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Georgiou, K., Domazakis, G. N., Pappas, D., & Yannacopoulos, Y. N. (2021). Markov chain Lumpability and Applications to Credit Risk Modelling in Compliance with the International Financial Reporting Standard 9 framework. Elsevier.
https://doi.org/10.1016/j.ejor.2020.11.014

has been cited by the following article:

• TITLE: Aggregation and Establishment of Onerous Contracts as Required by IFRS17 Based on a Stochastic Matrix and the Lumpability Concept of a Markov Chain

  AUTHORS: Alexandros A. Zimbidis, Ioannis Gkounopoulos

  KEYWORDS: IFRS17, Onerous Contracts, Markov Chains, Lumpability, Wasserstein Distance, Motor Insurance

  JOURNAL NAME: Journal of Financial Risk Management, Vol.13 No.2, May 28, 2024

  ABSTRACT: This paper aims to formulate a new innovative method for contract classification under IFRS17 for motor insurance operating under the typical Bonus-Malus System. The specific method of classification provides robust results with respect to borderlines drawn between the three categories imposed by IFRS17, as the criterion of lumpability preserves the important stochastic elements of the typical Bonus-Malus System. This approach eliminated any subjectivity which may arise when considering only the profitability criterion based on loss ratio which is affected by the high volatility of the claim experience. We apply this method to various forms of indicative stochastic matrices. Our results reveal the impact of the proposed method on contract classification. This provides valuable insights for practitioners and regulators seeking to enhance and empower their professional actuarial judgement on financial reporting and risk assessment within the IFRS17 framework.