Analysis of Forecasting Models using MS Excel versus Machine Learning Models

Abstract

Forecasting foresees trends and possibilities that your company can capitalize on in the future. This is a process used by both old and new businesses to affect company choices such as budgeting, hiring, and overall business practices. Usage of excel and machine learning techniques for forecasting comes with its set of pros and cons which we will uncover in the following sections. To handle risk, maximize resource allocation, and make informed strategicecisions, the banking sector depends largely on precise forecasting. The strengths and limits of MS Excel and ML models are contrasted in this study rticle, which dives into a comparative examination of forecasting models in the banking business. We evaluate their performance in various forecasting situations, taking into account criteria such as data complexity, accuracy, flexibility, and resource needs. The goal is to give useful insights for financial organizations looking to improve their forecasting procedures and use the power of advanced analytics in this critical subject.