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Using an adaptive network-based fuzzy inference system model to predict the loss ratio of petroleum insurance in Egypt

Recurso electrónico / Electronic resource
Registro MARC
Tag12Valor
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040  ‎$a‎MAP‎$b‎spa‎$d‎MAP
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1001 ‎$0‎MAPA20220005067‎$a‎Khalil, Ahmed A.
24510‎$a‎Using an adaptive network-based fuzzy inference system model to predict the loss ratio of petroleum insurance in Egypt‎$c‎Ahmed A. Khalil, Zaiming Liu,Attia A. Ali
520  ‎$a‎Insurance companies and those interested in developing insurance services seek to use modern mathematical and statistical methods to study further and analyze all the company's corporate internal and external performance indicators. Loss ratio is a vital indicator used to measure performance and predict future losses in insurance companies. Many pivotal processors, such as underwriting and pricing depending on it. Therefore, accurate predictions assist insurance companies in making decisions properly. Thus, this paper aims to use the adaptive network-based fuzzy inference system (ANFIS) and autoregressive integrated moving average (ARIMA) models in forecasting the loss ratio of petroleum insurance in Misr Insurance Holding Company from 1995 to 2019. We applied many ANFIS models according to ANFIS properties and used the first 21 years (19952015), making up the training data set, which represents 85% of the data, as well as the past 4 years (20162019). Which are used for the testing stage and represent 15% of the data. Our finding concluded that ANFIS models give more accurate results than ARIMA models in predicting the loss ratio during the investigation by comparing results using predictive accuracy measures.
650 4‎$0‎MAPA20080555863‎$a‎Petroleros
650 4‎$0‎MAPA20080579258‎$a‎Cálculo actuarial
650 4‎$0‎MAPA20080570651‎$a‎Siniestralidad
651 1‎$0‎MAPA20120019348‎$a‎Egipto
7001 ‎$0‎MAPA20220005074‎$a‎Liu, Zaiming
7001 ‎$0‎MAPA20220005081‎$a‎Ali, Attia A.
7730 ‎$w‎MAP20077001748‎$g‎02/05/2022 Tomo 25 Número 1 - 2022 , p. 5-18‎$x‎1098-1616‎$t‎Risk management & insurance review‎$d‎Malden, MA : The American Risk and Insurance Association by Blackwell Publishing, 1999-