Innovative Semi-Markov Models for Cancer Insurance Solutions
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Chapter 1: Introduction to Our Research
I am thrilled to share that our paper titled “Semi-Markov modeling for cancer insurance” has been accepted for publication in the European Actuarial Journal. Recent advancements in medical science and biostatistics have significantly improved insurance accessibility for individuals diagnosed with cancer. This progress is exemplified by the implementation of the “right to be forgotten” in several EU nations, which allows individuals to access insurance after a waiting period of no more than 10 years following successful treatment.
Chapter 2: Focus of the Paper
This paper specifically addresses insurance products available in markets where the aforementioned right is in effect. It evaluates both stand-alone insurance options and additional guarantees included as riders in existing packages. Furthermore, we assess the implications of providing standard premium rates for all applicants in relation to mortgage insurance tied to property loans.
Section 2.1: The Semi-Markov Model Framework
The research utilizes a 3-state (healthy — ill — dead) Semi-Markov hierarchical model, initially developed by Denuit et al. (2019) for long-term care insurance, to conduct actuarial analyses. Transition intensities within the Semi-Markov framework are estimated using data from cancer cases documented by the Belgian Cancer Registry. Our findings indicate a potential market for tailored insurance solutions that cater to the specific needs of cancer survivors.
This paper is a collaborative effort with Prof. Legrand and Prof. Denuit, my PhD supervisors at UCLouvain, alongside Dr. Silversmit from the Belgian Cancer Registry.
Chapter 3: Conclusion and Future Implications
Thank you for engaging with our research. I hope this study proves beneficial for your own investigations. Should you have any questions regarding the topics discussed, please feel free to leave a comment so that others can also benefit from the conversation.
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