Generative artificial intelligence algorithms in Internet of Things blockchain-based fintech management DOI Creative Commons
Mihai Andronie, Roman Blažek, Mariana Iatagan

et al.

Oeconomia Copernicana, Journal Year: 2024, Volume and Issue: 15(4), P. 1349 - 1381

Published: Dec. 30, 2024

Research background: Big data-driven artificial Internet of Things (IoT) fintech algorithms can provide real-time personalized financial service access, strengthen risk management, and manage, monitor, mitigate transaction operational risks by credit suspicious abnormal pattern detection, synthetic data-based fraud simulation. Blockchain technologies, automated planning investment advice services, scoring detection tools be leveraged in trading forecasting planning, cryptocurrency transactions, workflow automation detection. Algorithmic tools, distributed ledger ensemble learning support vector machine are pivotal predictive analytics-based mitigation, customer behavior preference-based product personalization, automation. Credit management offer recommendations based on data, behavior, preferences, addition to history, generative adversarial deep recurrent neural networks. Purpose the article: We show that blockchain edge computing IoT-based algorithms, monitoring harnessed decision-making processes loan default rate mitigation for transaction, payment, process efficiency. Generative intelligence (AI) algorithmic systems drive coherent operations, tailored advice, influence decision processing, while performing assessment scenario simulation across fluctuating market conditions. Fraud money laundering prevention federated decentralized articulate profiling-based data patterns structures, assessment, repaying likelihood prediction, interest lending economic forecast-based analysis payment record infrastructures. Methods: published between 2023 2024 was identified analyzed ProQuest, Scopus, Web Science databases use screening quality software such as Abstrackr, AMSTAR, AXIS, CADIMA, CASP, Catchii, DistillerSR, Eppi-Reviewer, MMAT, Nested Knowledge, PICO Portal, Rayyan, ROBIS, SRDR+. Findings & value added: The main added derived from systematic literature review is AI-based services clarify decisions operations dynamic business environments capabilities assessment. benefits theory current state art AI technologies deployed optimization, score fraudulent Policy implications reveal streamline activity efficiency, design forecasting, carry out informed incident taking into account history evaluation improving experiences.

Language: Английский

Blockchain for Ethical and Transparent Generative AI Utilization by Banking and Finance Lawyers DOI
Swati Sachan, Vinícius Dezem, Dale S. Fickett

et al.

Communications in computer and information science, Journal Year: 2024, Volume and Issue: unknown, P. 319 - 333

Published: Jan. 1, 2024

Language: Английский

Citations

0
Fueling financial development: The crucial role of generative AI financing across nations DOI Creative Commons
Abu Bakkar Siddik,

Yong Li,

Min Du

et al.

Finance research letters, Journal Year: 2024, Volume and Issue: 72, P. 106519 - 106519

Published: Nov. 26, 2024

Language: Английский

Citations

0
Generative artificial intelligence algorithms in Internet of Things blockchain-based fintech management DOI Creative Commons
Mihai Andronie, Roman Blažek, Mariana Iatagan

et al.

Oeconomia Copernicana, Journal Year: 2024, Volume and Issue: 15(4), P. 1349 - 1381

Published: Dec. 30, 2024

Research background: Big data-driven artificial Internet of Things (IoT) fintech algorithms can provide real-time personalized financial service access, strengthen risk management, and manage, monitor, mitigate transaction operational risks by credit suspicious abnormal pattern detection, synthetic data-based fraud simulation. Blockchain technologies, automated planning investment advice services, scoring detection tools be leveraged in trading forecasting planning, cryptocurrency transactions, workflow automation detection. Algorithmic tools, distributed ledger ensemble learning support vector machine are pivotal predictive analytics-based mitigation, customer behavior preference-based product personalization, automation. Credit management offer recommendations based on data, behavior, preferences, addition to history, generative adversarial deep recurrent neural networks. Purpose the article: We show that blockchain edge computing IoT-based algorithms, monitoring harnessed decision-making processes loan default rate mitigation for transaction, payment, process efficiency. Generative intelligence (AI) algorithmic systems drive coherent operations, tailored advice, influence decision processing, while performing assessment scenario simulation across fluctuating market conditions. Fraud money laundering prevention federated decentralized articulate profiling-based data patterns structures, assessment, repaying likelihood prediction, interest lending economic forecast-based analysis payment record infrastructures. Methods: published between 2023 2024 was identified analyzed ProQuest, Scopus, Web Science databases use screening quality software such as Abstrackr, AMSTAR, AXIS, CADIMA, CASP, Catchii, DistillerSR, Eppi-Reviewer, MMAT, Nested Knowledge, PICO Portal, Rayyan, ROBIS, SRDR+. Findings & value added: The main added derived from systematic literature review is AI-based services clarify decisions operations dynamic business environments capabilities assessment. benefits theory current state art AI technologies deployed optimization, score fraudulent Policy implications reveal streamline activity efficiency, design forecasting, carry out informed incident taking into account history evaluation improving experiences.

Language: Английский

Citations

0