Umetna inteligenca in finančni nadzor v evrskem območju in Združenih državah Amerike

Zupanc, Darko

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Title:	Umetna inteligenca in finančni nadzor v evrskem območju in Združenih državah Amerike
Authors:	ID Zupanc, Darko (Author) ID Romih, Dejan (Mentor) More about this mentor... ID Taškar Beloglavec, Sabina (Comentor)
Files:	UN_Zupanc_Darko_2024.pdf (973,61 KB) MD5: A3C8D9C03DDB666B26FF67F36D54FCC5
Language:	Slovenian
Work type:	Bachelor thesis/paper
Typology:	2.11 - Undergraduate Thesis
Organization:	EPF - Faculty of Business and Economics
Abstract:	Umetna inteligenca ima potencial za izboljšanje učinkovitosti in inovacij v finančnem sektorju, vendar prinaša tudi probleme. Kompleksnost in občutljivost algoritmov umetne inteligence lahko vodita v nenadne šoke in destabilizacijo finančnih sistemov. Regulatorji se soočajo s težavami pri nadzoru umetne inteligence zaradi kompleksnosti delovanja in pomanjkanja transparentnosti, kar otežuje pravočasno prepoznavanje tveganj. Umetna inteligenca pa se lahko uporabi tudi kot rešitev, čeprav ne Evropska centralna banka ne ameriške Zvezne rezerve ne uporabljajo umetne inteligence pri svojih osnovnih dejavnostih, pa obe centralni banke raziskujeta potencialno uporabo umetne inteligence pri svojem delovanju. Eden možnih primerov uporabe umetne inteligence pri finančnem nadzoru je uporaba pri obvladovanju sistemskega tveganja, kjer jo lahko uporabljamo na dveh ravneh. Na mikro ravni se umetna inteligenca lahko uporablja za mikrobonitetni nadzor in notranje upravljanje tveganj, kar omogoča bolj natančno analizo in odločanje. Nasprotno pa je uporaba umetne inteligence pri makrobonitetnem nadzoru, ki se osredotoča na stabilnost celotnega finančnega sistema, bolj zapletena zaradi pomanjkanja podatkov in kompleksnosti finančnih trgov. Za uspešno integracijo umetne inteligence v regulativne okvire so potrebni jasni pravilniki, etične smernice ter sodelovanje med regulatorji, industrijo in akademsko skupnostjo. Nadaljnje raziskave in razvoj so ključni za izboljšanje razumevanja in obvladovanja tveganj, povezanih z uporabo umetne inteligence v finančnem sektorju.
Keywords:	umetna inteligenca, sistemsko tveganje, finančni nadzor, finančništvo, centralno bančništvo
Place of publishing:	Maribor
Publisher:	D. Zupanc
Year of publishing:	2024
PID:	20.500.12556/DKUM-89924-75118e6b-8868-544c-9fd2-a32c088a9551
UDC:	336:004.8
COBISS.SI-ID:	206790915
Publication date in DKUM:	09.09.2024
Views:	174
Downloads:	73
Metadata:
Categories:	EPF
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Licences

License:	CC BY 4.0, Creative Commons Attribution 4.0 International

Link:	http://creativecommons.org/licenses/by/4.0/
Description:	This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:	19.08.2024

Secondary language

Language:	English
Title:	Artificial intelligence and financial supervision in the euro area and the United States
Abstract:	Artificial intelligence has the potential to enhance efficiency and innovation in the financial sector, but it also presents challenges. The complexity and sensitivity of artificial intelligence algorithms can lead to sudden shocks and destabilization of financial systems. Regulators face difficulties in overseeing artificial intelligence due to its operational complexity and lack of transparency, which complicates timely risk identification. However, artificial intelligence can also be utilized as a solution, although neither the European Central Bank nor the Federal Reserves currently employs artificial intelligence in their core activities, both central banks are exploring the potential use of artificial intelligence in their operations. One potential application of artificial intelligence in financial oversight is its use in managing systemic risk, where it can be applied at two levels. Artificial intelligence can be used for micro-prudential supervision and internal risk management at the micro level, enabling more precise analysis and decision-making. Conversely, the use of artificial intelligence in macroprudential supervision, which focus on the stability of the entire financial system, is more complex due to data scarcity and the intricacies of financial markets. Clear policies, ethical guidelines, and collaboration among regulators, industry, and academia are essential for the successful integration of artificial intelligence into regulatory frameworks. Further research and development are crucial for improving understanding and managing the risks associated with the use of artificial intelligence in the financial sector.
Keywords:	artificial intelligence, systemic risk, financial supervision, finance, central banking

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