-engineering large actuarial systems. Large actuarial systems have become drains on human, computing and financial resources. And in some cases, daily actuarial functions have grown beyond the scope of normal cost-containment techniques. Re-engineering actuarial systems can significantly alter the trend.

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: Read how the world’s largest provider of specialty insurance for classic vehicles uses its media department’s YouTube videos to its full advantage.

Description: This article looks at how the underwriting process has transformed from a paper process to become fully online. Not only has the process been digitized, there has been various innovations incorporating technology thus enabling large volume process automation, better customer experience as well as higher closing ratio. Other than improvement on speed and efficiency, various smart solutions are being explored to refine risk management through data mining and analysis of underwriting data.

Description: The landscape of the reinsurance industry is evolving amid profound changes in the insurance sector. Innovation is vital for reinsurers as risks become more complex and insurers transition from a role of "protection" to "prevention." Successful reinsurers are responding to market dynamics, particularly through open innovation – collaboration with startups.

Description: Learn more about the predictive modeling that was applied to industry data for the lapse and mortality experience in the post-level term period. Novel approaches were taken to model the shock lapse, subsequent lapse, and mortality experience. Observe a demonstration of the Tableau tool, which was built to allow users to analyze data on their own.