Big data management algorithms in artificial Internet of Things-based fintech

• Authors: Mihai Andronie , Mariana Iatagan , Cristian Uță , Iulian Hurloiu , Adrian Dijmărescu , Irina Dijmărescu

Abstracts

EN

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.

Keywords

EN

big data management algorithms; artificial intelligence; Internet of Things; fintech; banking; capital markets

• Publisher: Instytut Badań Gospodarczych
• Journal: Oeconomia Copernicana
• Year: 2023
• Volume: 14
• Issue: 3
• Pages: 769-793

Dates

published

2023

Contributors

author

Mihai Andronie

• Spiru Haret University

• https://orcid.org/0000000285777227

author

Mariana Iatagan

• Spiru Haret University

• https://orcid.org/0000000187022162

author

Cristian Uță

• Spiru Haret University

• https://orcid.org/0000000342326263

author

Iulian Hurloiu

• Spiru Haret University

• https://orcid.org/000000027642901X

author

Adrian Dijmărescu

• Fundeni Clinical Institute

• https://orcid.org/000000034536496X

author

Irina Dijmărescu

• Grigore Alexandrescu Children’s Emergency Hospital

• https://orcid.org/0000000258142082

References

• Akmal, S., Talha, M., Faisal, S. M., Ahmad, M., & Khan, A. K. (2023). Perceptions about FinTech: New evidences from the Middle East. Cogent Economics & Finance, 11(1), 2217583.
• Andronie, M., Lăzăroiu, G., Iatagan, M., Uță, C., Ștefănescu, R., & Cocoșatu, M. (2021a). Artificial intelligence-based decision-making algorithms, Internet of Things sensing networks, and deep learning-assisted smart process management in cyber-physical production systems. Electronics, 10, 2497.
• Andronie, M., Lăzăroiu, G., Iatagan, M., Hurloiu, I., & Dijmărescu, I. (2021b). Sustainable cyber-physical production systems in big data-driven smart urban economy: A systematic literature review. Sustainability, 13, 751.
• Andronie, M., Lăzăroiu, G., Iatagan, M., Hurloiu, I., Ștefănescu, R., Dijmărescu, A., Dijmărescu, I. (2023a). Big data management algorithms, deep learning-based object detection technologies, and geospatial simulation and sensor fusion tools in the Internet of Robotic Things. ISPRS International Journal of Geo-Information, 12, 35.
• Andronie, M., Lăzăroiu, G., Karabolevski, O. L., Ștefănescu, R., Hurloiu, I., Dijmărescu, A., & Dijmărescu, I. (2023b). Remote big data management tools, sensing and computing technologies, and visual perception and environment mapping algorithms in the Internet of Robotic Things. Electronics, 12, 22.
• Awais, M., Afzal, A., Firdousi, S., & Hasnaoui, A. (2023). Is fintech the new path to sustainable resource utilisation and economic development? Resources Policy, 81, 103309.
• Babaei, G., Giudici, P., & Raffinetti, E. (2023). Explainable FinTech lending. Journal of Economics and Business. Advance online publicaiton.
• Barbu, C. M., Florea, D. L., Dabija, D. C., & Barbu, M. C. R. (2021). Customer experience in fintech. Journal of Theoretical and Applied Electronic Commerce Research, 16(5), 1415‒1433.
• Ben Romdhane, Y., Kammoun, S., & Loukil, S. (2023). The impact of Fintech on inflation and unemployment: The case of Asia. Arab Gulf Journal of Scientific Research. Advance online publicaiton.
• Caragea, D., Cojoianu, T., Dobri, M., Hoepner, A., Peia, O., & Romelli, D. (2023). Competition and innovation in the financial sector: Evidence from the rise of FinTech start-ups. Journal of Financial Services Research. Advance online publicaiton.
• Cazazian, R. (2022). Blockchain technology adoption in artificial intelligence-based digital financial services, accounting information systems, and audit quality control. Review of Contemporary Philosophy, 21, 55–71.
• Chen, W., Wu, W., & Zhang, T. (2023). Fintech development, firm digitalization, and bank loan pricing. Journal of Behavioral and Experimental Finance, 39, 100838.
• Dabija, D. C., Csorba, L. M., Isac, F. L., & Rusu, S. (2022). Building trust towards sharing economy platforms beyond the COVID-19 pandemic. Electronics, 11(18), 2916.
• Dabija, D. C., Csorba, L. M., Isac, F. L., & Rusu, S. (2023). Managing sustainable sharing economy platforms: A stimulus–organism–response based structural equation modelling on an emerging market. Sustainability, 15(6), 5583.
• Doumpos, M., Zopounidis, C., Gounopoulos, D., Platanakis, E., & Zhang, W. (2023). Operational research and artificial intelligence methods in banking. European Journal of Operational Research, 306(1), 1–16.
• Edo, O. C., Etu, E.-E., Tenebe, I., Oladele, O. S., Edo, S., Diekola, O. A., & Emakhu, J. (2023). Fintech adoption dynamics in a pandemic: An experience from some financial institutions in Nigeria during COVID-19 using machine learning approach. Cogent Business & Management, 10(2), 2242985.
• Jareño, F., & Yousaf, I. (2023). Artificial intelligence-based tokens: Fresh evidence of connectedness with artificial intelligence-based equities. International Review of Financial Analysis, 89, 102826.
• Gajdosikova, D., Lăzăroiu, G., & Valaskova, K. (2023). How particular firm-specific features influence corporate debt level: A case study of Slovak enterprises. Axioms, 12, 183.
• Gonçalves, A. R., Breda Meira, A., Shuqair, S., & Costa Pinto, D. (2023). Artificial intelligence (AI) in FinTech decisions: The role of congruity and rejection sensitivity. International Journal of Bank Marketing. Advance online publicaiton.
• Gordon, S. (2022). Virtual navigation and geospatial mapping tools, customer data analytics, and computer vision and simulation optimization algorithms in the blockchain-based metaverse. Review of Contemporary Philosophy, 21, 89–104.
• Grupac, M., Machcinik, S., & Negoianu, A.-E. (2023). Immersive engagement and geospatial mapping technologies, deep learning and neural network algorithms, and visual perception and data mining tools in metaverse interactive and extended reality environments. Linguistic and Philosophical Investigations, 22, 196–212.
• Ha, L. T. (2023). Dynamic connectedness between FinTech innovation and energy volatility during the war in time of pandemic. Environmental Science and Pollution Research, 30, 83530–83544.
• He, C., Geng, X., Tan, C., & Guo, R. (2023a). Fintech and corporate debt default risk: Influencing mechanisms and heterogeneity. Journal of Business Research, 164, 113923.
• He, M., Song, G., & Chen, Q. (2023b). Fintech adoption, internal control quality and bank risk taking: Evidence from Chinese listed banks. Finance Research Letters, 57, 104235.
• Horak, J., Voumik, L. C., & Popescu, G. H. (2023). Remote sensing data fusion techniques, multimodal behavioral predictive and mobile location analytics, and spatial cognition and context awareness algorithms in the metaverse economy. Linguistic and Philosophical Investigations, 22, 77–93.
• Ionescu, L. (2022). Big data algorithms and artificial intelligence technologies in cloud-based accounting information systems. Analysis and Metaphysics, 21, 42–57.
• Jiang, B. (2023). Does fintech promote the sustainable development of renewable energy enterprises? Environmental Science and Pollution Research, 30, 65141–65148.
• Khan, S., Khan, H. U., & Nazir, S. (2023). Utilizing the collective wisdom of fintech in the gcc region: A systematic mapping approach. Measurement and Control, 56(3/4), 713–732.
• Kliestik, T., Valaskova, K., Lăzăroiu, G., Kovacova, M., & Vrbka, J. (2020). Remaining financially healthy and competitive: The role of financial predictors. Journal of Competitiveness, 12(1), 74–92.
• Kliestik, T., Vochozka, M., & Vasić, M. (2022). Biometric sensor technologies, visual imagery and predictive modeling tools, and ambient sound recognition software in the economic infrastructure of the metaverse. Review of Contemporary Philosophy, 21, 72–88.
• Kovacova, M., Horak, J., & Popescu, G. H. (2022). Haptic and biometric sensor technologies, deep learning-based image classification algorithms, and movement and behavior tracking tools in the metaverse economy. Analysis and Metaphysics, 21, 176–192.
• Lai, X., Yue, S., Guo, C., & Zhang, X. (2023). Does FinTech reduce corporate excess leverage? Evidence from China. Economic Analysis and Policy, 77, 281–299.
• Lăzăroiu, G., Andronie, M., Iatagan, M., Geamănu, M., Ștefănescu, R., & Dijmărescu, I. (2022). Deep learning-assisted smart process planning, robotic wireless sensor networks, and geospatial big data management algorithms in the Internet of Manufacturing Things. ISPRS International Journal of Geo-Information, 11, 277.
• Li, C., Xu, Y., Zheng, H., Wang, Z., Han, H., & Zeng, L. (2023). Artificial intelligence, resource reallocation, and corporate innovation efficiency: Evidence from China’s listed companies. Resources Policy, 81, 103324.
• Lin, R.-R., & Lee, J.-C. (2023). The supports provided by artificial intelligence to continuous usage intention of mobile banking: Evidence from China. Aslib Journal of Information Management. Advance online publicaiton.
• Mahmud, K., Joarder, M. M. A., & Sakib, K. (2023). Customer Fintech readiness (CFR): Assessing customer readiness for fintech in Bangladesh. Journal of Open Innovation: Technology, Market, and Complexity, 9(2), 100032.
• Mariani, M. M., Machado, I., & Nambisan, S. (2023). Types of innovation and artificial intelligence: A systematic quantitative literature review and research agenda. Journal of Business Research, 155(B), 113364.
• Mirza, N., Elhoseny, M., Umar, M., & Metawa, N. (2023a). Safeguarding FinTech innovations with machine learning: Comparative assessment of various approaches. Research in International Business and Finance, 66, 102009.
• Mirza, N., Umar, M., Afzal, A., & Firdousi, S. F. (2023b). The role of fintech in promoting green finance, and profitability: Evidence from the banking sector in the euro zone. Economic Analysis and Policy, 78, 33–40.
• Moldovan, G. M., Dabija, D. C., & Pocol, C.B. (2022). Resources management for a resilient world: A literature review of Eastern European countries with focus on household behaviour and trends related to food waste. Sustainability, 14(12), 7123.
• Nica, E., & Vahancik, J. (2023). Geospatial big data management and computer vision algorithms, remote sensing and image recognition technologies, and event modeling and forecasting tools in the virtual economy of the metaverse. Linguistic and Philosophical Investigations, 22, 9–25.
• Osei-Assibey Bonsu, M., Wang, Y., & Guo, Y. (2023). Does fintech lead to better accounting practices? Empirical evidence. Accounting Research Journal, 36(2/3), 129–147.
• Peters, M. A., Jackson, L., Papastephanou, M., Jandrić, P., Lăzăroiu, G., Evers, C. W., Cope, B., Kalantzis, M., Araya, D., Tesar, M., Mika, C., Chen, L., Wang, C., Sturm, S., Rider, S., & Fuller, S. (2023). AI and the future of humanity: ChatGPT-4, philosophy and education – Critical responses. Educational Philosophy and Theory. Advance online publicaiton.
• Qiu, Z., Wang, J., Wu, K., & Yang, S. (2023). The value of FinTech innovations for the finance industry: Evidence from China. Economic and Political Studies. Advance online publicaiton.
• Rabbani, M. R., Lutfi, A., Ashraf, M. A., Nawaz, N., & Watto, W. A. (2023). Role of artificial intelligence in moderating the innovative financial process of the banking sector: A research based on structural equation modeling. Frontiers in Environmental Science, 10, 978691.
• Rahmani, A. M., Rezazadeh, B., Haghparast, M., Chang, W.-C., & Ting, S. G. (2023). Applications of artificial intelligence in the economy, including applications in stock trading, market analysis, and risk management. IEEE Access, 11, 80769–80793.
• Sampat, B., Mogaji, E., & Nguyen, N. P. (2023). The dark side of FinTech in financial services: A qualitative enquiry into FinTech developers’ perspective. International Journal of Bank Marketing. Advance online publication.
• Singh, C. (2023). Artificial intelligence and deep learning: Considerations for financial institutions for compliance with the regulatory burden in the United Kingdom. Journal of Financial Crime. Advance online publicaiton.
• Su, F., & Xu, C. (2023). Curbing credit corruption in China: The role of FinTech. Journal of Innovation & Knowledge, 8(1), 100292.
• Upreti, K., Syed, M. H., Khan, M. A., Fatima, H., Alam, M. S., & Sharma, A. K. (2023). Enhanced algorithmic modelling and architecture in deep reinforcement learning based on wireless communication Fintech technology. Optik, 272, 170309.
• Vagner, L., Valaskova, K., Durana, P., & Lăzăroiu, G. (2021). Earnings management: A bibliometric analysis. Economics and Sociology, 14(1), 249‒262.
• Valaskova, K., Nagy, M., Zabojnik, S., & Lăzăroiu, G. (2022). Industry 4.0 wireless networks and cyber-physical smart manufacturing systems as accelerators of value-added growth in Slovak exports. Mathematics, 10, 2452.
• Wang, L., Cao, Z., & Dong, Z. (2023). Are artificial intelligence dividends evenly distributed between profits and wages? Evidence from the private enterprise survey data in China. Structural Change and Economic Dynamics, 66, 342–356.
• Wu, G., Luo, J., & Tao, K. (2023). Research on the influence of FinTech development on credit supply of commercial banks: The case of China. Applied Economics. Advance online publicaiton.
• Yan, X. (2023). Research on financial field integrating artificial intelligence: Application basis, case analysis, and SVR model-based overnight. Applied Artificial Intelligence, 37(1), 2222258.
• Zhao, Y., Goodell, J. W., Wang, Y., & Abedin, M. Z. (2023). Fintech, macroprudential policies and bank risk: Evidence from China. International Review of Financial Analysis, 87, 102648.
• Zheng, Z., He, J., Yang, Y., Zhang, M., Wu, D., Bian, Y., & Cao, J. (2023). Does financial leverage volatility induce systemic financial risk? Empirical insight based on the Chinese fintech sector. Managerial and Decision Economics, 44(2), 1142–1161.
• Zvarikova, K., Rowland, Z., & Nica, E. (2022). Multisensor fusion and dynamic routing technologies, virtual navigation and simulation modeling tools, and image processing computational and visual cognitive algorithms across Web3-powered metaverse worlds. Analysis and Metaphysics, 21, 125–141.

Identifiers

DOI

10.24136/oc.2023.023

Biblioteka Nauki

19902795