Data-driven decision-making and its application to the corporate cash management problem

F. Salas-Molina, J. A. Rodríguez-Aguilar, F. J. Martín, P. Díaz-García

Companies increasingly focus on the analysis of their business data to transform it into knowledge. In particular, cash managers daily face critical decisions to find a balance between cash holdings and short-term investments. We here explore the opportunities for improved decision-making derived from modeling cash flow uncertainty with the help of data-driven techniques within a multiobjective context. We first show that efforts in improving predictive accuracy are proportionally rewarded by cost savings. Next, we propose a multiobjective approach to the cash management problem and we also provide further insights on the selection of cash management models. Finally, we formulate new multiobjective cash management models based on linear and compromise programming. The results derived from this paper are ready to be implemented in decision support systems for cash managers.

Keywords: Multiple criteria decision-making, cash management, forecasting, risk, compromise programming

GT3-2 Multicritery Decision. Thesis Award
September 3, 2019  4:50 PM
I2L7. Georgina Blanes building

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