Umetna inteligenca - trenutni in prihodnji izzivi bančništva

delo diplomskega projekta

Jasmina Gergorec (Author), Andreja Primec (Mentor)

Abstract

Uporaba orodij za umetno inteligenco se je v zadnjem času stopnjevala v vseh gospodarskih panogah, med drugim tudi zaradi naraščajočega obsega digitalnih podatkov in vse večje računalniške zmogljivosti. Umetna inteligenca spreminja vse vidike poslovanja, tudi v bančništvu. Banke si danes ne morejo več privoščiti dolge čakalne vrste in pogoste obiske njihovih poslovalnic. Potrebujejo preobrazbo, da bi lahko sledile pričakovanjem svojih strank. Poglobljeno in strojno učenje so izboljšale izkušnje s strankami. Umetna inteligenca vključuje obdelavo naravnega jezika, prepoznavanje govora in strojni vid. Na izbiro imamo več vrst tehnik, ene izmed teh so: nevronske mreže, genetski algoritem ali mehka logika. Motivi za uvajanje umetne inteligence v bančništvo so predvsem odpravljanje človeških napak, boljši regulativni nadzor, hitrejše prepoznavanje in obvladovanje tveganj, prepoznavanje goljufij, boljša finančna varnost, kar se odraža pri nižjih stroških poslovanja ter predstavlja konkurenčno prednost posamezne banke.

Keywords

umetna inteligenca;strojno učenje;chatbot;bančništvo;varnost;

Data

Language:	Slovenian
Year of publishing:	2020
Typology:	2.11 - Undergraduate Thesis
Organization:	UM EPF - Faculty of Economics and Business
Publisher:	[J. Gergorec]
UDC:	004.8:336.71
COBISS:	40000003
Views:	583
Downloads:	99
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Artificial intelligence - current and future challenges in banking
Secondary abstract:	Lately, the use of tools for artificial intelligence has been increasing in every branch. The main reasons for this are the rapid growth of digital information and computer data storage. It affects all aspects of business, including banking. Banks can not afford to have long waiting lines and frequent visits to their offices. They need to incorporate change so they can satisfy the expectations of their clients. In-depth learning and machine learning have improved customer experiences. Artificial intelligence consists of natural language processing, speech recognition, and machine vision. There are different techniques of artificial intelligence, such as neural networks, genetic algorithms, and fuzzy logic. With the use of artificial intelligence, banks can avoid human error. Other advantages of artificial intelligence are better regulatory control, risk detection and damage control, fraud detection, and financial stability. As a result, the costs are lower, and business performance is improved.
Secondary keywords:	Artificial intelligence;banking;machine learning;chatbot;natural language processing;
Type (COBISS):	Diploma project paper
Thesis comment:	Univ. v Mariboru, Ekonomsko-poslovna fak.
Pages:	II, 37 str.
ID:	11991852