22 citations · 144 across the 21 of their papers we have counts for
7 papers · 1 filter
Reinforcement Learning for Micro-Level Claims Reserving
Benjamin Avanzi, Ronald Richman, Bernard Wong +2
Outstanding claim liabilities are revised repeatedly as claims develop, yet most modern reserving models are trained as one-shot predictors and typically learn only from settled cl…
SynthETIC: an individual insurance claim simulator with feature control
Benjamin Avanzi, Gregory Clive Taylor, Melantha Wang +1
Recent years have seen rapid increase in the application of machine learning to insurance loss reserving. They yield most value when applied to large data sets, such as individual…
On the optimality of joint periodic and extraordinary dividend strategies
Benjamin Avanzi, Hayden Lau, Bernard Wong
In this paper, we model the cash surplus (or equity) of a risky business with a Brownian motion. Owners can take cash out of the surplus in the form of "dividends", subject to tran…
On unbalanced data and common shock models in stochastic loss reserving
Benjamin Avanzi, Gregory Clive Taylor, Phuong Anh Vu +1
Introducing common shocks is a popular dependence modelling approach, with some recent applications in loss reserving. The main advantage of this approach is the ability to capture…
A multivariate evolutionary generalised linear model framework with adaptive estimation for claims reserving
Benjamin Avanzi, Gregory Clive Taylor, Phuong Anh Vu +1
In this paper, we develop a multivariate evolutionary generalised linear model (GLM) framework for claims reserving, which allows for dynamic features of claims activity in conjunc…
On the modelling of multivariate counts with Cox processes and dependent shot noise intensities
Benjamin Avanzi, Gregory Clive Taylor, Bernard Wong +1
In this paper, we develop a method to model and estimate several, _dependent_ count processes, using granular data. Specifically, we develop a multivariate Cox process with shot no…
Modelling and understanding count processes through a Markov-modulated non-homogeneous Poisson process framework
Benjamin Avanzi, Greg Taylor, Bernard Wong +1
The Markov-modulated Poisson process is utilised for count modelling in a variety of areas such as queueing, reliability, network and insurance claims analysis. In this paper, we e…