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All Journal EKSAKTA: Journal of Sciences and Data Analysis
Hani’atul Maghfuroh
Statistics Department FMIPA Universitas Islam Indonesia, Jln. Kaliurang Km 14.5 Sleman, Yogyakarta, Indonesia
Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Materials Science & Nanotechnology

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Prediction of Outstanding Claims Liability in Non-Life Insurance: An Application of Adaptive Grey Model Mujiati Dwi Kartikasari; Hani’atul Maghfuroh
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 2, ISSUE 2, August 2021
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol2.iss2.art4

Abstract

In order to assess the solvency of non-life insurance companies, the prediction of outstanding claims liability is very important. Prediction of outstanding claims liability is usually done by using a run-off triangle data scheme. However, if data are not available to form the scheme, the prediction of outstanding claims liability cannot be made. Another alternative for predicting of outstanding claims liability is to use time series analysis. This research uses an adaptive grey model that has the advantage of being free of assumptions of data patterns and a minimum amount of data used to predict is small (at least 4 data). To determine the accuracy of the adaptive grey model, we compare the prediction of outstanding claims liability using a grey model classic. Based on the analysis results, the adaptive grey model is better than the classic gray model in predicting outstanding claims liability.
Co-Authors Mujiati Dwi Kartikasari