Description: Hop into a panel discussion between InsurTech Advisory Council and a startup, followed by a demo of life event prediction and analyses with multiple applications across financial services. You will also learn about: the SOA office hours program and member participation, the startup ecosystem filled with incubators, company contests, opportunities and outcomes, how to build a data set providing additional insights for customization and enhanced user experience, and - actuaries' engagement with startup strategic advisory boards.

Description: Analyzing large quantities of raw complex data is often a challenge in the health care industry. During this webcast, there will be a demonstration of how unsupervised machine learning techniques can be applied to such data to help bring useful insights. This will include examples that use unsupervised learning techniques spanning dimensionality reduction, clustering and anomaly detection.

Description: Artificial Intelligence (AI) has become a key component of the insurance landscape and getting full value from an AI depends on much more than simply building the model. Please join us to hear the challenges and potential solutions around successfully deploying an AI-driven initiative within an organization. Hear from panelists as they describe the human impacts of model implementation, how to assess a model for effectiveness and (lack of) bias, and detail the journey of implementing AI-driven underwriting models at a large insurance company.

Description: Pandemics are a main driver of losses for both life and non-life (re-)insurance. Until COVID-19, risk assessment mostly relied on a few historic examples, most importantly the Spanish flu. The COVID-19 pandemic has shown that other pathogens (namely the coronaviruses) need to be taken into account. Also, modern societies and governments drastically respond to novel threats and implement measures such as social distancing, mask mandates, and lockdowns. Besides the properties of the pathogen itself, these reactions and the medical progression (namely the development of vaccines) are key influences on the course of a pandemic, and thus also the resulting outcomes. To account for the new insights, join us as we take a look at a stochastic, age-structured compartmental model that is calibrated on recent pandemics with several parameters sets to model different levels of reaction speed and stringency between groups of countries. Other important factors also must be defined in close collaboration with experts. Get ready to explore the development of a model and framework that can provide potential outcomes to be used as the basis to derive both summary and tail statistics to assess pandemic risk and help price complex deals.

Description: Electronic Health Records are here to stay. Take a deep dive into the world of electronic health records and how the industry is poised to utilize this new form of digital medical data to transform the way policies are underwritten and ultimately, transforming the client experience. Listen to industry experts speak about what they are doing to use this data most effectively and how this ultimately develops into ground-breaking solutions for the industry.

Description: Analyze the market volatility behavior in context with historical extreme events during this webcast. There will be a focus on understanding volatility clustering and relationships, both contemporary and temporal, in addition to key economic and capital market variables. You'll also learn from a comprehensive attribution analysis, which uses economic data, asset data, retail investor data and event data as explanatory variables. Dive into investment-related Reddit comments used to capture features of retail investors and tree-based models, including Random Forests and Gradient Boosting Machines to justify changes in volatility modeling. Expect this webcast to end with an example of liability-driven investment optimization that illustrates the potential impact of increased volatility assumption, how to adopt stochastic volatility models, how to reflect volatility clustering and return jumps.

Description: ALM and hedging can reap significant benefits from innovation in computation and operations research. Explore applications of static and dynamic optimization in two different ALM and hedging use cases. Insurers are increasingly moving offshore by establishing Bermuda captive reinsurers. In calculating the Bermuda Best Estimate Liability ('BEL'), reinsurers will need to segment assets to support liabilities in each treaty. A Linear Programming ('LP') problem can be formulated to tactically select assets in a way that minimizes the BEL and consequently the total asset requirement. Learn more about what US Variable Annuity Insurers face with the regulatory requirement to reflect 'future hedging strategy' in their statutory funding calculation. The traditional numerical method of finding the optimal hedging target and then allocating assets may encounter the curse of dimensionality with expanding product and economic environment complexity. A Reinforcement Learning algorithm may well fit this problem and provide insurers a solution for dynamic hedging.

Description: The industry sees extreme value in predictive modeling and its ability to help us meet customer demands and remain profitable, but do customers and regulators look at this as a favorable addition to our process? Hear from a dynamic panel of industry experts who will tackle a variety of issues and questions from the state of the regulatory environment to the responsibilities of the carrier.

Description: As the speed of technological innovation increases, actuarial leaders are trying to determine how to use emerging technologies to unlock more business value and improve competitive positioning. This includes enabling new capabilities, improving process efficiency, and increasing the effectiveness of human capital. The session will discuss what we are hearing from clients who are in the process of transforming their business, how they are approaching these transformations, and what they are focusing on. This will include different aspects of transformation, including visualization dashboards, data science applications, no-code platforms, automation, data, and the cloud. Find out how organizations are thinking of human capital and collaboration between actuaries, IT, and other professionals.

Description: Predictive analytics projects in the life insurance industry are oftentimes set up as research ideas leading to intangible or unusable results for the practicing actuary. What if you could change that? What if the research turned into development and practical use through leveraging valuable resources properly? Learn how to structure predictive analytics projects, and about the project team, so there will be actionable takeaways for the business unit. Specific areas of value for you include underwriting, experience studies, assumption-setting, and product development. Watch as presenters talk through real case studies on turning a predictive analytics project into workable solutions rather than a resource drain, an unclear goal, or a misunderstood business need, which are some of the pitfalls of a poorly planned project.