Improving insurers’ loss reserve error prediction: Adopting combined unsupervised-supervised machine learning techniques in risk management-Reference-Cited by-同舟云学术

Improving insurers’ loss reserve error prediction: Adopting combined unsupervised-supervised machine learning techniques in risk management

Published:2022-11 Issue: Volume:8 Page:233-254
ISSN:2405-9188
Container-title:The Journal of Finance and Data Science
language:en
Short-container-title:The Journal of Finance and Data Science

Author:

Song In Jung,Heo Wookjae^ORCID

Funder

Hankuk University of Foreign Studies

Publisher

Elsevier BV

Subject

Applied Mathematics,Computer Science Applications,Economics and Econometrics,Finance,Business, Management and Accounting (miscellaneous),Statistics and Probability

Reference94 articles.

1. Management of the loss reserve accrual and the distribution of earnings in the property-casualty insurance industry;Beaver;J Account Econ,2003

2. Research design issues in earnings management studies;McNichols;J Account Publ Pol,2000

3. Principles of Risk Management and Insurance;Rejda,2020

4. Ratings: it’S accrual world: ratings: it's accrual world;Carson;J Risk Insur,2018

5. Insurer reserve error and executive compensation: insurer reserve error and executive compensation;Eckles;J Risk Insur,2009

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Business Strategy for Insurance Companies Using Deep Learning for Risk Assessment and Mitigation;2024 2nd International Conference on Disruptive Technologies (ICDT);2024-03-15

2. The effect of reinsurance treaties on the cedent loss reserving;Journal of Modelling in Management;2023-08-23

3. Transformação digital e seguro: uma revisão sistemática da literatura;Revista de Gestão e Secretariado (Management and Administrative Professional Review);2023-06-07