Description: Since the international financial crisis, accounting standards have become an important part of financial supervision rules, which objectively requires us to study the reform and development of accounting standards from the perspective of financial stability. Since the release of IFRS17 in 2017, the research and discussion of IFRS17 in the insurance industry has focused on technical details and implementation, while the economic impact and pros and cons analysis of IFRS17 are few. As a result, the industry's understanding of IFRS17 is not comprehensive enough, and there are still many disputes, and no industry consensus has been formed. In the future, the insurance industry should strengthen the research and analysis of IFRS17 from the perspective of financial stability, deepen the understanding and cognition of IFRS17, and improve the ability to control and use IFRS17.

Description: Maintaining solid financial performance is a KPI for senior management. With the advancement of technology, the management can leverage new techniques to improve their decision making and focus on higher value activities in a timely manner. This presentation sets out the use of 1. correlation analysis to draw relationship between financial metrics and 2. smart analytics techniques, including text mining and analytics, to identify trends and drivers that impact the valuation of a company. We will also assess how the results of a comprehensive financial analysis could influence risk management considerations, including business steering and risk strategy.

Description: Predictive modeling continues to gain traction in the life insurance industry with the rapid growth of available data and maturity of open source tools. New methods and technology in predictive analytics have enabled the evaluation of extremely large data more quickly and allow us to incorporate features previously not considered. The presenters will provide background on predictive modeling tools and algorithms utilized by actuaries and data scientists for life insurance, highlighting applications from marketing to underwriting.

Description: The presenters will discuss predictive analytics as applied to recent group life and disability experience studies and other applications.

Description: The management of the investments of an insurance enterprise has undergone a considerable evolution since the pioneering work of Redington in the mid 20th century. Best practices have evolved to incorporate ever more complex insurance liabilities, expanding investment asset classes and global market opportunities. Strategic asset allocation (SAA), liability driven investing, and other robust optimization approaches form the core of the professional management of insurance company investments.

Description: Institutional investors such as pension plans and insurance companies have enjoyed strong equity returns for a length of time with few historical precedents. Nearly a decade after the end of the financial crisis, strategies to provide downside protection remain expensive and the performance of traditional risk-managed funds has disappointed investors.

Description: In this session, we will discuss the advantages of using stochastic simulation of decrements in actuarial projections. We will also discuss practical approaches for parameterizing assumption probability distributions for simulation using predictive models as well as challenges the practitioner may face in implementation.

Description: Neural Networks are no longer limited to classification and regression solutions to numeric problems. CNNs add the ability to classify images, and GANs can create new images. Learn how these capabilities can provide competitive advantages to early adopters, how they work, and how to implement them.

Description: LON-CAPA is a full-featured course management, learning content management, and assessment system. It was initially developed by Michigan State University under several National Science Foundation grants. You can run LON-CAPA for free on your own dedicated server. Purdue University has used LON-CAPA to create a robust online homework system for the Financial Mathematics material of the FM Exam. This homework system is in the public domain and may be used by any university running LON-CAPA. This session will provide additional information and include a demonstration of the system.

Description: The interactive visuals provided a compelling demonstration for Allstate's leadership team to see the effects of changes to Allstate's risk profile.