Financing and Fiscality in the Context of Artificial Intelligence at the Global Level

  • Otilia Manta PhD

Abstract

The current financing models, as well as the fiscal models, are based on the current resources available at both the financial system and the fiscal system, but in close interdependence with those existing at the global level, the technology being one of them. Moreover, we consider that increasingly in the resource hierarchy, the place of the human factor is replaced by artificial intelligence (regardless of whether we are talking about industrial robots or intelligent technologies as is the case in the banking financial field). The new ways of approaching and coordinating finances aim to increase the degree of flexibility of financial networks and harmonize the results of those financial institutions that master and use complex but complementary technologies in order to obtain a final product or services optimal and with direct connection to its beneficiary. The defining elements for any financing and control model, regardless of whether we think of Fintech or other programs such as Fiscalis , are given by the following characteristics: digitization (artificial intelligence tools are crucial for digitizing financial services and fiscal), mobilization (virtual space offers not only the possibility but especially the platform for achieving the mobility of services), disintermediation (virtual space offers the possibility of direct access without intermediaries) and automation (through the financial services existing on the online platforms, the beneficiary of the service and the service provider optimizes its time and cost in favor of making the service profitable).
Published
Jan 1, 2020
How to Cite
MANTA, Otilia. Financing and Fiscality in the Context of Artificial Intelligence at the Global Level. European Journal of Marketing and Economics, [S.l.], v. 3, n. 1, p. 31-47, jan. 2020. ISSN 2601-8667. Available at: <http://journals.euser.org/index.php/ejme/article/view/4588>. Date accessed: 30 mar. 2020. doi: http://dx.doi.org/10.26417/ejme.v3i1.p31-47.