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: Certain valuation assumptions are difficult to set with a high degree of accuracy, whether because the underlying experience is in different economic or interest rate environments, in addition to other reasons. Examples include assumptions for long-term care insurance, annuity options, lapsation and premium persistency on ULSG. This session will share how the actuary can use predictive analytics to augment the assumption-setting process. Some of the benefits to the actuary (along with the company and the regulator) include more accurate assumptions with lower margins for adverse deviations. Of possible interest as well is that applications go beyond valuation and include acquisitions, reinsurance and pricing.

Description: Exploring how artificial intelligence can enable insurance to expand into new places with new insights.

Description: 1999 SOA Regional Meeting, Atlanta. In this session on data and interoperability standards for actuaries, the panel discusses the importance of open data standards which enable communication and transmission of data between different systems developed by different vendors. They also discuss the attached white paper entitled 'Proposed Data Standards for Table Data in the Insurance and Pension Industries' which was written by the Computer Science Section of the SOA to encourage adoption of the described standard.

Description: 1999 SOA Annual Meeting, San Francisco. Presenters discussed ways in which nontraditional methods of distributing insurance products are continuing to evolve and offered their views on where that evolution may lead for the industry.

Description: This article explores the disruptive applications of blockchain, an emerging technology, and its impact on the pharmacy benefit space, and pharmacy benefit managers (PBM).

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: 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: Companies with the intention of being the top, trusted source(s) in an information overloaded world.

Description: Support systems and new solutions to enable caregivers to deliver better care and reduce personal stress.