Temat: artificial intelligence algorithms - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Artificial intelligence algorithms and cloud computing technologies in blockchain-based fintech management
Autorzy:: Lăzăroiu, George
Bogdan, Mădălina
Geamănu, Marinela
Hurloiu, Lăcrămioara
Luminița, Luminița
Ștefănescu, Roxana
Powiązania:: https://bibliotekanauki.pl/articles/19901187.pdf
Data publikacji:: 2023
Wydawca:: Instytut Badań Gospodarczych
Tematy:: artificial intelligence algorithms
cloud computing
blockchain
fintech
green and sustainable finance
banking
Opis:: Research background: Fintech development shapes corporate investment efficiency and economic growth with innovative tools, and can decrease financing constraints of enterprises, enabling direct and indirect financing and furthering inter-bank competition. Crowdfunding- and blockchain-based fintech operations harness deep and maching learning algorithms, augmented and virtual reality technologies, and big data analytics in mobile payment transactions. Purpose of the article: We show that fintechs have reconfigured financial service delivery by harnessing AI-based data-driven algorithms and cloud and blockchain technologies. Fintech optimizes financial organization and services, economic structures and growth, data analysis, and digital banking performance. Machine learning algorithms can streamline payment operation capabilities and process promptness, ensuring smooth operational flows, assessing risks, and detecting frauds and money laundering by historical data and customer behavior analysis across instant payment networks and infrastructures. Methods: Quality tools: AXIS, Eppi-Reviewer, PICO Portal, and SRDR. Search period: July 2023. Search terms: “fintech” + “artificial intelligence algorithms”, “cloud computing technologies”, and “blockchain technologies”. Selected sources: 40 out of 195. Published research inspected: 2023. Data visualization tools: Dimensions and VOSviewer. Reporting quality assessment tool: PRISMA. Findings & value added: Fintech development enables organizational innovation by mitigating information asymmetry and financing limitations while providing financial assistance and tax incentives in relation to products and services. The fintech growth has influenced the dynamic intermediary function of financial institutions in terms of sustainability and economic development. Fintech and natural resources negatively influence, while green innovations and financial development further, environmental sustainability.
Źródło:: Oeconomia Copernicana; 2023, 14, 3; 707-730
2083-1277
Pojawia się w:: Oeconomia Copernicana
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Skocz do pozycji: 2.

Tytuł:: Big data management algorithms in artificial Internet of Things-based fintech
Autorzy:: Andronie, Mihai
Iatagan, Mariana
Uță, Cristian
Hurloiu, Iulian
Dijmărescu, Adrian
Dijmărescu, Irina
Powiązania:: https://bibliotekanauki.pl/articles/19902795.pdf
Data publikacji:: 2023
Wydawca:: Instytut Badań Gospodarczych
Tematy:: big data management algorithms
artificial intelligence
Internet of Things
fintech
banking
capital markets
Opis:: Research background: Fintech companies should optimize banking sector performance in assisting enterprise financing as a result of firm digitalization. Artificial IoT-based fintech-based digital transformation can relevantly reverse credit resource misdistribution brought about by corrupt relationship chains. Purpose of the article: We aim to show that fintech can decrease transaction expenses and consolidates firm stock liquidity, enabling excess leverage decrease and cutting down information asymmetry and transaction expenses across capital markets. AI- and IoT-based fintechs enable immersive and collaborative financial transactions, purchases, and investments in relation to payment tokens and metaverse wallets, managing financial data, infrastructure, and value exchange across shared interactive virtual 3D and simulated digital environments. Methods: AMSTAR is a comprehensive critical measurement tool harnessed in systematic review methodological quality evaluation, DistillerSR is harnessed in producing accurate and transparent evidence-based research through literature review stage automation, MMAT appraises and describes study checklist across systematic mixed studies reviews in terms of content validity and methodological quality predictors, Rayyan is a responsive and intuitive knowledge synthesis tool and cloud-based architecture for article inclusion and exclusion suggestions, and ROBIS appraises systematic review bias risk in relation to relevance and concerns. As a reporting quality assessment tool, the PRISMA checklist and flow diagram, generated by a Shiny App, was used. As bibliometric visualization and construction tools for large datasets and networks, Dimensions and VOSviewer were leveraged. Search terms were “fintech” + “artificial intelligence”, “big data management algorithms”, and “Internet of Things”, search period was June 2023, published research inspected was 2023, and selected sources were 35 out of 188. Findings & value added: The growing volume of financial products and optimized operational performance of financial industries generated by fintech can provide firms with multifarious financing options quickly. Big data-driven fintech innovations are pivotal in banking and capital markets in relation to financial institution operational efficiency. Through data-driven technological and process innovation capabilities, AI system-based businesses can further automated services.
Źródło:: Oeconomia Copernicana; 2023, 14, 3; 769-793
2083-1277
Pojawia się w:: Oeconomia Copernicana
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Informacja

Wyszukujesz frazę "artificial intelligence algorithms" wg kryterium: Temat

Źródło danych

Dostawca treści

Kolekcja

Rok wydania

Wydawca

Temat

Autor

Typ dokumentu

Język