TY - GEN
T1 - Insurance Reserve Prediction
T2 - 2021 International Conference on Computational Science and Computational Intelligence, CSCI 2021
AU - Taha, Ayman
AU - Cosgrave, Bernard
AU - Rashwan, Wael
AU - McKeever, Susan
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/12
Y1 - 2021/12
N2 - Predicting claims' reserve is a critical challenge for insurers and has dramatic consequences on their managerial, financial and underwriting decisions. The insurers' capital and their underwriting capacity of further business are impacted by inaccurate reserve estimates. Increasing premium rates and adjusting the underwriting policy decisions may balance the impact of unexpected claims, but will have a negative impact on their business opportunities. To address this, several papers focusing on the prediction of insurance reserve have been published in the literature. In this paper, we provide a comprehensive review of the research on the insurance reserve prediction techniques in economics and actuarial science literature as well as machine learning and computer science literature. Moreover, we classify these techniques into different approaches based on the prediction mechanism they use in estimation. For each approach, we survey reserve prediction methods, and then show the similarities and differences among them. In addition, the review is armed with a discussion on the challenges and the future opportunities.
AB - Predicting claims' reserve is a critical challenge for insurers and has dramatic consequences on their managerial, financial and underwriting decisions. The insurers' capital and their underwriting capacity of further business are impacted by inaccurate reserve estimates. Increasing premium rates and adjusting the underwriting policy decisions may balance the impact of unexpected claims, but will have a negative impact on their business opportunities. To address this, several papers focusing on the prediction of insurance reserve have been published in the literature. In this paper, we provide a comprehensive review of the research on the insurance reserve prediction techniques in economics and actuarial science literature as well as machine learning and computer science literature. Moreover, we classify these techniques into different approaches based on the prediction mechanism they use in estimation. For each approach, we survey reserve prediction methods, and then show the similarities and differences among them. In addition, the review is armed with a discussion on the challenges and the future opportunities.
KW - Actuarial chain ladder
KW - Insurance data analytics
KW - Loss estimation
KW - Reserve prediction
KW - Stochastic methods
UR - https://www.scopus.com/pages/publications/85127515671
U2 - 10.1109/csci54926.2021.00120
DO - 10.1109/csci54926.2021.00120
M3 - Conference contribution
AN - SCOPUS:85127515671
T3 - Proceedings - 2021 International Conference on Computational Science and Computational Intelligence, CSCI 2021
SP - 290
EP - 295
BT - Proceedings - 2021 International Conference on Computational Science and Computational Intelligence, CSCI 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 15 December 2021 through 17 December 2021
ER -