Description: Many insurers preparing market consistent financial statements encounter the issue of developing volatility assumptions for equity options and guarantees that are longer than any observable market data. This presentation develops a generalization of the classical Black Scholes option pricing model that is consistent with the European CRO Forum's framework for valuing non-hedgeable risk. The presentation argues that, with reasonable parameter choices, the model fits observed volatility surfaces well enough that it can be used to estimate implied volatilities where no market data exists.

Description: One important lesson learnt from the recent financial crisis was that overreliance on financial models could lead to unforeseen and harmful consequences. Model risk management (MRM) is becoming a core and mandatory component in enterprise risk management for many financial institutions, especially Fed/OCC CCAR-compliant firms. In recent years, insurance companies are also being required to have model risk management programs by Solvency II, ORSA and other supervisory guidance. MRM is not just model validation. It consists of governance and policies regarding a model's life cycle including data, model development, model test and implementation, model validation, model monitoring and documentation. It also provides guidelines and standards for risk assessment and model inventory management. The presenters will discuss current and best practice MRM, approach for model validation and auditing, as well as topics for technical issues such as types of model risks. It will also discuss the differences between Fed/OCC standards and Solvency II standards. At the conclusion of the session, attendees will be able to: Describe best practice in model risk management; Explain requirements and standards; and Develop model validation procedure.

Description: Due to the development of mobile internet, Chinese insurers now have a variety of valuable ways to collect and use customers' health data.The speaker will share his experience in heath data application in the following fields:Using data to customize health information and suggestion for customers;Using data to stimulate customers' needs for insurance products; and Using data to provide tailor-made products and services

Description: This session will cover clustering techniques generally (k-means, hierarchical), and how k-means have been used to segment policyholders using third party features such as credit scores to assess customer profitability.

Description: This session will review limited fluctuation credibility, and how to apply that approach to a GLM. Alternative credibility approaches through the lens of ASOP 25 will also be discussed.

Description: Most actuaries deal with model development at some point in their career. However, very few of us have proper training in programming, software engineering or software shop operations. Explore topics, techniques, and practices from the FinTech and IT industries that can be applied to building robust, high-quality actuarial models. This session will be of particular interest to actuaries engaged in 'in-house' model development, managers of modeling teams, and actuaries interested in software development.

Description: Claims are insurers deepest and richest transactional data – yet we rarely unleash the full potential of this data. In this session, we will discuss potential sources and attributes of claims data, traditional approaches alongside new analytic techniques and how to integrate models into existing claims management processes. During this session, the presenters will discuss different areas of how machine learning can drive significant value unleashing the potential in claims data, these include data capture, claims management and workflow design as well as behaviour prediction. In addition, the audiences will also have opportunity to learn different use cases of how claims models taking advantage of machine learning, such as foreign death fraud detection and critical illness triage.

Description: To evaluate the risk associated with personal auto coverage, insurers have traditionally relied on information about the driver (such as age, gender and marital status), location (such as territory or ZIP code), the intended use of the vehicle (such as business or pleasure) and information about the vehicle when new (such as original cost). Insurers then added detail to driver information using sophisticated credit scoring and demographic models, and added detail to vehicle use information with telematics and usage-based insurance pricing. Now, insurers are adding detail about the vehicle itself using vehicle history. The presenters will discuss how carriers use vehicle history to more accurately price and underwrite risks. They will discuss obvious data elements, such as salvage title brands, verified average annual mileage and severe damage, as well as data that may not be as obvious but has proven predictive of loss in the past. Finally, using vehicle history as an entry point for UBI programs will be covered.

Description: The class involves a combination of presentations, class participation, in-class exercises and structured hands-on work with the MA BPT in small workgroups. Prior to this course, participants are expected to spend 3 to 10 hours preparing, depending on prior experience level.

Description: The prospects for China's health insurance has increased significantly in 2018, incentivized by a series of favorable government policies to support the development of commercial health insurance. However, the market still lacks relatively mature products and services. Overall there is a common understanding in the industry that good coverage plus service is the foundation for health insurance future development, and product innovation plus care management is key for an insurance company to maintain sustainable development in the competition. In this presentation, Dr. Yang will discuss the market trend both at home and abroad with respect to health management as well as its impact on product design, pricing and cost control. With the development of internet and big data, today’s health actuary has a special role in taking advantage of the digital transformation and achieving a high-quality and efficient health care service model.