Description: This article summarizes key points from the recently published research paper “Deep Learning for Liability-Driven Investment,” which applies reinforcement learning and deep learning techniques to liability-driven investment (LDI).

Description: This is the strong message to encourage all actuaries in the world, who are struggling against low/zero/negative interest rate. Japanese actuaries have been struggling with low/zero/negative interest rate since 1995. There are experiences in asset management, product revision, pricing strategy, and capital management that can be applicable to other countries.

Description: A review of the Johns Hopkins Data Science Specialization courses with special emphasis on how they may be useful to actuaries.

Description: An autobiographical journey from actuarial student to data scientist.

Description: This article describes a method that can be useful when re-fitting a risk score model to a population of only moderate size. Learn how to use concepts like ridge regression to train a model with partial credibility.

Description: The predictive analytics application growth in the Asia-Pacific region has been gaining momentum.

Description: Wright State University is a public research university in Dayton, Ohio, with approximately 11,000 students. With the lowest tuition fees in Ohio, the university has an access mission and plays a critical role in the region by offering high-quality, affordable education. I joined Wright State University in fall 2019 as the director of the Actuarial Science program. In spring 2020 we attained the Universities and Colleges with Actuarial Programs (UCAP)-AC designation from the Society of Actuaries (SOA), becoming one of only three universities in southwest Ohio at this recognition tier. In this article, I would like to tell you about the journey our program has taken—its successes and its challenges. The goal is to offer a resource to other universities seeking to upgrade their Actuarial Science programs.

Description: This article will highlight new model visualization approaches we use to shed light on the “black-box” nature of advanced modeling techniques. These visualizations help us better highlight and understand the key drivers of predictions so that they can be understood and validated by all stakeholders