Description: The article provides a high-level, non-technical, introduction to artificial neural networks (ANNs) and deep learning with an application to risk management. The method relies on typical ANN components such as nodes, activation functions, and optimization through gradient descent.

Description: While many know that machine learning is a big deal and even have a general idea of what it is, many do not know what machine learning can do for them. As an alternative to citing achievements or explaining algorithms, this article outlines the challenges that occur in statistics and the solutions that machine learning offers. Some of those challenges include correlated predictors, missing data, data interaction, and prediction intervals. Corresponding solutions include regularization technics, missing value imputation with KNN, tree based models, and cluster analysis for backtesting.

Description: Discount rate curve construction has been a topic of renewed interest following recent changes in financial reporting standards. Interpolation is a key component of curve construction and can be conducted via an assortment of methods. This article explores six popular interpolation techniques and assesses how they perform with regards to desirable features of such methods: continuity of forwards, stability and locality, simplicity, and market consistency.

Description: This is the first of a two-part article introducing and elaborating an “Adaptor” strategy for ERM. Such a strategy is intended to fulfil two purposes: first, switching among four styles of risk-coping strategies in order to track qualitative changes in a business’s risk environment; and, second, to support the business in navigating with resilience through all the seasons of a business-economic cycle, i.e., of boom, bust, moderate, uncertain. This latter requires careful study of the nature of resilience, the familiar idea of bounce back, and the less familiar idea of bounce forward. Part I of our article is underpinned therefore by a supplementary document (available from https://riskviews.wordpress.com/adaptor-exceptionalism/), which addresses the issue of structural change in a business or economy. It draws heavily on ideas taken from the discipline of control engineering, as well as some from ecology, social anthropology, and economics. The entire two-part article is thus an exercise in cross-disciplinary Systems Thinking.

Description: A brief discussion on the importance of governance and documentation being in place. The article provides some resources to assist in the development, and the reasons behind having it in place.

Description: A preview of the details and content of the new Certificate in Climate Risk to be offered by the SOA beginning in early 2023.

Description: The direct and indirect effects of the pandemic have impacted many actuaries’ work since the spring of 2020. This article addresses three considerations actuaries should account for when using risk evaluation models which are focused on projecting remote, highly unlikely losses: model effectiveness, asset risk, and insurance (mortality and mortality) risk.

Description: This training session will include lessons learned in 2021 and revisit a presentation given last year, discussing the new Actuarial Standard of Practice (ASOP56), which fills in the gap for guidance on Actuarial Modeling. Prior to ASOP 56, actuarial judgement reigned where standards and guidance lacked. Learn the foundation for designing, developing, modifying and validating a model according to SOA guidelines. By attending this session, you will: • Learn how to identify model’s intended purpose. • Strategically extract input data and assumptions. • Use the level of detail required in output data as a consideration for model design. • Choose from SOA recommended validation techniques.

Description: This is the second of a two-part article introducing and elaborating an “Adaptor” strategy for ERM. Such a strategy is intended to fulfil two purposes: first, switching among four styles of risk-coping strategies in order to track qualitative changes in a business’s risk environment; and, second, to support the business in navigating with resilience through all the seasons of a business-economic cycle, i.e., of boom, bust, moderate, uncertain. This latter requires careful study of the nature of resilience, the familiar idea of bounce back, and the less familiar idea of bounce forward. Part I of our article is underpinned therefore by a supplementary document (available from https://riskviews.wordpress.com/adaptor-exceptionalism/), which addresses the issue of structural change in a business or economy. It draws heavily on ideas taken from the discipline of control engineering, as well as some from ecology, social anthropology, and economics. The entire two-part article is thus an exercise in cross-disciplinary Systems Thinking.

Description: Data is at the core of the actuaries' role within companies, but how can actuaries translate data insights into informed and actionable decision making? The key is communicating data insights into a language that transcends analysis and enables real-time decisions that can provide an advantage to your management team. Learn an approach to choosing a tool or medium for your data insights, questions to ask yourself to better understand the communication necessary, and perspectives on how actuaries can take a larger role in actionable decisions within the industry. Understand availability, quality, and practical application of data sources health actuaries can access easily, how that data looks, approaches to transforming data into decisions, how it enriches administrative and claims data, and applications to pricing and reserving. Finally, discuss implications of ASOP 23, ASOP 41, and ASOP 56 as it relates to this topic. By attending this session, you will be able to: - Create an action plan on how to transform data into messaging for your leaders. - Use real experiences to formulate a strategy to expand the actuaries' role in informing decisions within the industry, including examples, to illustrate how data can benefit financials of health coverages. - Understand the application of ASOP 23 (Data), ASOP 41 (Communication), and ASOP 56 (Modeling) as it relates to turning data into decisions. - Be knowledgeable about new sources of morbidity for medical care and LTC and how to acquire and apply this information in actuarial models.