Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal International Journal of Quantitative Research and Modeling
Maelowati, Indah Dewi
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Environmental Science Physics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Risk Prediction and Estimation of Corporate Product Claim Reserve Funds in Insurance Companies Using the Extreme Value Theory Maelowati, Indah Dewi; Mayaningtyas, Chibi Adinda
International Journal of Quantitative Research and Modeling Vol 5, No 4 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i4.820

Abstract

Every human action involves risk, and in the insurance industry, customer claims are the biggest risk that companies face. This risk must be managed effectively through claim prediction, especially for corporate products. This research analyzes the risk of claims at insurance companies using the Extreme Value Theory (EVT) method, which can estimate extreme risks. Identification of extreme values in claims data is done through the EVT approach, namely Block-Maxima (BM). Generalized Extreme Value (GEV) distribution parameter estimation is performed, followed by prediction of claim risk using Value at Risk (VaR) and estimation of claim reserve funds. The results show that the GEV approach with a 95% confidence level is most suitable for predicting claim risk. Based on these results, the company requires a claim reserve fund of IDR 100,798,248,000 to deal with potential losses due to extreme claims.
Risk Prediction and Estimation of Corporate Product Claim Reserve Funds in Insurance Companies Using the Extreme Value Theory Maelowati, Indah Dewi; Mayaningtyas, Chibi Adinda
International Journal of Quantitative Research and Modeling Vol. 5 No. 4 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i4.820

Abstract

Every human action involves risk, and in the insurance industry, customer claims are the biggest risk that companies face. This risk must be managed effectively through claim prediction, especially for corporate products. This research analyzes the risk of claims at insurance companies using the Extreme Value Theory (EVT) method, which can estimate extreme risks. Identification of extreme values in claims data is done through the EVT approach, namely Block-Maxima (BM). Generalized Extreme Value (GEV) distribution parameter estimation is performed, followed by prediction of claim risk using Value at Risk (VaR) and estimation of claim reserve funds. The results show that the GEV approach with a 95% confidence level is most suitable for predicting claim risk. Based on these results, the company requires a claim reserve fund of IDR 100,798,248,000 to deal with potential losses due to extreme claims.
Co-Authors Mayaningtyas, Chibi Adinda