magistrsko delo
Abstract
Tehnološki napredek je nedvomno spremenil način opravljanja bančnih storitev, saj ponuja udobje, učinkovitost in razširjene funkcije. Vendar pa je tehnologija poleg prednosti prinesla tudi precejšnje zaplete, ki jih morajo banke obvladovati. Naša naloga se osredotoči na informacijske rešitve za odkrivanje finančnih goljufij prevar, ki imajo ključno vlogo v zagotavljanju stabilnega bančnega okolja. V današnjem digitalnem okolju, v katerem bančne transakcije potekajo preko spleta, kršitve varnosti podatkov pa predstavljajo velika tveganja, so zanesljive rešitve za odkrivanje goljufij bistvenega pomena za banke, da zagotovijo varnost in celovitost svojega poslovanja. Te rešitve uporabljajo najsodobnejše tehnologije, kot so podatkovno rudarjenje, strojno učenje in umetno inteligenco, za analizo velikih količin finančnih podatkov in prepoznavanje vzorcev, ki kažejo na goljufivo ravnanje. S spremljanjem transakcij v realnem času in povezovanjem več virov podatkov te rešitve bankam omogočajo hitro odkrivanje sumljivih dejavnosti in sprejemanje potrebnih ukrepov za zmanjšanje morebitnih izgub. Poleg tega vključujejo napredno analitiko za prepoznavanje zapletenih vzorcev goljufij in prilagajanje razvijajočim se taktikam goljufij. Ključni vidik teh rešitev je tudi skladnost z bančnimi regulacijami, ki pomagajo bankam upoštevati predpise in zahteve za poročanje ter zagotavljajo preglednost in odgovornost. Z uvedbo informacijskih rešitev za odkrivanje finančnih goljufij se lahko banke proaktivno borijo proti finančnim goljufijam, ščitijo premoženje strank ter ohranjajo zaupanje svojih strank.
S pomočjo obstoječe literature smo zasnovali konceptualno zasnovo informacijskega orodja, ki izhaja iz tehnike nadzorovanega učenja za odkrivanje transakcijskih prevar s kreditnimi karticami.
Keywords
informacijske rešitve;informacijski sistemi;bančni sektor;finančne prevare;goljufije;kreditne kartice;
Data
Language: |
English |
Year of publishing: |
2023 |
Typology: |
2.09 - Master's Thesis |
Organization: |
UM EPF - Faculty of Economics and Business |
Publisher: |
N. V. Zidarič |
UDC: |
004.77:336.71 |
COBISS: |
167616003
|
Views: |
10 |
Downloads: |
1 |
Average score: |
0 (0 votes) |
Metadata: |
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Other data
Secondary language: |
Slovenian |
Secondary title: |
Financial fraud detection information solution |
Secondary abstract: |
Technological advancements have revolutionized the banking industry, offering unparalleled convenience, efficiency, and enhanced features. However, alongside these benefits, technology has also introduced intricate challenges that banks must navigate. Our research focuses on the realm of cutting-edge IT solutions for financial fraud detection, which serves as a crucial pillar in establishing a secure and stable banking environment. In today's digital landscape, where online banking transactions thrive and the specter of data breaches looms large, robust fraud detection solutions are indispensable for banks to safeguard the sanctity and trustworthiness of their operations. These solutions leverage state-of-the-art technologies such as data mining, machine learning, and artificial intelligence to analyze vast volumes of financial data, unveiling telltale patterns indicative of fraudulent activities. By monitoring transactions in real-time and seamlessly integrating multiple data sources, these solutions empower banks to promptly identify suspicious behavior and take swift actions to minimize potential losses. Moreover, they incorporate advanced analytics to uncover intricate fraud patterns and swiftly adapt to ever-evolving fraudulent tactics. Compliance with rigorous banking regulations stands as a pivotal aspect of these solutions, enabling banks to diligently adhere to regulatory frameworks and reporting obligations, thereby upholding transparency and accountability. By embracing and deploying these IT solutions to combat financial fraud, banks can proactively protect customer assets, thwart illicit activities, and preserve unwavering customer trust.
Drawing upon extensive scholarly research, we have devised a conceptual design for an innovative IT tool, founded on the principles of supervised learning techniques, specifically tailored to detect credit card transaction fraud |
Secondary keywords: |
Information solutions;banking sector;information system;financial fraud;fraud detection system;credit cards; |
Type (COBISS): |
Master's thesis/paper |
Thesis comment: |
Univ. v Mariboru, Ekonomsko-poslovna fak. |
Pages: |
III, 65 str. |
ID: |
18916077 |