Many investors, both novice and seasoned, have made considerable profits by strategizing and investing in stocks over the years. The study described in this paper uses a time series approach to model and forecast the stock values of the State Bank of India and the Indian Bank in India. From the Yahoo Finance web-site, we retrieved the stock prices for SBIN.NS and INDIANB.NS. This article’s primary goal is the Hampel filter-based outlier detection of stock prices. We used the Augmented Dickey-Fuller (ADF) test and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test to check the time series of stock prices for stationarity. We also discovered the (partial) autocorrelation function graphs (PACF/ACF). Finally, we used the AutoRegressive Integrated Moving Average (ARIMA) models to forecast the stock values of Indian banks.