Description: APL is both a unique form of mathematical notation and a programming language. As a notation it has intrinsic appeal and gives rise to many elegant and ingenious definitions of mathematical concepts. As a programming Language, or system, it also provides the user with instant evaluation of these concepts. The combination is extremely powerful, and some interesting applications may be demonstrated with respect to annuities.

Description: The key tasks of credit risk capital project under CROSS II mainly focus onL(1 )Adjustment of measurement framework; (2) Calibration of risk factors, including both credit spread risk and credit default risk;3)Introduction of concentration risk measurement; (4) Higher requirement on look-through rule.

Description: This article includes a description of robotic process automation as it relates to actuarial departments. Robotic process automation is becoming more prevalent in actuarial departments as different regulatory changes cause the processes to be more complex. As robotic process automation takes over more jobs, actuaries will have to enhance and evolve their skillsets to better complement the new tools. This article provides an introduction for actuaries to inform them what they should expect, and how they can adapt to these changes.

Description: Healthcare cost is increasing at 9.3% in Asia in 2017 and health insurance cost will eventually catch up, making healthcare unaffordable to aging populations. Inefficiency in healthcare system is a contributing factor. In this session, use cases on how AI is impacting the health insurance operations on 3 core challenges. Document processing: A lot of documents are generated in the healthcare ecosystem, medical reports, diagnosis, invoices etc. Currently most of the documents are still reviewed manually and rely heavily on users’ judgement. Customer engagement: Customers are generally under distress and feel rejected during the claim process. It is due to the time and process needed to get the information they look for, the gap between the sales and claims process, and the reimbursement amount. Claim settlements: Claim adjudication is a technical process that review the disease, treatment and policy coverage. The process is specific to disease and difficult to be generalized. Thus, the process is far from consistent and invites fraud, abuse and wastage in this area.

Description: In this article, we discuss the future of wearable technology in life insurance. Evidence from recent research shows that low levels of physical activity, as measured by steps per day indicate much higher mortality risk while higher levels of activity correspond with lower risk. The article shares insights of how insurers can use wearables to innovate by improving the customer journey, expanding insurability, engaging customers, promoting healthy lifestyles and improving risk assessment. Lastly, we discuss the challenges and considerations when using new data and technology to ensure success.

Description: Big data and predictive models have disrupted the life insurance new business and underwriting processes over the past few years. How did we get here? What does the future hold? This session will review the lessons learned from the evolutionary process and discuss what the potential next steps are in this journey. Are real time fully underwritten decisions an achievable goal?

Description: An overview of the basic tooling and packages available for the Julia programming language, with a focus on why this is of interest to the actuarial profession. It covers some of the built-in language features as well parts of the Julia package ecosystem that make Julia ideal for modeling and data analysis. This is the second installment in a series of article aimed at actuaries. The first installment, Julia for Actuaries, was published in the October 2020 edition of Actuarial Technology Today, and covered the base language itself, its high-level, math-friendly syntax, and why the actuary of the future should consider its adoption.

Description: This chapter focuses on creating practical models that aid in the prediction of the risk of readmission to a specific hospital within 30 days of discharge for Medicare patients, to aid in the identification and stratification of at-risk patients for hospitals considering building an intervention program in a cost-effective manner. For readers who wish to develop their own predictive model, a dataset is provided on the Actexmadriver.com website, and R code is provided in the appendix to this chapter.

Description: LDTI’s introduction has forced many insurers to examine their existing operations and technologies. They must determine how to optimize compliance efforts while balancing data, analytics and system modernization considerations to achieve maximum value. This article will examine the four key facets—the data, technology, processes, and people—essential to any successful LDTI exercise. It will also touch on the various approaches for tackling LDTI and how a modernization mindset can help insurers realize much greater transformation for the business.

Description: This article describes how to externalize code of Moody's Axis platform to Visual Studio, so that all the actuarial calculation code run through corporate DevOps pipeline. This article gives specific examples of the author has used in his job to accomplish automated model governance.