We develop the economic and operational foundations of a new method of financing companies' financial obligations. In this new banking business model, a network funder sets an optimal combination of netting and financing. Given a network of companies and their respective invoices, and under the condition of a full settlement of the invoices, the netting procedure consists in applying a multilateral netting algorithm to the network, conceived as an oriented multi-graph. This algorithm explores the set of invoices produced during regular periods of time (i.e. monthly, weekly, or even daily sessions) and maximises the amount of debt offset, given a quantity of loanable funds. From a systemic point of view, the algorithmic exploration of the multigraph is subject to optimisation constraints. The result of exploration allow the network funder to manage a policy trade-o_ between the maximisation invoices value and the minimisation of the amount of financing needed to settle payments in full. To test our method, we use an empirical dataset from an electronic invoices operator consisting of more than 60,000 companies. The policy trade-o_ shows that it is economically significant and feasible for a network funder to reduce the financial need of about 50% of companies by about 45% of the total amount of their financial obligations.

The economics and algorithmics of an integral settlement procedure on B2B networks

Massimo Amato
;
2021

Abstract

We develop the economic and operational foundations of a new method of financing companies' financial obligations. In this new banking business model, a network funder sets an optimal combination of netting and financing. Given a network of companies and their respective invoices, and under the condition of a full settlement of the invoices, the netting procedure consists in applying a multilateral netting algorithm to the network, conceived as an oriented multi-graph. This algorithm explores the set of invoices produced during regular periods of time (i.e. monthly, weekly, or even daily sessions) and maximises the amount of debt offset, given a quantity of loanable funds. From a systemic point of view, the algorithmic exploration of the multigraph is subject to optimisation constraints. The result of exploration allow the network funder to manage a policy trade-o_ between the maximisation invoices value and the minimisation of the amount of financing needed to settle payments in full. To test our method, we use an empirical dataset from an electronic invoices operator consisting of more than 60,000 companies. The policy trade-o_ shows that it is economically significant and feasible for a network funder to reduce the financial need of about 50% of companies by about 45% of the total amount of their financial obligations.
Amato, Massimo; Fatès, Nazim; Gobbi, Lucio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/4041737
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