Description: The article is Part 1 of two articles that provide a case study for the development of a profitability and risk dashboard. The sample dashboard provides distilled information regarding actual to expected (A/E) ratios for key risks, agent quality scores and customer value scores. The dashboard would also provide the value of new business written, surplus strain, debit balances, and expected losses on debit balances at different levels, down to the agent level. A product mix index is provided, together with visual comparisons of key metrics to the company's business plan. The Part 2 article will add information to the dashboard regarding risk margins, target capital, and company value.

Description: The work of Patrick Getzen and his team requires technical skills and strong problem-solving abilities to help them move quickly in a changing environment.

Description: If anyone is a paradigm of the notion that learning never stops, it’s Head of Actuarial Modeling and Experience Study for Munich RE Winnie Liu. Winnie set her sights on new horizons after almost 20 years in the insurance industry. Her interest in cutting-edge predictive analytics had been budding for years, and in 2017, she set out to earn her Predictive Analytics (PA) Certificate from the Society of Actuaries (SOA).

Description: View 2018 Kaggle Involvement Program Results.

Description: Cover a variety of topics centered around the unsupervised learning technique called 'clustering'. The presenters will take you through a wide array of topics that range from 'What is Clustering?' to 'How can I use this technique to solve problems I didn't even know existed?' In the health care industry, everyone is looking for an edge in reducing total spend-cluster analysis finds the unambiguous in an ambiguous framework of results.

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: 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.

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: In this webcast, the presenter will cover mental health in insurance products. Learn about the public’s increased interest in mental health and the ways insurers can meet this demand, how we can embed such offerings in insurance and how to successfully expand mental health coverage to those in need. The second speaker will cover how cancer and the simplified issue insurance market has evolved in Korea. In this session, the speaker will share the ease of selling / onboarding, thus allowing a greater penetration of products.

Description: This session will explore governance considerations for insurance carriers leveraging machine learning models. During the session, panelists will share insights on the evolving predictive model and AI regulatory landscape, as well as techniques for developing or enhancing AI governance frameworks that comply with emerging regulatory guidance.