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Multivariate Modelling of Motor Third Party Liability Insurance Claims

Author

Listed:
  • Aivars Spilbergs

    (BA School of Business and Finance, Riga, Latvia)

  • Andris Fomins

    (BA School of Business and Finance, Riga, Latvia)

  • Māris Krastiņš

    (BA School of Business and Finance, Riga, Latvia)

Abstract

The aim of the study is to identity the main factors that affect claims amount paid by insurers in case of road accidents and to predict losses from valid third-party liability insurance (MTPLI) policies until their expiration. Such an assessment is essential to adequately cover MTPLI policies and ensure the sustainable development of insurance companies. The geography of the study covers the MTPLI market of Europe in the main areas, but a deeper analysis of the impact of various factors, interactions, and interrelationships in MTPLI product is focused on Latvian market data due to availability of high-quality primary data. The research is based on the analysis of primary Latvian MTPLI policies data of more than 128,000 road traffic accidents that have occurred during the time period from 2014 till 2020. Risk driver selection was performed based on the existing scientific studies and correlation analysis of the sample set. Both linear and nonlinear forms of relationships were used for modelling. A multivariate modeling was used to identify significant risk factors and to quantify their impact on loss of incidents. Statistical stability of the models was tested using chi-squared, t-tests and p-values. Validation of models calibrated where done using prediction errors measurements: mean square error (MSE), root mean squared error (RMSE), and mean absolute error (MAE) assessment both within sample and out of sample technics. The results indicated that the driver's behavior (penalties and Bonus-Malus) as well as vehicle parameters (weight and age), had significant impacts on crash losses.

Suggested Citation

  • Aivars Spilbergs & Andris Fomins & Māris Krastiņš, 2022. "Multivariate Modelling of Motor Third Party Liability Insurance Claims," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 8(1), pages 5-18.
    • Handle: RePEc:men:journl:v:8:y:2022:i:1:p:5-18
    DOI: 10.11118/ejobsat.2022.002
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    References listed on IDEAS

    as
    1. Klein, Nadja & Denuit, Michel & Lang, Stefan & Kneib, Thomas, 2014. "Nonlife ratemaking and risk management with Bayesian generalized additive models for location, scale, and shape," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 225-249.
    2. Denuit, Michel & Lang, Stefan, 2004. "Non-life rate-making with Bayesian GAMs," Insurance: Mathematics and Economics, Elsevier, vol. 35(3), pages 627-647, December.
    3. Frangos, Nikolaos & Karlis, Dimitris, 2004. "Modelling losses using an exponential-inverse Gaussian distribution," Insurance: Mathematics and Economics, Elsevier, vol. 35(1), pages 53-67, August.
    4. Klein, Nadja & Denuit, Michel & Lang, Stefan & Kneib, Thomas, 2014. "Nonlife ratemaking and risk management with Bayesian generalized additive models for location, scale, and shape," LIDAM Reprints ISBA 2014006, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. de Jong,Piet & Heller,Gillian Z., 2008. "Generalized Linear Models for Insurance Data," Cambridge Books, Cambridge University Press, number 9780521879149.
    6. Frees, Edward W. & Valdez, Emiliano A., 2008. "Hierarchical Insurance Claims Modeling," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1457-1469.
    7. Arthur Charpentier & Arthur David & Romuald Elie, 2016. "Optimal Claiming Strategies in Bonus Malus Systems and Implied Markov Chains," Working Papers hal-01326798, HAL.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Marian Reiff & Erik Šoltés & Silvia Komara & Tatiana Šoltésová & Silvia Zelinová, 2022. "Segmentation and estimation of claim severity in motor third-party liability insurance through contrast analysis," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(3), pages 803-842, September.

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    More about this item

    Keywords

    road traffic accidents; risk drivers; non-life insurance; MTPL insurance; private insurance; passenger cars; Bonus-Malus system; MTPL insurance claims paid; multivariate modelling;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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