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@article{203861,
        author = {Ms. Gayathri N M and Mr. Selva Kumar M and Dr.Rajalakshmi C and Dr. K. Vijayalakshmi},
        title = {A COMPARATIVE TIME SERIES ANALYSIS OF ARIMA AND EXPONENTIAL SMOOTHING MODELS IN FORECASTING HEALTH INSURANCE PENETRATION IN POST-PANDEMIC INDIA (2018–2026) (WITH PROJECTIONS TOWARD INSURANCE FOR ALL BY 2047)},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {667-671},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=203861},
        abstract = {This study analyses the quarterly trend of health insurance penetration in post-pandemic India from 2018 to 2024 using ARIMA and Exponential Smoothing models. Secondary data were collected from IRDAI, the General Insurance Council, and Ministry of Statistics and Programme Implementation (MoSPI). Time series forecasting techniques were applied to examine trends and generate forecasts for 2025–2030. The forecasting performance of both models was evaluated using MAE, RMSE, and MAPE. The findings indicate a steady increase in health insurance penetration, with the ARIMA model showing comparatively better forecasting accuracy. The study provides useful insights toward achieving the “Insurance for All by 2047” initiative.},
        keywords = {Health Insurance Penetration, ARIMA, Exponential Smoothing, Time Series Forecasting, Post-Pandemic India, Insurance for All 2047},
        month = {June},
        }