Forecasting of bank sales with Sberbank as a case study

Introduction. This scientific study highlights the relevance of modeling and forecasting sales of Sberbank in terms of effective business management. Sales forecast is an important tool for predicting the demand for goods and services, as well as determining the adequate strategies and tactics to achieve the company’s goals. The research is distinguished by its reference to artificial intelligence methods in the field of marketing. Forecasting methods applied to a proprietary data sample of Sberbank’s daily sales give novel results, which reliably supports the development of adequate strategies and tactics for successful business management. The key hypothesis of the study is to check the prognostic potential of machine learning methods against the traditional econometric approaches to modeling Sberbank’s sales. The purpose of the study is to develop sales forecasting models for multifunctional products and their practical instruments for Sberbank’s Sales Network Block.