Mario V. Wuthrich

RiskLab, ETH Zurich

Prof. Dr.

Department of Mathematics

Ramistrasse 101

Zurich, 8092

Switzerland

  • RiskLab, ETH Zurich

SCHOLARLY PAPERS

76

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127

Scholarly Papers (76)

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1.

Non-Life Insurance: Mathematics & Statistics

Number of pages: 325 Posted: 03 Sep 2013 Last Revised: 16 Feb 2024
Mario V. Wuthrich
RiskLab, ETH Zurich
Downloads 21,210 (278)
Citation 24

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non-life insurance, general insurance, property and casualty insurance, collective risk modeling, individual claim size modeling, approximations for compound distributions, ruin theory, premium calculation principles, tariffication with GLM, credibility theory, claims reserving, solvency

2.

Data Analytics for Non-Life Insurance Pricing

Swiss Finance Institute Research Paper No. 16-68
Number of pages: 292 Posted: 17 Nov 2016 Last Revised: 19 Jun 2023
Mario V. Wuthrich and Christoph Buser
RiskLab, ETH Zurich and AXA-Winterthur
Downloads 15,631 (510)
Citation 16

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non-life insurance pricing, car insurance pricing, generalized linear models, generalized additive models, credibility theory, neural networks, regression trees, CART, bootstrap, bagging, random forest, boosting, telematic data, data science, machine learning, data analytics

3.

Case Study: French Motor Third-Party Liability Claims

Number of pages: 41 Posted: 18 Apr 2018 Last Revised: 05 Mar 2020
Alexander Noll, Robert Salzmann and Mario V. Wuthrich
PartnerRe Ltd - PartnerRe Holdings Europe Limited, SIGNAL IDUNA Reinsurance Ltd and RiskLab, ETH Zurich
Downloads 8,937 (1,333)
Citation 24

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data science, machine learning, predictive modeling, claims frequency, motor insurance, regression trees, boosting machine, neural network, generalized linear models, feature engineering, covariate selection

4.

Machine Learning in Individual Claims Reserving

Swiss Finance Institute Research Paper No. 16-67
Number of pages: 19 Posted: 11 Nov 2016 Last Revised: 29 Mar 2017
Mario V. Wuthrich
RiskLab, ETH Zurich
Downloads 3,816 (5,659)
Citation 12

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individual claims data, individual claims reserving, micro-level stochastic reserving, regression tree, machine learning

5.

Nesting Classical Actuarial Models into Neural Networks

Number of pages: 27 Posted: 25 Jan 2019
Jürg Schelldorfer and Mario V. Wuthrich
Swiss Re and RiskLab, ETH Zurich
Downloads 3,704 (5,964)
Citation 11

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regression model, generalized linear model, neural network model, embedding layer, representation learning, Poisson regression

6.

Stochastic Claims Reserving Manual: Advances in Dynamic Modeling

Swiss Finance Institute Research Paper No. 15-34
Number of pages: 322 Posted: 23 Aug 2015
Mario V. Wuthrich and Michael Merz
RiskLab, ETH Zurich and University of Hamburg
Downloads 2,882 (8,871)
Citation 18

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Claims reserving, non-life insurance run-off, chain-ladder method, Bornhuetter-Ferguson method, claims modeling, claims development result, risk margin, run-off uncertainty, conditional mean square error of prediciton

7.

Insights from Inside Neural Networks

Number of pages: 64 Posted: 19 Aug 2018 Last Revised: 24 Apr 2020
Andrea Ferrario, Alexander Noll and Mario V. Wuthrich
Dep. Management, Technology, and Economics ETH ZurichMobiliar Lab for Analytics at ETH, PartnerRe Ltd - PartnerRe Holdings Europe Limited and RiskLab, ETH Zurich
Downloads 2,593 (10,513)
Citation 10

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Neural Networks, Architecture, Over-Fitting, Loss Function, Dropout, Regularization, LASSO, Ridge, Gradient Descent, Class Imbalance, Car Insurance, Claims Frequency, Poisson Regression Model, Machine Learning, Deep Learning

8.

Claims Run-Off Uncertainty: The Full Picture

Swiss Finance Institute Research Paper No. 14-69
Number of pages: 45 Posted: 15 Nov 2014 Last Revised: 03 Jul 2015
Michael Merz and Mario V. Wuthrich
University of Hamburg and RiskLab, ETH Zurich
Downloads 2,334 (12,415)
Citation 8

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Claims reserving, chain-ladder method, gamma-gamma Bayesian chain-ladder model, conditional mean square error of prediction, claims development result, one-year uncertainty, run-off uncertainty, Mack’s formula, Merz- Wüthrich formula, risk margin, R package ChainLadder

9.

Neural Networks Applied to Chain-Ladder Reserving

Number of pages: 26 Posted: 10 May 2017 Last Revised: 19 Jul 2018
Mario V. Wuthrich
RiskLab, ETH Zurich
Downloads 2,296 (12,761)
Citation 10

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claims reserving, Mack's CL model, individual claims reserving, micro-level reserving, neural networks, individual claims features, claims covariates

10.

Lee and Carter go Machine Learning: Recurrent Neural Networks

Number of pages: 30 Posted: 23 Aug 2019 Last Revised: 29 Aug 2019
Ronald Richman and Mario V. Wuthrich
Old Mutual Insure and RiskLab, ETH Zurich
Downloads 1,926 (16,850)
Citation 20

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recurrent neural network (RNN), long short-term memory (LSTM), gated recurrent unit (GRU), Lee-Carter (LC) model, mortality forecasting, feed-forward neural network (FNN)

11.

SHAP for Actuaries: Explain any Model

Number of pages: 25 Posted: 21 Mar 2023
Michael Mayer, Daniel Meier and Mario V. Wuthrich
Schweizerische Mobiliar Versicherungsgesellschaft, Swiss Reinsurance Company and RiskLab, ETH Zurich
Downloads 1,814 (18,537)

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XAI, explainability, machine learning, SHAP, Shapley values, regression modeling, interaction, partial dependence plot, motor insurance, claims frequency

12.

On the Lifetime and One-Year Views of Reserve Risk, with Application to IFRS 17 and Solvency II Risk Margins

Number of pages: 31 Posted: 15 Mar 2018 Last Revised: 30 May 2019
Peter England, R. J. Verrall and Mario V. Wuthrich
City University London - The Business School, City University London - The Business School and RiskLab, ETH Zurich
Downloads 1,700 (20,543)
Citation 4

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Stochastic Reserving, General Insurance, Bootstrap, Chain-Ladder, Prediction Error, Mean Square Error of Prediction, Cost-of-Capital, Risk Margin, Risk Adjustment, Solvency II, IFRS 17, Value-at-Risk, Tail Value-at-Risk, One-Year View, Proportional Hazards Transform, Coherent Risk Measure

13.

A Neural Network Extension of the Lee-Carter Model to Multiple Populations

Number of pages: 21 Posted: 01 Nov 2018 Last Revised: 07 Nov 2018
Ronald Richman and Mario V. Wuthrich
Old Mutual Insure and RiskLab, ETH Zurich
Downloads 1,416 (27,002)
Citation 32

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Mortality forecasting, Lee-Carter model, Multiple Populations, Neural Networks

14.

Individual Claims Generator for Claims Reserving Studies: Data Simulation.R

UNSW Business School Research Paper Forthcoming
Number of pages: 17 Posted: 15 Jun 2022
Melantha Wang and Mario V. Wuthrich
UNSW Australia Business School, School of Risk & Actuarial Studies and RiskLab, ETH Zurich
Downloads 1,385 (27,938)

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individual claims reserving, granular claims data, individual claims generator, chain-ladder reserving method, Mack’s reserving model, non-life insurance

15.

LocalGLMnet: A Deep Learning Architecture for Actuaries

Number of pages: 35 Posted: 03 Sep 2021
Jürg Schelldorfer and Mario V. Wuthrich
Swiss Re and RiskLab, ETH Zurich
Downloads 1,318 (30,110)

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LocalGLMnet, neural network, deep learning, variable selection, interactions, explainable artificial intelligence, XAI, generalized linear model, GLM, tabular data, variable importance, Shapley additive explanation, natural language processing, NLP, text recognition, recurrent neural network, LSTM

16.

Experience Rating in Insurance

Number of pages: 175 Posted: 12 Mar 2024
Mario V. Wuthrich
RiskLab, ETH Zurich
Downloads 1,178 (35,344)

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Experience rating, posterior rating, bonus-malus systems, generalized linear models, neural networks, attention layer, Transformer, fixed effects models, random effects models, mixed effects models, panel data, cross-sectional data, credibility theory, Bayesian theory, insurance pricing, actuarial pricing

17.

Neural Network Embedding of the Over-Dispersed Poisson Reserving Model

Number of pages: 30 Posted: 14 Dec 2018
Andrea Gabrielli, Ronald Richman and Mario V. Wuthrich
ETH Zurich, Department of Mathematics, RiskLab, Students, Old Mutual Insure and RiskLab, ETH Zurich
Downloads 1,124 (37,748)
Citation 10

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cross-classified over-dispersed Poisson model, neural network, model blending, nested models, learning across portfolios, claims reserving in insurance, chain-ladder reserves, mean square error of prediction

18.

Time-Series Forecasting of Mortality Rates using Deep Learning

Number of pages: 26 Posted: 04 Jun 2020
Francesca Perla, Ronald Richman, Salvatore Scognamiglio and Mario V. Wuthrich
University of Naples Parthenope - Department of Management Studies and Quantitative Methods, Old Mutual Insure, University of Naples "Parthenope" and RiskLab, ETH Zurich
Downloads 1,052 (41,547)
Citation 16

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Mortality Forecasting, Recurrent Neural Networks, Convolutional Neural Networks, Representation Learning, Time-Series Forecasting, Lee Carter Model, Human Mortality Database

19.

Unsupervised Learning: What is a Sports Car?

Number of pages: 54 Posted: 22 Aug 2019 Last Revised: 14 Oct 2019
Simon Rentzmann and Mario V. Wuthrich
AXA Switzerland and RiskLab, ETH Zurich
Downloads 1,043 (42,121)
Citation 6

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PCA, biplot, autoencoder, bottleneck neural network (BNN), K-means clustering, K-medoids clustering, PAM algorithm, EM algorithm, clustering with Gaussian mixture models (GMMs), t-SNE, UMAP, SOM, Kohonen maps

20.

Back-Testing the Chain-Ladder Method

Number of pages: 29 Posted: 31 Jul 2018
Andrea Gabrielli and Mario V. Wuthrich
ETH Zurich, Department of Mathematics, RiskLab, Students and RiskLab, ETH Zurich
Downloads 1,032 (42,713)

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chain-ladder, individual claims history simulation machine, claims reserving, loss reserving, back-testing, portfolio size, reserve uncertainty

21.

Convolutional Neural Network Case Studies: (1) Anomalies in Mortality Rates (2) Image Recognition

Number of pages: 24 Posted: 08 Oct 2020
Daniel Meier and Mario V. Wuthrich
Swiss Reinsurance Company and RiskLab, ETH Zurich
Downloads 873 (53,979)
Citation 5

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convolutional neural network, CNN, regression, classification, mortality rates

22.

Claims Frequency Modeling Using Telematics Car Driving Data

Scandinavian Actuarial Journal, Forthcoming
Number of pages: 23 Posted: 23 Jan 2018 Last Revised: 23 Sep 2018
Guangyuan Gao, Shengwang Meng and Mario V. Wuthrich
Renmin University of China - School of Statistics, School of Statistics, Renmin University of China and RiskLab, ETH Zurich
Downloads 791 (61,758)
Citation 6

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Telematics Data, K-Means Algorithm, Principal Components Analysis, Bottleneck Neural Network, Generalized Additive Model, v-a Heatmap, Pattern Recognition, Kullback-Leibler Divergence, Claims Frequency Modeling, Car Insurance Pricing

23.

Covariate Selection from Telematics Car Driving Data

Number of pages: 18 Posted: 19 Dec 2016
Mario V. Wuthrich
RiskLab, ETH Zurich
Downloads 737 (67,632)
Citation 2

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telematics data, driving habits, driving styles, regression, categorical classes, pattern recognition, clustering, K-means clustering, unsupervised learning, machine learning

24.

Gini Index and Friends

Number of pages: 35 Posted: 19 Oct 2022
Christian Lorentzen, Michael Mayer and Mario V. Wuthrich
Schweizerische Mobiliar Versicherungsgesellschaft, Schweizerische Mobiliar Versicherungsgesellschaft and RiskLab, ETH Zurich
Downloads 709 (71,112)

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Gini index, Gini score, Gini coefficient, accuracy ratio, consistency, consistent scoring, auto-calibration, Lorenz curve, concentration curve, cumulative accuracy profile, CAP, receiver operating characteristics curve, ROC curve, area under the curve, AUC, model selection, binary classification

25.

Feature Extraction from Telematics Car Driving Heatmaps

Number of pages: 16 Posted: 16 Nov 2017
Guangyuan Gao and Mario V. Wuthrich
Renmin University of China - School of Statistics and RiskLab, ETH Zurich
Downloads 639 (81,097)
Citation 9

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Telematics car driving data, driving styles, unsupervised learning, pattern recognition, image recognition, bottleneck neural network, singular value decomposition, principal component analysis, Kullback-Leibler divergence

26.

Machine Learning Techniques for Mortality Modeling

Number of pages: 16 Posted: 23 Feb 2017
Philippe Deprez, Pavel V. Shevchenko and Mario V. Wuthrich
ETH Zürich - Department of Mathematics, Macquarie University - Department of Actuarial Studies and Business Analytics and RiskLab, ETH Zurich
Downloads 616 (85,244)
Citation 6

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mortality modeling, cause-of-death mortality, machine learning, boosting, regression

27.

Statistical Review of Nuclear Power Accidents

Number of pages: 13 Posted: 06 Sep 2011 Last Revised: 04 Jul 2012
Marius Hofert and Mario V. Wuthrich
The University of Hong Kong and RiskLab, ETH Zurich
Downloads 616 (84,902)
Citation 8

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nuclear safety, nuclear power accidents, risk managment, Fukushima, extremes, extreme value theory, Pareto distribution, Hill plot, peaks-over-threshold

28.

Believing the Bot - Model Risk in the Era of Deep Learning

Number of pages: 40 Posted: 05 Sep 2019
Ronald Richman, Nicolai von Rummell and Mario V. Wuthrich
Old Mutual Insure, QED Actuaries and Consultants and RiskLab, ETH Zurich
Downloads 608 (86,287)
Citation 13

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Deep learning, Model Risk, Pricing, Mortality Forecasting, Insurance Modelling

29.

Market Consistent Pricing of Insurance Products

Number of pages: 32 Posted: 15 Mar 2007
Semyon Malamud, Eugene Trubowitz and Mario V. Wuthrich
Ecole Polytechnique Federale de Lausanne, Swiss Federal Institute of Technology Zurich and RiskLab, ETH Zurich
Downloads 554 (97,125)
Citation 14

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insurance, hedging, incomplete markets, utility indifference, market consistent

30.

Smoothness and Monotonicity Constraints for Neural Networks Using ICEnet

Number of pages: 33 Posted: 21 May 2023
Ronald Richman and Mario V. Wuthrich
Old Mutual Insure and RiskLab, ETH Zurich
Downloads 470 (118,635)
Citation 2

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Smoothing, Whittaker–Henderson Smoothing, Graduation, Monotonicity, Deep Neural Networks, Constrained Likelihood, Individual Conditional Expectation

31.

Paid-Incurred Chain Reserving Method with Dependence Modeling

Number of pages: 20 Posted: 22 Aug 2011
Sebastian Happ and Mario V. Wuthrich
University of Hamburg and RiskLab, ETH Zurich
Downloads 462 (121,390)
Citation 3

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claims reserving, outstanding loss liabilities, ultimate loss prediction, claims payments, claims incurred, incurred losses, prediction uncertainty, paid-incurred chain model, PIC reserving method, general insurance, non-life insurance

32.

Reflections on deep learning and the actuarial profession(al)

Number of pages: 28 Posted: 17 Jan 2024
Roseanne Harris, Ronald Richman and Mario V. Wuthrich
University of Witwatersrand, Johannesburg, South Africa, Old Mutual Insure and RiskLab, ETH Zurich
Downloads 435 (129,960)

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33.

What is fair? Proxy discrimination vs. demographic disparities in insurance pricing

Number of pages: 37 Posted: 14 May 2023 Last Revised: 05 Jul 2024
Mathias Lindholm, Ronald Richman, Andreas Tsanakas and Mario V. Wuthrich
Stockholm University, Old Mutual Insure, Bayes Business School (formerly Cass), City, University of London and RiskLab, ETH Zurich
Downloads 428 (132,428)
Citation 4

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discrimination, indirect discrimination, proxy discrimination, fairness, protected attributes, discrimination-free, unawareness, group fairness, demographic parity, statistical parity, independence axiom, equalized odds, separation axiom, predictive parity, sufficiency axiom, input pre-process

34.

LASSO Regularization within the LocalGLMnet Architecture

Number of pages: 29 Posted: 24 Sep 2021 Last Revised: 01 Jun 2022
Ronald Richman and Mario V. Wuthrich
Old Mutual Insure and RiskLab, ETH Zurich
Downloads 401 (142,785)
Citation 3

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Deep learning, neural networks, LocalGLMnet, regression model, variable selection, regularization, LASSO, group LASSO, ridge regularization, Tikhonov regularization.

35.

Bias Regularization in Neural Network Models for General Insurance Pricing

Number of pages: 23 Posted: 28 Mar 2019
Mario V. Wuthrich
RiskLab, ETH Zurich
Downloads 390 (147,330)
Citation 7

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generalized linear model; exponential dispersion family; neural network; gradient descent method; unbiasedness; regression tree

36.

A Discussion of Discrimination and Fairness in Insurance Pricing

Number of pages: 14 Posted: 18 Sep 2022
Mathias Lindholm, Ronald Richman, Andreas Tsanakas and Mario V. Wuthrich
Stockholm University, Old Mutual Insure, Bayes Business School (formerly Cass), City, University of London and RiskLab, ETH Zurich
Downloads 382 (150,727)

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discrimination, indirect discrimination, proxy discrimination, fairness, protected information, discrimination-free, unawareness, group fairness, statistical parity, independence axiom, equalized odds, separation axiom, predictive parity, sufficiency axiom

37.

A Multi-Task Network Approach for Calculating Discrimination-Free Insurance Prices

Number of pages: 33 Posted: 19 Jul 2022 Last Revised: 02 Nov 2022
Mathias Lindholm, Ronald Richman, Andreas Tsanakas and Mario V. Wuthrich
Stockholm University, Old Mutual Insure, Bayes Business School (formerly Cass), City, University of London and RiskLab, ETH Zurich
Downloads 364 (159,104)
Citation 7

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indirect discrimination, proxy discrimination, discrimination-free insurance pricing, unawareness price, best-estimate price, protected information, discriminatory covariates, fairness, incomplete information, multi-task learning, multioutput network

38.

Accurate and Explainable Mortality Forecasting with the LocalGLMnet

Number of pages: 27 Posted: 10 Mar 2023
Francesca Perla, Ronald Richman, Salvatore Scognamiglio and Mario V. Wuthrich
University of Naples Parthenope - Department of Management Studies and Quantitative Methods, Old Mutual Insure, University of Naples "Parthenope" and RiskLab, ETH Zurich
Downloads 345 (168,590)

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Mortality forecasting, explainable deep learning, neural networks, Lee–Carter model, multi-population mortality model, Human Mortality Database, LocalGLMnet

39.

Full Bayesian Analysis of Claims Reserving Uncertainty

Number of pages: 20 Posted: 24 May 2016
Gareth Peters, Rodrigo Targino and Mario V. Wuthrich
University of California Santa Barbara, Getulio Vargas Foundation (FGV) - EMAp - School of Applied Mathematics and RiskLab, ETH Zurich
Downloads 321 (182,142)
Citation 1

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Chain-Ladder Method, Claims Reserving Uncertainty, Claims Development Result, Mack's Formula, Merz-WüThrich's Formula, Conditional Mean Square Error of Prediction, Runoff Uncertainty, Full Bayesian Chain-Ladder Model

40.

Convolutional Neural Network Classification of Telematics Car Driving Data

Number of pages: 18 Posted: 01 Nov 2018
Guangyuan Gao and Mario V. Wuthrich
Renmin University of China - School of Statistics and RiskLab, ETH Zurich
Downloads 308 (190,264)
Citation 1

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telematics car driving data, driving styles, pattern recognition, image recognition, convolutional neural networks

41.

The Structural Modelling of Operational Risk Via Bayesian Inference: Combining Loss Data with Expert Opinions

The Journal of Operational Risk 1(3), pp. 3-26, 2006
Number of pages: 26 Posted: 24 Nov 2014
Pavel V. Shevchenko and Mario V. Wuthrich
Macquarie University - Department of Actuarial Studies and Business Analytics and RiskLab, ETH Zurich
Downloads 297 (197,636)
Citation 6

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operational risk, loss distribution approach, Bayesian inference, Basel II Advanced Measurement Approaches, compound process, quantitative risk management

42.

Gamma Mixture Density Networks and their application to modelling insurance claim amounts

Number of pages: 38 Posted: 23 Nov 2020 Last Revised: 14 Apr 2021
Lukasz Delong, Mathias Lindholm and Mario V. Wuthrich
University of Warsaw, Faculty of Economic Sciences, Stockholm University and RiskLab, ETH Zurich
Downloads 294 (199,822)
Citation 2

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Expectation-Maximization, neural networks, boosting, mixtures of distributions

43.

The Quantification of Operational Risk Using Internal Data, Relevant External Data and Expert Opinion

The Journal of Operational Risk 2(3), pp.3-27, 2007.
Number of pages: 30 Posted: 24 Nov 2014
Dominik Lambrigger, Pavel V. Shevchenko and Mario V. Wuthrich
ETH Zürich, Macquarie University - Department of Actuarial Studies and Business Analytics and RiskLab, ETH Zurich
Downloads 288 (204,174)
Citation 1

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Operational Risk, Basel II, Loss Distribution Approach, Bayesian inference, Advanced Measurement Approach, Quantitative Risk Management, generalized inverse Gaussian distribution

44.

Bayesian Modelling, Monte Carlo Sampling and Capital Allocation of Insurance Risks

Number of pages: 53 Posted: 03 May 2017
Gareth Peters, Rodrigo Targino and Mario V. Wuthrich
University of California Santa Barbara, Getulio Vargas Foundation (FGV) - EMAp - School of Applied Mathematics and RiskLab, ETH Zurich
Downloads 287 (204,873)
Citation 2

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Capital Allocation, Premium and Reserve Risk, Solvency Capital Requirement (SCR), Sequential Monte Carlo (SMC), Swiss Solvency Test (SST)

45.

Market Value Margin via Mean-Variance Hedging

The final version of this article has appeared as: Tsanakas A., Wüthrich, M., Cerny, A. (2013), 'Market value margin via mean-variance hedging', ASTIN Bulletin, 43(3), p.301-322.
Number of pages: 21 Posted: 20 Sep 2012 Last Revised: 03 Jan 2014
Andreas Tsanakas, Mario V. Wuthrich and Aleš Černý
Bayes Business School (formerly Cass), City, University of London, RiskLab, ETH Zurich and Bayes Business School, City, University of London
Downloads 264 (223,042)
Citation 5

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Cost-of-capital, market consistent valuation, market value margin, mean-variance hedging, Solvency II

46.

Best-Estimate Claims Reserves in Incomplete Markets

Swiss Finance Institute Research Paper No. 14-64
Number of pages: 21 Posted: 17 Aug 2014 Last Revised: 12 Nov 2014
Sebastian Happ, Michael Merz and Mario V. Wuthrich
University of Hamburg, University of Hamburg and RiskLab, ETH Zurich
Downloads 258 (228,250)
Citation 3

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best-estimate reserves, dynamic hedging, sequential local risk minimization, state-price deflator, incomplete market, technical provisions, risk margin

47.

Conditional Expectation Network for SHAP

Number of pages: 24 Posted: 25 Jul 2023
Ronald Richman and Mario V. Wuthrich
Old Mutual Insure and RiskLab, ETH Zurich
Downloads 234 (251,069)
Citation 1

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Shapley value, SHAP, conditional SHAP, unconditional SHAP, interventional SHAP, anova, drop1, analysis-of-deviance, least squares Monte Carlo, partial dependence plot, PDP, explainability, XAI

48.

Isotonic regression for variance estimation and its role in mean estimation and model validation

Downloads 202 (257,494)
Citation 2

Isotonic regression for variance estimation and its role in mean estimation and model validation

Number of pages: 37 Posted: 19 Jun 2023 Last Revised: 13 Jan 2024
Lukasz Delong and Mario V. Wuthrich
University of Warsaw, Faculty of Economic Sciences and RiskLab, ETH Zurich
Downloads 202 (287,338)
Citation 2

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Isotonic regression, generalized linear model, quasi-likelihood, lognormal model, T-reliability diagram

49.

Consistent Re-Calibration in Yield Curve Modeling: An Example

Swiss Finance Institute Research Paper No. 15-26
Number of pages: 22 Posted: 14 Jul 2015
Mario V. Wuthrich
RiskLab, ETH Zurich
Downloads 206 (283,081)

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yield curve modeling, term structure model, affine term structure model, interest rate model, spot rate model, Vasicek model, Hull-White extension, Heath-Jarrow-Morton framework, HJM, calibration, consistent re-calibration, CRC.

50.

Capital Allocation for Portfolios with Non-Linear Risk Aggregation

Insurance: Mathematics and Economics, Forthcoming
Number of pages: 32 Posted: 21 May 2016 Last Revised: 16 Nov 2016
Tim J. Boonen, Andreas Tsanakas and Mario V. Wuthrich
University of Hong Kong, Bayes Business School (formerly Cass), City, University of London and RiskLab, ETH Zurich
Downloads 199 (292,099)
Citation 3

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Capital allocation, Euler rule, fuzzy core, Aumann-Shapley value, risk measures

51.

Dynamic Operational Risk: Modeling Dependence and Combining Different Sources of Information

The Journal of Operational Risk 4(2), pp. 69-104, 2009
Number of pages: 47 Posted: 23 Nov 2014
Gareth Peters, Pavel V. Shevchenko and Mario V. Wuthrich
University of California Santa Barbara, Macquarie University - Department of Actuarial Studies and Business Analytics and RiskLab, ETH Zurich
Downloads 191 (303,233)

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dependence modelling, copula, compound process, operational risk, Bayesian inference, Markov chain Monte Carlo, Slice sampling.

52.

Driving Risk Evaluation Based on Telematics Data

Number of pages: 20 Posted: 13 Dec 2018
Guangyuan Gao, Mario V. Wuthrich and Hanfang Yang
Renmin University of China - School of Statistics, RiskLab, ETH Zurich and Renmin University of China - School of Statistics
Downloads 167 (341,628)

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Telematics data; Driving habit; Driving style; v-a heatmap; Acceleration pattern; K-mediods algorithm; Principal components analysis; Generalized additive model; Generalized linear model; Variable selection; Collinearity; Poisson regression; Deviance statistics; Claims frequency modeling; Car

53.

Chain Ladder Method: Bayesian Bootstrap Versus Classical Bootstrap

Number of pages: 37 Posted: 05 Jun 2017
Gareth Peters, Mario V. Wuthrich and Pavel V. Shevchenko
University of California Santa Barbara, RiskLab, ETH Zurich and Macquarie University - Department of Actuarial Studies and Business Analytics
Downloads 160 (354,292)
Citation 1

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claims reserving, distribution-free chain ladder, mean square error of prediction, Bayesian chain ladder, approximate Bayesian computation, Markov chain Monte Carlo, adaption, annealing, bootstrap

54.

Sequential Monte Carlo Sampling for State Space Models

Number of pages: 24 Posted: 25 Apr 2016
Mario V. Wuthrich
RiskLab, ETH Zurich
Downloads 134 (408,620)

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State space models, sequential Monte Carlo sampling, SMC, Kalman filter

55.

A 'Toy' Model for Operational Risk Quantification Using Credibility Theory

The Journal of Operational Risk 2(1), pp. 3-19, 2007
Number of pages: 18 Posted: 24 Nov 2014
Hans BuŸhlmann, Pavel V. Shevchenko and Mario V. Wuthrich
ETH Zurich - Department of Mathmatics, Macquarie University - Department of Actuarial Studies and Business Analytics and RiskLab, ETH Zurich
Downloads 123 (436,374)

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quantitative risk management, operational risk, loss distribution approach, credibility theory, combining different data sources, Basel II Advanced Measurement Approaches

56.

The Balance Property in Insurance Pricing

Number of pages: 38 Posted: 16 Sep 2024
Mathias Lindholm and Mario V. Wuthrich
Stockholm University and RiskLab, ETH Zurich
Downloads 37 (836,447)

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Unbiasedness, auto-calibration, balance property, actuarial pricing, regression, generalized linear model, GLM, neural network, maximum likelihood estimation, MLE

57.

Sensitivity-Based Measures of Discrimination in Insurance Pricing

Number of pages: 30 Posted: 19 Aug 2024
Mathias Lindholm, Ronald Richman, Andreas Tsanakas and Mario V. Wuthrich
Stockholm University, Old Mutual Insure, Bayes Business School (formerly Cass), City, University of London and RiskLab, ETH Zurich
Downloads 23 (953,264)

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Proxy discrimination, demographic parity, global sensitivity analysis, insurance pricing, algorithmic fairness

58.

High-Cardinality Categorical Covariates in Network Regressions

Japenese Journal of Statistics and Data Science. Open Access: https://link.springer.com/article/10.1007/s42081-024-00243-4
Posted: 24 Aug 2023 Last Revised: 13 Mar 2024
Ronald Richman and Mario V. Wuthrich
Old Mutual Insure and RiskLab, ETH Zurich

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categorical covariates, categorical features, nominal features, high-cardinality features, entity embedding, embedding layer, random effects model, neural network, re- current neural network, attention layer, transformer, regularization, ridge regularization, variational inference

59.

LocalGLMnet: interpretable deep learning for tabular data

Scandinavian Actuarial Journal 2022 https://www.tandfonline.com/doi/full/10.1080/03461238.2022.2081816
Posted: 26 Jul 2021 Last Revised: 09 Jun 2022
Ronald Richman and Mario V. Wuthrich
Old Mutual Insure and RiskLab, ETH Zurich

Abstract:

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deep learning, neural networks, generalized linear model, regression model, variable selection, explainable deep learning, attention layer, tabular data, exponential dispersion family, Shapley values, SHapley Additive exPlanations (SHAP), integrated gradients

60.

Deep Learning under Model Uncertainty

Posted: 08 Jul 2021 Last Revised: 01 Feb 2022
Michael Merz and Mario V. Wuthrich
University of Hamburg and RiskLab, ETH Zurich

Abstract:

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deep learning, neural network, representation learning, model uncertainty, exponential dispersion family, Tweedie's family, generalized linear model, regression

61.

Statistical Foundations of Actuarial Learning and its Applications

Springer Actuarial, Open Access, https://link.springer.com/book/10.1007/978-3-031-12409-9
Posted: 21 Apr 2021 Last Revised: 28 Nov 2022
Mario V. Wuthrich and Michael Merz
RiskLab, ETH Zurich and University of Hamburg

Abstract:

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Insurance modeling, actuarial modeling, statistical modeling, regression, generalized linear models, neural networks, mixture models, expectation-maximization algorithm, maximum likelihood estimation, regularization, forecast dominance, scoring

62.

Interpreting Deep Learning Models with Marginal Attribution by Conditioning on Quantiles

Data Mining and Knowledge Discovery (2022) https://link.springer.com/article/10.1007/s10618-022-00841-4
Posted: 22 Mar 2021 Last Revised: 22 Jun 2022
Michael Merz, Ronald Richman, Andreas Tsanakas and Mario V. Wuthrich
University of Hamburg, Old Mutual Insure, Bayes Business School (formerly Cass), City, University of London and RiskLab, ETH Zurich

Abstract:

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explainable AI (XAI), model-agnostic tools, deep learning, attribution, accumulated local e ects (ALE), partial dependence plot (PDP), locally interpretable model-agnostic explanation (LIME), variable importance, post-hoc analysis

63.

Nagging Predictors

Risks 2020, 8(3), 83; https://doi.org/10.3390/risks8030083
Posted: 16 Jul 2020 Last Revised: 22 Mar 2021
Ronald Richman and Mario V. Wuthrich
Old Mutual Insure and RiskLab, ETH Zurich

Abstract:

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bagging, neural networks, network aggregation, insurance pricing, regression modeling

64.

Making Tweedie's Compound Poisson Model More Accessible

Eur. Actuar. J. (2021). https://doi.org/10.1007/s13385-021-00264-3
Posted: 01 Jul 2020 Last Revised: 17 Feb 2021
Lukasz Delong, Mathias Lindholm and Mario V. Wuthrich
University of Warsaw, Faculty of Economic Sciences, Stockholm University and RiskLab, ETH Zurich

Abstract:

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compound Poisson model, gamma claim sizes, Tweedie's distribution, exponential dispersion family, generalized linear models, neural network

65.

Boosting Poisson Regression Models with Telematics Car Driving Data

Mach Learn (2021). https://doi.org/10.1007/s10994-021-05957-0
Posted: 04 Jun 2020 Last Revised: 22 Mar 2021
Guangyuan Gao, He Wang and Mario V. Wuthrich
Renmin University of China - School of Statistics, affiliation not provided to SSRN and RiskLab, ETH Zurich

Abstract:

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Densely connected neural network, Convolutional neural network, Combined actuarial neural network, Claims frequency modeling, Telematics car driving data, Poisson regression, Generalized linear model, Regression tree, Telematics heatmap

66.

Collective Reserving using Individual Claims Data

Scandinavian Actuarial Journal 2021 https://www.tandfonline.com/doi/full/10.1080/03461238.2021.1921836
Posted: 19 May 2020 Last Revised: 11 May 2021
Lukasz Delong, Mathias Lindholm and Mario V. Wuthrich
University of Warsaw, Faculty of Economic Sciences, Stockholm University and RiskLab, ETH Zurich

Abstract:

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claims reserving, general insurance, individual claims data, micro-level reserving, neural networks, IBNR claims, RBNS claims, chain-ladder method, over-dispersed Poisson model

67.

Neural Networks for the Joint Development of Individual Payments and Claim Incurred

Risks 2020, 8(2), https://doi.org/10.3390/risks8020033
Posted: 10 Apr 2020 Last Revised: 26 Feb 2021
Lukasz Delong and Mario V. Wuthrich
University of Warsaw, Faculty of Economic Sciences and RiskLab, ETH Zurich

Abstract:

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Neural networks, individual claims, Reported But Not Settled claims, claims simulations

68.

Discrimination-Free Insurance Pricing

ASTIN Bulletin open access FirstView 2021 https://www.cambridge.org/core/journals/astin-bulletin-journal-of-the-iaa/article/discriminationfree-insurance-pricing/ED25C4053690E56050F437B8DF2AD117
Posted: 10 Feb 2020 Last Revised: 11 Oct 2021
Mathias Lindholm, Ronald Richman, Andreas Tsanakas and Mario V. Wuthrich
Stockholm University, Old Mutual Insure, Bayes Business School (formerly Cass), City, University of London and RiskLab, ETH Zurich

Abstract:

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discrimination, differentiation, insurance pricing, individual policy char- acteristics, discriminatory covariates, direct discrimination, indirect discrimination, neural networks, complex algorithmic models, causal inference, confounding

69.

Assessing Asset-Liability Risk With Neural Networks

Risks 2020, 8, 16.
Posted: 13 Jan 2020 Last Revised: 10 Feb 2020
Patrick Cheridito, John Ery and Mario V. Wuthrich
ETH Zurich, ETH Zürich and RiskLab, ETH Zurich

Abstract:

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Asset-asset liability risk, risk capital, solvency calculation, value-at-risk, expected shortfall, neural networks, importance sampling

70.

From Generalized Linear Models to Neural Networks, and Back

This paper has been integrated into SSRN Manuscript 3822407
Posted: 09 Dec 2019 Last Revised: 24 Nov 2021
Mario V. Wuthrich
RiskLab, ETH Zurich

Abstract:

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generalized linear model, GLM, neural network, regression modeling, exponential dispersion family, deviance loss, balance property, canonical link, representation learning, regularization, LASSO, claims frequency modeling

71.

Individual Claims History Simulation Machine

Risks 2018 https://www.mdpi.com/2227-9091/6/2/29
Posted: 06 Mar 2018 Last Revised: 09 Jun 2022
Andrea Gabrielli and Mario V. Wuthrich
ETH Zurich, Department of Mathematics, RiskLab, Students and RiskLab, ETH Zurich

Abstract:

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claims reserving, individual claims, claims cash flows, micro-level stochastic reserving, loss reserving, claims simulation, neural network reserving, individual claims features, individual claims covariates, chain-ladder

72.

Model Uncertainty in Claims Reserving within Tweedie's Compound Poisson Models

ASTIN Bulletin 39(1), pp.1-33, 2009
Posted: 23 Nov 2014
Gareth Peters, Pavel V. Shevchenko and Mario V. Wuthrich
University of California Santa Barbara, Macquarie University - Department of Actuarial Studies and Business Analytics and RiskLab, ETH Zurich

Abstract:

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Claims reserving, model uncertainty, Tweedie's compound Poisson model, Bayesian analysis, model selection, model averaging, Markov chain Monte Carlo

73.

Modified Munich Chain-Ladder Method

Risks 2015 https://www.mdpi.com/2227-9091/3/4/624, Swiss Finance Institute Research Paper No. 14-65
Posted: 30 Aug 2014 Last Revised: 09 Jun 2022
Michael Merz and Mario V. Wuthrich
University of Hamburg and RiskLab, ETH Zurich

Abstract:

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Munich chain-ladder method, claims reserving, prediction uncertainty, mean square error of prediction, multivariate Gaussian model, claims paid and claims incurred

74.

Dependence Modeling in Multivariate Claims Run-Off Triangles

Annals of Actuarial Science, Forthcoming
Posted: 22 Dec 2011 Last Revised: 05 Jul 2012
Michael Merz, Mario V. Wuthrich and Enkelejd Hashorva
University of Hamburg, RiskLab, ETH Zurich and University of Lausanne, Actuarial Department

Abstract:

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general insurance, non-life insurance, claims reserving, aggregation of run-off portfolios, claims inflation, outstanding loss liabilities

75.

Claims Development Result in the Paid-Incurred Chain Reserving Method

Insurance: Mathematics and Economics, Forthcoming
Posted: 17 Aug 2011 Last Revised: 04 Jul 2012
Sebastian Happ, Michael Merz and Mario V. Wuthrich
University of Hamburg, University of Hamburg and RiskLab, ETH Zurich

Abstract:

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stochastic claims reserving, PIC method, outstanding loss liabilities, claims payments, incurred losses, prediction uncertainty, conditional mean square error, claims development result, solvency

76.

Risk Margin for a Non-Life Insurance Run-Off

The final version of this article has appeared as: Wuethrich M. V., Embrechts, P., Tsanakas, A. (2011), 'Risk margin for a non-life insurance run-off', Statistics & Risk Modeling, 28, p. 299-317.
Posted: 15 Aug 2011 Last Revised: 03 Jan 2014
Mario V. Wuthrich, Paul Embrechts and Andreas Tsanakas
RiskLab, ETH Zurich, Swiss Federal Institute of Technology Zurich and Bayes Business School (formerly Cass), City, University of London

Abstract:

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claims reserving, best-estimate reserves, run-off risks, risk margin, market value margin, one-year uncertainty, claims development result, market-consistent valuation