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: in the insurance industry, machine learning models are increasingly used to make decisions that affect people's lives. In order to ensure that models are fair, they should be audited for bias. There are no hard and fast rules for bias audit; metrics that can be used to evaluate fairness vary depending on the context in which the model is deployed. The presenters in this session present a flexible framework that highlights key considerations in bias evaluation that can be adjusted to suit your process.

Description: In September 2017, the China Insurance Regulatory Commission (CIRC) issued the “C-ROSS Phase II project construction plan”, planned to be used across three years’ time, by perfecting the regulations, improving the operational mechanism and strengthening the regulatory cooperation.

Description: This presentation shares experience and ideas of both AIA Group and AIA China during implementation of the IFRS17 project and will discuss potential impact and outlooks in the domestic market from IFRS 17. This presentation includes a general overview of an IFRS17 implementation project, focusing on changes and requirements, as well as the resources cost of the main challenges and relative resources.

Description: The presenters will cover the variation in risk adjustment approaches used across state Medicaid programs and compare them to other Federal programs. Additionally, recent developments, such as the use of OCR to extract data from medical charts for risk adjustment, will be discussed.

Description: As the use of predictive models and novel datasets becomes more prevalent, a focus on consumer protection is being highlighted by regulators, ethicists, and industry insiders. Over time, increased rigor should and will be applied in model development and implementation. These issues are not new. Hundreds of individuals have worked on these issues in the laboratory, the board room, and the court room. The Civil Rights Act of 1964, Uniform Guidelines of the US EEOC, the Principles for the Validation and Use of Personnel Selection and other sources are intended to protect the rights of citizens and consumers and provide guidance to professionals in the development and use of decision-making tools. Drawing heavily on examples and parallels from psychology and employment practices as well as other disciplines, concepts such as model bias, fairness, adverse impact, disparate treatment and the like will be presented. Suggestions to ensure model validity, demonstrate model and data relevancy and minimize the potential for adverse impact to protected classes will also be offered. Each of these considerations will be linked to recent dialogue and concerns in the Life Insurance sector.