Proceedings of the 3rd International Conference on Digital Economy and Computer Application (DECA 2023)

Acturial analysis of insolvency probability considering correlations among claims: case study for transmisstion tower failures

Authors
Andy Wan1, Yanxiang Wang2, Yihan Xu3, Eric Zhang4, *
1Glenbrook North High School, IL, USA, 60062
2University of Wisconsin-Madison, WI, USA, 53715
3Hefei No.1 High School, Hefei, China, 230000
4University of Rochester, Rochester, NY, USA, 14642
*Corresponding author. Email: ericzzhang@gmail.com
Corresponding Author
Eric Zhang
Available Online 4 December 2023.
DOI
10.2991/978-94-6463-304-7_32How to use a DOI?
Keywords
Actuarial analysis. Insolvency probability; Correlations; Infrastructure; Property insurance; Nationwide transmission tower failures
Abstract

This research aims to develop an actuarial analysis framework to evaluate the probability of insolvency for the infrastructure property insurance of a specific region. The study focuses on the case of nationwide transmission tower failures. The proposed framework takes into account the correlations among claims, as well as the interdependence of individual infrastructure failures, in order to calculate revised insurance premiums. To achieve this, the research utilizes advanced statistical modeling techniques to capture the intricate relationships between claims and their correlation patterns. By integrating historical data on transmission tower failures, claims, and relevant economic factors, a comprehensive risk assessment model is constructed. This model estimates the probability of insolvency for the insurance portfolio, accounting for the interplay of correlated claims. Furthermore, the research investigates the interdependence among individual transmission towers, recognizing that failures in one tower can trigger a cascading effect throughout the network. This dynamic is captured through network analysis methods, allowing for a more accurate assessment of the risk and potential systemic repercussions. The findings of this study could provide valuable insights for insurance companies, policyholders, and risk managers involved in the infrastructure sector. The actuarial analysis framework incorporates correlations among claims and accounts for the interconnectedness of transmission tower failures. Such a comprehensive approach improves accuracy in estimating insolvency probabilities, enabling better risk pricing, underwriting, and decision-making in the insurance industry.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 3rd International Conference on Digital Economy and Computer Application (DECA 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
4 December 2023
ISBN
978-94-6463-304-7
ISSN
2589-4900
DOI
10.2991/978-94-6463-304-7_32How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Andy Wan
AU  - Yanxiang Wang
AU  - Yihan Xu
AU  - Eric Zhang
PY  - 2023
DA  - 2023/12/04
TI  - Acturial analysis of insolvency probability considering correlations among claims: case study for transmisstion tower failures
BT  - Proceedings of the 3rd International Conference on Digital Economy and Computer Application (DECA 2023)
PB  - Atlantis Press
SP  - 300
EP  - 307
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-304-7_32
DO  - 10.2991/978-94-6463-304-7_32
ID  - Wan2023
ER  -