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This book presents the fundamentals for understanding the concept of big data, including data analysis methods, learning processes, its applications to insurance and its position within the insurance market. Topics ranging from classical data analysis methods to the impact of big data on the present and future insurance market are discussed to give an overview of big data methods applied to insurance problems. As an edited book, the reader will find chapters written by authors well-known in their fields, including data scientists, actuaries, statisticians and engineers. This book has been written for readers who want to gain a better understanding of big data and its applications within companies and organizations in the fields of banking, insurance and marketing

Quantitative finance has become these last years a extraordinary field of research and interest as well from an academic point of view as for practical applications. At the same time, pension issue is clearly a major economical and financial topic for the next decades in the context of the well-known longevity risk. Surprisingly few books are devoted to application of modern stochastic calculus to pension analysis. The aim of this book is to fill this gap and to show how recent methods of stochastic finance can be useful for to the risk management of pension funds. Methods of optimal c.

Monounireducible nonhomogeneous semi-
Markov processes are defined and investigated. The mono-
unireducible topological structure is a sufficient condition
that guarantees the absorption of the semi-Markov process
in a state of the process. This situation is of fundamental
importance in the modelling of credit rating migrations because permits the derivation of the distribution function of
the time of default. An application in credit rating modelling is given in order to illustrate the results.

We show how it is possible to construct efficient duration dependent semi-Markov
reliability models by considering recurrence time processes. We define generalized reliability indexes and we show how it is possible to compute them. Finally, we describe a possible application in the study of credit rating dynamics by considering the credit rating migration as a reliability problem.

Credit risk is one of the most important contemporary problems for banks and insurance companies. Indeed, for banks, more than forty percent of the equities are necessary to cover this risk. Though this problem is studied by large rating agencies with substantial economic, social and financial tools, building stochastic models is nevertheless necessary to complete this descriptive orientation. This book presents a complete presentation of such a category of models using homogeneous and non-homogeneous semi-Markov processes developed by the authors in several recent papers.

This book introduces ALM in the context of banks and insurance companies. Although this strategy has a core of fundamental frameworks, models may vary between banks and insurance companies because of the different risks and goals involved. The authors compare and contrast these methodologies to draw parallels between the commonalities and divergences of these two services and thereby provide a deeper understanding of ALM in general.--