Description: Introducing Random Effects into Risk Score Models

Description: Come discuss the benefits and challenges of collaboration between academic institutions and industry stakeholders in shaping actuarial education and research agendas. Register for this event now.

Description: In this presentation, actuaries and data scientists from Cleveland Clinic and Milliman discuss the development of a sepsis prediction model using machine learning. Presented with a unique challenge of handling massive amounts of data for near real-time risk scoring, the team took their model development to the cloud and delivered a product in less than a week through a unique virtual engagement.

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.

Description: How might retirement income strategies be designed, and their suitability assessed, when retirees may differ substantially in their objectives, preferences and personal circumstances? This webcast provides a wide-ranging overview of the key elements involved in formulating retirement strategies, drawing on the “Primer on Retirement Income Strategy Design and Evaluation” that was recently released by the SOA. It will cover three types of income objective – income floor, income target and income optimization – and how they imply different retirement strategies along with a different set of metrics to evaluate outcomes. It will also touch on: key member attributes to account for; the nature of income risk; approaches to investing and drawing down on available assets to generate income; and how stochastic modelling can support the analysis. This webcast should deliver something of interest for all attendees, regardless of prior familiarity with strategies for retirement.

Description: Much of the work performed by disability insurance actuaries depends on the availability of accurate and detailed data, which is not always as simple as it sounds. Explore a variety of data challenges faced by disability actuaries, along with potential solutions. Potential topics include finding relevant data, the impact of poor data on valuation work, the impact of new privacy rules, and the potential bias in the data used to develop predictive models.

Description: Cluster modeling is emerging as a powerful technique to manage cloud costs and run time. It also enables quick responses to "what if" scenarios, and aids in attributing results between reporting cycles. In this webcast, we provide insight into cluster modeling, present case studies that focus on various key performance indicators and discuss the benefits and challenges to cluster modeling from an insurer’s perspective. We also discuss the considerations associated with moving from an on-prem based computing solution to a cloud-based approach.

Description: Learn about the industrial practice for constructing the mortality table from 0 to 1 through journeys in Hong Kong and Singapore, including key takeaways. Hear speakers share their biggest challenges during their process, how they resolved them, and discover the most common technical issues faced in conducting the mortality tables.

Description: In this session, we will delve into the powerful capabilities of two essential algorithms in the field of data science and machine learning: Generalized Additive Models (GAM) and CatBoost. These algorithms can play a crucial role in conducting experience studies for insurance.

Description: The importance of storytelling in financial communication and its role in conveying complex financial reporting results and insights to diverse stakeholders cannot be denied.