Neural calibration of hidden inhomogeneous Markov chains -- Information decompression in life insurance. (arXiv:2201.02397v1 [cs.LG])

Markov chains play a key role in a vast number of areas, including life
insurance mathematics. Standard actuarial quantities as the premium value can
be interpreted as compressed, lossy information about the underlying Markov
process. We introduce a method to reconstruct the underlying Markov chain given
collective information of a portfolio of contracts. Our neural architecture
explainably characterizes the process by explicitly providing one-step
transition probabilities. Further, we provide an intrinsic, economic model
validation to inspect the quality of the …

arxiv information insurance life markov