English
Related papers

Related papers: Model uncertainty in claims reserving within Tweed…

200 papers

The Tweedie generalized linear models are commonly applied in the insurance industry to analyze semicontinuous claim data. For better prediction of the aggregated claim size, the mean and dispersion of the Tweedie model are often estimated…

Methodology · Statistics 2024-05-27 Yuwen Gu

In this paper the utility optimization problem for a general insurance model is studied. The reserve process of the insurance company is described by a stochastic differential equation driven by a Brownian motion and a Poisson random…

Probability · Mathematics 2009-09-01 Yuping Liu , Jin Ma

Within the Solvency II framework the insurance industry requires a realistic modelling of the risk processes relevant for its business. Every insurance company should be capable of running a holistic risk management process to meet this…

Risk Management · Quantitative Finance 2010-09-23 Magda Schiegl

This paper focuses on modelling loss reserving to pay outstanding claims. As the amount liable on any given claim is not known until settlement, we propose a flexible model via heavy-tailed and skewed distributions to deal with outstanding…

Methodology · Statistics 2023-12-07 William L. Leão , Viviana G. R. Lobo

Tweedie exponential dispersion family constitutes a fairly rich sub-class of the celebrated exponential family. In particular, a member, compound Poisson gamma (CP-g) model has seen extensive use over the past decade for modeling mixed…

Applications · Statistics 2023-02-14 Aritra Halder , Shariq Mohammed , Kun Chen , Dipak Dey

We study a reinsurer who faces multiple sources of model uncertainty. The reinsurer offers contracts to $n$ insurers whose claims follow compound Poisson processes representing both idiosyncratic and systemic sources of loss. As the…

Risk Management · Quantitative Finance 2024-10-03 Emma Kroell , Sebastian Jaimungal , Silvana M. Pesenti

This paper focuses on the superset model problem that arises in the context of regression. To address this problem, we take the Bayesian approach to measure its uncertainty. An illustrative example with the real dataset is provided.

Methodology · Statistics 2022-09-30 Koji Miyawaki , Steven N. MacEachern

A common approach to the claims reserving problem is based on generalized linear models (GLM). Within this framework, the claims in different origin and development years are assumed to be independent variables. If this assumption is…

Applications · Statistics 2013-06-18 Šárka Hudecová , Michal Pešta

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 structural dependence coming from known relationships. In…

Risk Management · Quantitative Finance 2021-07-01 Benjamin Avanzi , Gregory Clive Taylor , Phuong Anh Vu , Bernard Wong

Traditionally, actuaries have used run-off triangles to estimate reserve ("macro" models, on agregated data). But it is possible to model payments related to individual claims. If those models provide similar estimations, we investigate…

Applications · Statistics 2016-03-01 Arthur Charpentier , Mathieu Pigeon

The Tweedie Compound Poisson-Gamma model is routinely used for modeling non-negative continuous data with a discrete probability mass at zero. Mixed models with random effects account for the covariance structure related to the grouping…

Machine Learning · Statistics 2019-02-05 Yaodong Yang , Rui Luo , Yuanyuan Liu

We revisit Schnieper's model, which decomposes incurred but not reported (IBNR) reserves into two components: reserves for newly reported claims (true IBNR) and reserves for changes over time in the estimated cost of already reported claims…

Methodology · Statistics 2026-03-13 Nicolas Baradel

We introduce an individual claims forecasting framework utilizing Bayesian mixture density networks that can be used for claims analytics tasks such as case reserving and triaging. The proposed approach enables incorporating claims…

Applications · Statistics 2020-03-06 Kevin Kuo

The Tweedie GLM is a widely used method for predicting insurance premiums. However, the structure of the logarithmic mean is restricted to a linear form in the Tweedie GLM, which can be too rigid for many applications. As a better…

Methodology · Statistics 2016-04-22 Yi Yang , Wei Qian , Hui Zou

This paper deals with the problem of model selection for a general class of integer-valued time series. We propose a penalized criterion based on the Poisson quasi-likelihood of the model. Under certain regularity conditions, the…

Statistics Theory · Mathematics 2020-02-21 Mamadou Lamine Diop , William Kengne

A non-homogeneous Poisson cluster model is studied, motivated by insurance applications. The Poisson center process which expresses arrival times of claims, triggers off cluster member processes which correspond to number or amount of…

Probability · Mathematics 2013-12-02 Muneya Matsui

Bayesian model comparison (BMC) offers a principled probabilistic approach to study and rank competing models. In standard BMC, we construct a discrete probability distribution over the set of possible models, conditional on the observed…

Machine Learning · Statistics 2023-02-22 Marvin Schmitt , Stefan T. Radev , Paul-Christian Bürkner

A procedure to include the uncertainty on the background estimate for upper limit calculations using Poissonian sampling is presented for the case where a Gaussian assumption on the uncertainty can be made. Under that hypothesis an analytic…

High Energy Physics - Experiment · Physics 2015-06-25 Luca Lista

Based on the recent paper by Delong et al. (2021), two distributions for the total claims amount (loss cost) are considered: Compound Poisson-gamma (CPG) and Tweedie. Each is used as an underlying distribution in the Bonus-Malus Scale (BMS)…

Applications · Statistics 2023-11-07 Jean-Philippe Boucher , Raïssa Coulibaly

Survival models are used in various fields, such as the development of cancer treatment protocols. Although many statistical and machine learning models have been proposed to achieve accurate survival predictions, little attention has been…

Machine Learning · Computer Science 2020-03-26 Hrushikesh Loya , Pranav Poduval , Deepak Anand , Neeraj Kumar , Amit Sethi
‹ Prev 1 2 3 10 Next ›