FORECASTING THE GROUP HEALTH INSURANCE CLAIM SIZE FOR OUTPATIENT BENEFIT USING ARIMA METHOD

Abstract

Group health insurance is a health insurance product that provides health protection to a group of individuals that covers their medical expenses and related cost if they experience illness or accident that offers benefits such as lower premiums and easier risk selection. As an insurer, an insurance company needs to prepare for the size of claims that will occur in the next period in order to minimize the misfortunes caused by uncertain or inflated claims. This study predicts the number of group health insurance claims using the Autoregressive Integrated Moving Average (ARIMA) method. The ARIMA method uses historical data to forecast future values by identifying patterns and trends. This research is based on the need for PT. ABC to forecast future claims based on claims data from September 2022 to August 2023, which shows random fluctuations. With the ARIMA (3,1,0) model, this study successfully predicted the number of group health insurance claims for outpatient care. The model was selected based on Akaike Information Criterion (AIC) and validated using Shapiro-Wilk and Ljung-Box tests, which confirmed the normality and absence of autocorrelation in the residuals. The ARIMA (3,1,0) model was selected because it was the only model that met the statistical test requirements. This study forecasts claim amounts for the next five weeks, from August 26th, 2023, to September 23rd, 2023. The results show an MAE and RMSE of 970,418,438, an MSE of 1.36 × 1018, and a MAPE of 4.05%, indicating a high level of accuracy.