Towards data driven decision support for financial institutions: Predicting small companies business volume in Switzerland

Abstract

In Switzerland small and medium-sized enterprises represent more than 99% of all businesses. Therefore, prediction of their micro- and macroeconomic business development is of importance. In this paper, we propose a novel approach for predicting business volume using company characteristics and characteristics of the county the company operates in. We investigate which data sources can be combined to achieve this goal for small and midsized enterprises in Switzerland, building a model, irrespective of industry. We build our model based on the dataset obtained from an insurance company and combined the dataset with census data. We present two quantitative models, which allow to predict business volume in Swiss franks (CHF) and classify customers by size. Our results show that operational data from financial institutions (FI) customer relationship management (CRM) systems linked with census data are valuable to predict customer business volume.