In this study the IBNP reserve has been predicted using the ARIMA model and MLP-ANN model and then the results of both models have been compared, taking into consideration the earned premiums, paid claims and time as independent variables, and concluded that the earned premiums, the paid claims and time have significant effects on the IBNP reserve value and the MLP-ANN model is one of the best statistical models used in predicting the IBNP reserve as it has high accuracy results of RMSE and MAE tests. The model has been applied to actual data obtained from statistical yearbooks to obtain the value of IBNP reserves, earned premiums and paid claims for the period from 1995 to 2020.
Youssef, Rehab, Abdelbary, Tarek, Bakhit, Ali, & Atta, Mohamed. (2024). A Comparison between Prediction Methods of Incurred but Not Paid (IBNP) Reserve (A Theoretical and Applied Study). مجلة البحوث التجارية المعاصرة, 38(1), 131-142. doi: 10.21608/sjcp.2024.348141
MLA
Rehab Youssef; Tarek Abdelbary; Ali Bakhit; Mohamed Atta. "A Comparison between Prediction Methods of Incurred but Not Paid (IBNP) Reserve (A Theoretical and Applied Study)", مجلة البحوث التجارية المعاصرة, 38, 1, 2024, 131-142. doi: 10.21608/sjcp.2024.348141
HARVARD
Youssef, Rehab, Abdelbary, Tarek, Bakhit, Ali, Atta, Mohamed. (2024). 'A Comparison between Prediction Methods of Incurred but Not Paid (IBNP) Reserve (A Theoretical and Applied Study)', مجلة البحوث التجارية المعاصرة, 38(1), pp. 131-142. doi: 10.21608/sjcp.2024.348141
VANCOUVER
Youssef, Rehab, Abdelbary, Tarek, Bakhit, Ali, Atta, Mohamed. A Comparison between Prediction Methods of Incurred but Not Paid (IBNP) Reserve (A Theoretical and Applied Study). مجلة البحوث التجارية المعاصرة, 2024; 38(1): 131-142. doi: 10.21608/sjcp.2024.348141
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