Description: Often actuarial practitioners are faced with working with data that is less than ideal. The data may be observed with gaps in it, a model may suggest variables that are observed at different frequencies, and sometimes predictive analytic results are very fragile to the inclusion or omission of just a few observations in the sample. Data, particularly big data, are often "messy" and something must be done about it. What is the actuary to do about these very practical matters? These types of questions are what this presentation is intended to address. Concerns on missing data, outliers, nonlinearity, mixed-frequency, cross-correlations are illustrated using real datasets in the Asia-Pacific countries. Some possible solutions to the messy data problems will be discussed.

Description: Often actuarial practitioners are faced with working with data that is less than ideal. The data may be observed with gaps in it, a model may suggest variables that are observed at different frequencies, and sometimes predictive analytic results are very fragile to the inclusion or omission of just a few observations in the sample. Data, particularly big data, are often "messy" and something must be done about it. What is the actuary to do about these very practical matters? These types of questions are what this presentation is intended to address. Concerns on missing data, outliers, nonlinearity, mixed-frequency, cross-correlations are illustrated using real datasets in the Asia-Pacific countries. Some possible solutions to the messy data problems will be discussed.

Description: Article describing content and key takeaways from experience completing the SOA PA Certificate

Description: This video by Arthur da Silva, FSA, FCIA provides a primer on Application Programming Interfaces (APIs), which are mechanisms that enable communication and integration between different software components. The video explains what APIs are, how they work, and how they are used by actuaries today and in the future. The video also discusses the benefits and trade-offs of APIs, as well as some examples of common and actuarial-specific use cases.

Description: In this video, Jing Lang FSA, FCIA, MAAA, FLMI provides a panoramic view of the history and evolution of Artificial Intelligence (AI), from its theoretical origins to contemporary breakthroughs in deep learning, autonomous vehicles, and natural language processing. It highlights key milestones such as the Turing Test and the development of chatbots such as ELIZA, while emphasizing the ethical considerations that come with AI advancement, including privacy, bias, and transparency.

Description: An introduction to the methods and parameters for Bayesian Hyperparameter Optimization in a Life Insurance context.

Description: This video by Arthur da Silva, FSA, FCIA introduces the core concepts of cloud computing and cloud platforms, and explains the benefits and trade-offs of using cloud-native, cloud-enabled, and cloud-based applications. It also provides an overview of the current and future usage of cloud computing among actuaries. The video is aimed at actuarial professionals who want to learn more about the cloud and how it can enhance their work.

Description: In this video, Chris Smith ASA MAAA, a health actuarial consultant and data science enthusiast, introduces the basics of machine learning and its applications in actuarial science. He covers various techniques, such as unsupervised, supervised, and reinforcement learning, as well as neural networks and gradient boosting. He also discusses the potential risks and ethical considerations of using these advanced technologies in the actuarial field. Contributors: Chris Smith, ASA, MAAA, Jason Reed, FSA, MAAA, Mitchell Momanyi FSA MAAA, Jessica Calafell, FSA, MAAA; Jon Forster ASA, MAAA

Description: Early in his career, Ehren Nagel, FSA, MAAA, scoured through podcasts and articles about predictive analytics, long suspecting this was a field with potential for him.

Description: In this video, Dave Ingram FSA MAAA, a SOA board member and podcast host, discusses the ten AI risks that insurers face and the specific mitigations that can be used for each of them. He also explains the importance of having an AI Use Policy that covers various aspects of data governance, ethical guidelines, transparency, fairness, human oversight, and compliance. He concludes by noting that AI will evolve and insurers will need to monitor and remediate their AI applications accordingly. Contributors: Dave Ingram FSA, MAAA; Chis Lombardi, FSA, MAAA; Jon Forster, ASA, MAAA