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BERT-based NLP techniques for classification and severity modeling in basic warranty data study

Author

Listed:
  • Xu, Shuzhe
  • Zhang, Chuanlong
  • Hong, Don

Abstract

This paper is to explore data-driven models based on a newly developed natural language processing (NLP) tool called Bidirectional Encoder Representations from Transformer (BERT) to incorporate textural data information for group classification and loss amount prediction on truck's basic warranty claims. In group classification modeling, multiple-class logistic regression is compared with BERT-based back-propagation neural networks (NN). In group loss severity modeling, direct NN regression is compared with BERT-based NN regression prediction. Furthermore, based on the results from a so-called optimal bin-width algorithm, the severity distribution is fitted in Gamma and its parameters are then estimated using maximum likelihood estimation (MLE). The data experiments show that the BERT framework for NLP improves the classification of the warranty claims as well as the loss severity prediction both in accuracy and stability.

Suggested Citation

  • Xu, Shuzhe & Zhang, Chuanlong & Hong, Don, 2022. "BERT-based NLP techniques for classification and severity modeling in basic warranty data study," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 57-67.
    • Handle: RePEc:eee:insuma:v:107:y:2022:i:c:p:57-67
    DOI: 10.1016/j.insmatheco.2022.07.013
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    References listed on IDEAS

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    More about this item

    Keywords

    BERT; Classification; Data-driven; Loss severity; NLP; NN-regression; Warranty policy pricing;
    All these keywords.

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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