Description: discussion of risk management and proper pricing of life insurance products.

Description: Target volatility, as an investment strategy, has been used by many funds not only as a way to smooth return but also as a way to manage risks of the VA guarantees. Contrary to existing research which favors volatility targeting over fixed allocation, this article shows that because of the existence of market jump risk, target volatility strategy does not necessarily offer an improved risk profile for VA writers. Further, target volatility coupled with leveraging can significantly increase tail risk for insurance companies.

Description: Constant Proportion Portfolio Insurance (CPPI) performance is assessed on realistic assumptions and dynamic strategies to mitigate the so-called ”gap risk”.

Description: The article talks about market consistent pricing, how risk neutral pricing and real world pricing are not fundamentally different if used appropriately. And using that knowledge, a rather new concept called the risk-adjusted real world pricing, which is a method where a mixture of risk neutral and real world pricing to achieve a holistic view on pricing, will be introduced.

Description: Recent advances in mortality modeling have enabled applicant-specific quantification of mortality risk in life insurance applicants using laboratory and physical measurements. Relative to more conventional underwriting, this approach identifies a small population of significantly under-priced policy and a much larger, cross-subsidizing group whose risk is presently overestimated. Applicants placed in the highest percentile by this scoring methodology are more than 10X as likely to die in a given period as their demographic peers, and represent approximately 5% of short-term claims. Implications for product design are substantial in both the short- and long-term, as the possibilities for adverse selection grow, and the opportunity for fully individualized pricing raises the more distant prospect of products with as many rate classes as applicants.