This bibliometric review examines the research state of artificial intelligence (AI) and
machine learning (ML) applications in the BFSI (Banking, Financial Services and Insurance) …

In this paper, we focus on numerical approximations of Piecewise Diffusion Markov
Processes (PDifMPs), particularly when the explicit flow maps are unavailable. Our …

Stochastic gradient descent is an optimisation method that combines classical gradient
descent with random subsampling within the target functional. In this work, we introduce the …

In insurance mathematics, optimal control problems over an infinite time horizon arise when
computing risk measures. An example of such a risk measure is the expected discounted …

In this paper, we consider discounted penalty functions, also called Gerber-Shiu functions, in
a Markovian shot-noise environment. At first, we exploit the underlying structure of piecewise …

Gliomas stand out as the most common and aggressive type of brain tumours, characterised
by their rapid cell growth and significant ability to penetrate surrounding brain tissue …

We discuss aspects of numerical methods for the computation of Gerber-Shiu or discounted
penalty-functions in renewal risk models. We take an analytical point of view and link this …

Gliomas stand out as the most common and aggressive type of brain tumours, characterised
by their rapid cell growth and significant ability to penetrate surrounding brain tissue …

We analyze the ruin event in a Markovian insurance risk model. For actual computations of
risk functionals, we sketch different numerical approaches and focus on assessing the …

We analyze the ruin event in a Markovian insurance risk model. For actual computations of
risk functionals, we sketch different numerical approaches and focus on assessing the …