AI integration in financial services: a systematic review of trends and regulatory challenges

0
AI integration in financial services: a systematic review of trends and regulatory challenges
  • Abou-Foul M, Ruiz-Alba JL, Soares A (2021) The impact of digitalization and servitization on the financial performance of a firm: an empirical analysis. Prod Plan Control 32(12):975–989

    Article 

    Google Scholar 

  • Ahern D (2021) Regulatory lag, regulatory friction and regulatory transition as fintech disenablers: Calibrating an EU response to the regulatory sandbox phenomenon. Eur Bus Organ Law Rev 22(3):395–432

    Article 

    Google Scholar 

  • Ahluwalia S, Mahto RV, Guerrero M (2020) Blockchain technology and startup financing: A transaction cost economics perspective. Technol Forecast Soc Change 151:119854

    Article 

    Google Scholar 

  • Ahmed S, Alshater MM, El Ammari A, Hammami H (2022) Artificial intelligence and machine learning in finance: A bibliometric review. Res Int Bus Financ 61:101646

    Article 

    Google Scholar 

  • Ahram et al. (2017) Blockchain technology innovations. In 2017 IEEE technology & engineering management conference (TEMSCON) (pp. 137-141). IEEE

  • Al Shiam SA, Hasan MM, Pantho MJ, Shochona SA, Nayeem MB, Choudhury MTH, Nguyen TN (2024) Credit Risk Prediction Using Explainable AI. J Bus Manag Stud 6(2):61–66

    Article 

    Google Scholar 

  • Ala’raj M, Abbod MF (2016) Classifiers consensus system approach for credit scoring. Knowl -Based Syst 104:89–105

    Article 

    Google Scholar 

  • Alapati NK, Valleru V (2023) The Impact of Explainable AI on Transparent Decision-Making in Financial Systems. J Innov Technol 6(1):1–5

  • Ali A, Abd Razak S, Othman SH, Eisa TAE, Al-Dhaqm A, Nasser M, Saif A (2022) Financial fraud detection based on machine learning: a systematic literature review. Appl Sci 12(19):9637

    Article 
    CAS 

    Google Scholar 

  • Alkaraan F, Albitar K, Hussainey K, Venkatesh VG (2022) Corporate transformation toward Industry 4.0 and financial performance: The influence of environmental, social, and governance (ESG). Technol Forecast Soc Change 175:121423

    Article 

    Google Scholar 

  • Alshater MM, Atayah OF, Khan A (2022) What do we know about business and economics research during COVID-19: A bibliometric review. Econ Res -Ekonomska Istraživanja 35(1):1884–1912

    Article 

    Google Scholar 

  • Antweiler W, Frank MZ (2004) Is all that talk just noise? The information content of internet stock message boards. J Financ 59(3):1259–1294

    Article 

    Google Scholar 

  • Aria M, Cuccurullo C (2017) Bibliometrix: An R-tool for comprehensive science mapping analysis. J Informetr 11(4):959–975

    Article 

    Google Scholar 

  • Arner DW, Buckley RP, Zetzsche DA, Veidt R (2020) Sustainability, FinTech and Financial Inclusion. Eur Bus Organ Law Rev 21(1):7–35. https://doi.org/10.1007/s40804-020-00183-y

    Article 

    Google Scholar 

  • Arner DW (2019) The evolution of fintech: A new post-crisis paradigm? In The Evolution of Fintech: A New Post-Crisis Paradigm?: Arner, Douglas W. [Sl]: SSRN

  • Arslanian H, Fischer F (2019) The future of finance: The impact of fintech, AI, and crypto on financial services. Springer Nature Switzerland AG

  • Atkins A, Niranjan M, Gerding E (2018) Financial news predicts stock market volatility better than close price. J Financ Data Sci 4(2):120–137

    Article 

    Google Scholar 

  • Aziz A, Naima U (2021) Rethinking digital financial inclusion: Evidence from Bangladesh. Technol Soc 64:101509

    Article 

    Google Scholar 

  • Azzutti A, Ringe W-G, Stiehl HS (2022) The regulation of AI trading from an AI life cycle perspective

  • Bahoo S, Cucculelli M, Goga X, Mondolo J (2024) Artificial intelligence in finance: A comprehensive review through bibliometric and content analysis. SN Bus Econ 4(2):23

    Article 

    Google Scholar 

  • Bank for International Settlements (2006) Basel committee on banking supervision (BCBS). International convergence of capital measurement and capital standards:: a revised framework

  • Basha SA, Elgammal MM, Abuzayed BM (2021) Online peer-to-peer lending: A review of the literature. Electron Commer Res Appl 48:101069

    Article 

    Google Scholar 

  • Begenau J, Farboodi M, Veldkamp L (2018) Big data in finance and the growth of large firms. J Monet Econ 97:71–87

  • Belanche D, Casaló LV, Flavián C (2019) Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers. Ind Manag Data Syst 119(7):1411–1430

    Article 

    Google Scholar 

  • Belanche D, Casaló LV, Flavián M, Loureiro SMC (2023) Benefit versus risk: A behavioral model for using robo-advisors. Service Industries J 45(1):132–159

  • Berdiyeva O, Islam MU, Saeedi M (2021) Artificial intelligence in accounting and finance: Meta-analysis. Int Bus Rev 3(1):56–79

    Google Scholar 

  • Beynon MJ, Peel MJ (2001) Variable precision rough set theory and data discretisation: an application to corporate failure prediction. Omega 29(6):561-576

  • Bibri SE (2020) The eco-city and its core environmental dimension of sustainability: green energy technologies and their integration with data-driven smart solutions. Energy Inform 3(1):4

    Article 

    Google Scholar 

  • Biju AKVN, Thomas AS, Thasneem J (2023) Examining the research taxonomy of artificial intelligence, deep learning & machine learning in the financial sphere—a bibliometric analysis. Quality & Quantity, 1–30

  • Blondel VD, Guillaume J-L, Lambiotte R, Lefebvre E (2008) Fast unfolding of communities in large networks. J Stat Mech: Theory Exp 2008(10):P10008

    Article 

    Google Scholar 

  • Bollen J, Mao H, Zeng X (2011) Twitter mood predicts the stock market. J Comput Sci 2(1):1–8

    Article 

    Google Scholar 

  • Boukherouaa EB, Shabsigh MG, AlAjmi K, Deodoro J, Farias A, Iskender ES, … Ravikumar R (2021) Powering the digital economy: Opportunities and risks of artificial intelligence in finance. International Monetary Fund

  • Boyack KW, Klavans R (2010) Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately? J Am Soc Inf Sci Technol 61(12):2389–2404

    Article 

    Google Scholar 

  • Breiman L (2001) Random forests. Mach Learn 45:5–32

    Article 

    Google Scholar 

  • Brummer C, Gorfine, D (2014) Fintech: Building a 21st century regulator’s toolkit. Milken Institute, 5

  • Butaru F, Chen Q, Clark B, Das S, Lo AW, Siddique A (2016) Risk and risk management in the credit card industry. J Bank Financ 72:218–239

    Article 

    Google Scholar 

  • Caniato F, Gelsomino LM, Perego A, Ronchi S (2016) Does finance solvethe supply chain financing problem? Int J Supply Chain Manag 21(5):534–549

  • Cardillo G, Chiappini H (2024) Robo-advisors: A systematic literature review. Finance Res Lett 105119

  • Černevičienė J, Kabašinskas A (2024) Explainable artificial intelligence (XAI) in finance: a systematic literature review. Artif Intell Rev 57(8):216

  • Chan SW, Chong MW (2017) Sentiment analysis in financial texts. Decis Support Syst 94:53-64

  • Charitou C, Garcez ADA, & Dragicevic S (2020) Semi-supervised GANs for fraud detection. In 2020 International Joint Conference on Neural Networks (IJCNN), IEEE p 1–8

  • Chatterjee S, Deng S, Liu J, Shan R, Jiao W (2018) Classifying facts and opinions in Twitter messages: a deep learning-based approach. J Bus Anal 1(1):29–39

  • Chen W, Yuan X (2021) Financial inclusion in China: an overview. Front Bus Res China 15:1–21

    Article 

    Google Scholar 

  • Chen X-Q, Ma C-Q, Ren Y-S, Lei Y-T, Huynh NQA, Narayan S (2023) Explainable artificial intelligence in finance: A bibliometric review. Financ Res Lett 56:104145. https://doi.org/10.1016/j.frl.2023.104145

    Article 

    Google Scholar 

  • Chokor A, Alfieri E (2021) Long and short-term impacts of regulation in the cryptocurrency market. Q Rev Econ Financ 81:157–173

    Article 

    Google Scholar 

  • Christensen CM, McDonald R, Altman EJ, Palmer JE (2018) Disruptive innovation: An intellectual history and directions for future research. J Manag Stud 55(7):1043–1078

    Article 

    Google Scholar 

  • Cockcroft S, Russell M (2018) Big data opportunities for accounting and finance practice and research. Aust Account Rev 28(3):323–333

    Article 

    Google Scholar 

  • Craja P, Kim A, Lessmann S (2020) Deep learning for detecting financial statement fraud. Decis Support Syst 139:113421

    Article 

    Google Scholar 

  • Das SR, Chen MY (2007) Yahoo! for Amazon: Sentiment extraction from small talk on the web. Manag Sci 53(9):1375–1388

    Article 

    Google Scholar 

  • Day MY, Lee CC (2016) Deep learning for financial sentiment analysis on finance news providers. In 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), IEEE p 1127–1134

  • Demirkan S, Demirkan I, McKee A (2020) Blockchain technology in the future of business cyber security and accounting. J Manag Anal 7(2):189–208

    Google Scholar 

  • Deodoro J, Gorbanyov M, Malaika M, Sedik TS (2021) Quantum computing and the financial system: spooky action at a distance?. International Monetary Fund

  • DiMaggio PJ, Powell WW (1983) The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 147–160

  • Dobre R, Bulin D, Iorgulescu M-C, Oehler-Sincai IM et al (2020) Artificial intelligence sector: The next technology bubble? A comparative analysis with dotcom based on stock market data. Roman Econ J (76):25–37

  • Donthu N, Kumar S, Mukherjee D, Pandey N, Lim WM (2021) How to conduct a bibliometric analysis: An overview and guidelines. J Bus Res 133:285–296

    Article 

    Google Scholar 

  • Doumpos M, Zopounidis C (2010) A multicriteria decision support system for bank rating. Decis support Syst 50(1):55–63

    Article 

    Google Scholar 

  • Dowling M, Lucey B (2023) ChatGPT for (finance) research: The Bananarama conjecture. Financ Res Lett 53:103662

    Article 

    Google Scholar 

  • Dubey R, Gunasekaran A, Childe SJ, Blome C, Papadopoulos T (2019) Big data and predictive analytics and manufacturing performance: Integrating institutional theory, resource-based view and big data culture. Br J Manag 30(2):341–361

    Article 

    Google Scholar 

  • Dwivedi YK, Hughes L, Ismagilova E, Aarts G, Coombs C, Crick T, Williams MD (2021) Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. Int J Inf Manag 57:101994

  • Ebers M (2023) The European Commission’s Proposal for an Artificial Intelligence Act. In Research Handbook on EU Internet Law, Edward Elgar Publishing p 271–292

  • El Hajj M, Hammoud J (2023) Unveiling the Influence of Artificial Intelligence and Machine Learning on Financial Markets: A Comprehensive Analysis of AI Applications in Trading, Risk Management, and Financial Operations. J Risk Financ Manage 16(10), 434

  • Erdélyi OJ, Goldsmith J (2018) Regulating artificial intelligence: Proposal for a global solution. In Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society p 95–101

  • Esteva A, Kuprel B, Novoa RA, Ko J, Swetter SM, Blau HM, Thrun S (2017) Dermatologist-level classification of skin cancer with deep neural networks. nature 542(7639):115–118

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Fazal A, Ahmed A, Abbas S (2024) Importance of artificial intelligence in achieving sustainable development goals through financial inclusion. Qualitative Research in Financial Markets

  • Federal Bureau of Investigation (2011) Financial Crimes Report to the Public. Retrieved Sep. 23, 2024, from https://www.fbi.gov/file-repository/stats-services-publications-financial-crimes-report-2010-2011-financial-crimes-report-2010-2011.pdf/view

  • Friedler SA, Scheidegger C, Venkatasubramanian S, Choudhary S, Hamilton EP, Roth D (2019) A comparative study of fairness-enhancing interventions in machine learning. In Proceedings of the Conference on Fairness, Accountability, and Transparency, p. 329–338

  • Frömmel M (2022) International financial markets in the digital era. In Digitalization and the Future of Financial Services: Innovation and Impact of Digital Finance. Springer, p 85–101

  • Fuller J, Jacobides MG, Reeves M (2019) The myths and realities of business ecosystems. MIT Sloan Manag Rev 60(3):1–9

    Google Scholar 

  • Gabor D, Brooks S (2020) The digital revolution in financial inclusion: international development in the fintech era. In: Material cultures of financialisation (pp. 69-82). Routledge

  • Gangwar H, Date H, Ramaswamy R (2015) Understanding determinants of cloud computing adoption using an integrated TAM-TOE model. J Enterp Inf Manag 28(1):107–130

  • Gao R, Zhang Z, Shi Z, Xu D, Zhang W, Zhu D (2021) A review of natural language processing for financial technology. In International Symposium on Artificial Intelligence and Robotics 2021, vol. 11884. SPIE, p 262–277

  • Ghoddusi H, Creamer GG, Rafizadeh N (2019) Machine learning in energyeconomics and finance: A review. Energy Econ 81:709–727

  • Glancy FH, Yadav SB (2011) A computational model for financial reporting fraud detection. Decis support Syst 50(3):595–601

    Article 

    Google Scholar 

  • Gomber P, Koch JA, Siering M (2017) Digital Finance and FinTech: current research and future research directions. J Bus Econ 87:537–580

    Google Scholar 

  • Gomber P, Kauffman RJ, Parker C, Weber BW (2018) On the fintech revolution: Interpreting the forces of innovation, disruption, and transformation in financial services. J Manag Inf Syst 35(1):220–265

    Article 

    Google Scholar 

  • Gómez JA, Arévalo J, Paredes R, Nin J (2018) End-to-end neural network architecture for fraud scoring in card payments. Pattern Recognit Lett 105:175–181

    Article 
    ADS 

    Google Scholar 

  • Goodell JW, Kumar S, Lahmar O, Pandey N (2023) A bibliometric analysis of cultural finance. Int Rev Financ Anal 85:102442

    Article 

    Google Scholar 

  • Goodell JW, Kumar S, Lim WM, Pattnaik D (2021) Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis. Journal of Behavioral and Experimental Finance, 32, 100577. Retrieved from https://linkinghub.elsevier.com/retrieve/pii/S2214635021001210https://doi.org/10.1016/j.jbef.2021.100577

  • Goodfellow I (2016) Deep learning

  • Gorton G, Metrick A (2012) Securitized banking and the run on repo. J Financ Econ 104(3):425–451

    Article 

    Google Scholar 

  • Grgurevic K, Stroughair J (2018) How gamification can attract consumers to sign up. The WealthTech Book: The FinTech Handbook for Investors, Entrepreneurs and Finance Visionaries, 65–67

  • Gunduz H, Yaslan Y, Cataltepe Z (2017) Intraday prediction of Borsa Istanbul using convolutional neural networks and feature correlations. Knowl -Based Syst 137:138–148

    Article 

    Google Scholar 

  • Gupta M, George JF (2016) Toward the development of a big data analytics capability. Inf Manag 53(8):1049–1064

    Article 

    Google Scholar 

  • Hajek P, Henriques R (2017) Mining corporate annual reports for intelligent detection of financial statement fraud–A comparative study of machine learning methods. Knowl -Based Syst 128:139–152

    Article 

    Google Scholar 

  • Hamza C, Lylia A, Nadine C, Nicolas C (2023) DEFD: Adapted Decision Tree Ensemble for Financial Fraud Detection. In International Conference on Information Technology-New Generations, Cham: Springer International Publishing p. 255–261

  • Hashem IAT, Yaqoob I, Anuar NB, Mokhtar S, Gani A, Khan SU (2015) The rise of “big data” on cloud computing: Review and open research issues. Inf Syst 47:98–115

    Article 

    Google Scholar 

  • Hernandez Aros L, Bustamante Molano LX, Gutierrez-Portela F, Moreno Hernandez JJ, Rodríguez Barrero MS (2024) Financial fraud detection through the application of machine learning techniques: a literature review. Humanities and Social Sciences. Communications 11(1):1–22

    Google Scholar 

  • Hilal W, Gadsden SA, Yawney J (2022) Financial fraud: a review of anomaly detection techniques and recent advances. Expert Syst Appl 193:116429

    Article 

    Google Scholar 

  • Hochreiter S (1997) Long Short-term Memory. Neural Computation MIT-Press

  • Horobet A, Boubaker S, Belascu L, Negreanu CC, Dinca Z (2024) Technology-driven advancements: Mapping the landscape of algorithmic trading literature. Technol Forecast Soc Change 209:123746

    Article 

    Google Scholar 

  • Hu H, Tang L, Zhang S, Wang H (2018) Predicting the direction of stock markets using optimized neural networks with Google Trends. Neurocomputing 285:188–195

  • Humpherys SL, Moffitt KC, Burns MB, Burgoon JK, Felix WF (2011) Identification of fraudulent financial statements using linguistic credibility analysis. Decis Support Syst 50(3):585–594

  • Hussain M, Papastathopoulos A (2022) Organizational readiness for digital financial innovation and financial resilience. Int J Prod Econ 243:108326

  • Huynh TLD, Hille E, Nasir MA (2020) Diversification in the age of the 4th industrial revolution: The role of artificial intelligence, green bonds and cryptocurrencies. Technol Forecast Soc Change 159:120188

    Article 

    Google Scholar 

  • Iaia V (2022) To Be, or Not to Be… Original Under Copyright Law, That Is (One of) the Main Questions Concerning AI-Produced Works. GRUR Int 71(9):793–812

    Article 

    Google Scholar 

  • Inairat M, Al-kassem, AH (2022) How Artificial Intelligence Is Promoting Financial Inclusion? A Study on Barriers of Financial Inclusion

  • Iovine A, Narducci F, Musto C, de Gemmis M, Semeraro G (2023) Virtual Customer Assistants in finance: From state of the art and practices to design guidelines. Comput Sci Rev 47:100534

  • Jagtiani J, Lemieux C (2019) The roles of alternative data and machine learning in fintech lending: evidence from the LendingClub consumer platform. Financ Manag 48(4):1009–1029

    Article 

    Google Scholar 

  • Jeong YK, Song M, Ding Y (2014) Content-based author co-citation analysis. J Informetr 8(1):197–211

    Article 

    Google Scholar 

  • Johnson K, Pasquale F, Chapman J (2019) Artificial intelligence, machine learning, and bias in finance: Toward responsible innovation. 88 Fordham Law Review. Retrieved from https://ir.lawnet.fordham.edu/flr/vol88/iss2/5

  • Kamuangu P (2024) A Review on Financial Fraud Detection using AI and Machine Learning. J Econ, Financ Account Stud 6(1):67–77

    Article 

    Google Scholar 

  • Kearns J (2023) AI’s reverberations across finance. IMF. Retrieved from https://www.imf.org/en/Publications/fandd/issues/2023/12/AI-reverberations-across-finance-Kearns#:~:text=For%20other%20uses%2C%20such%20as,%2C%20ethical%2C%20and%20compliant%20framework

  • Kingma DP, Ba LJ (2015) Adam: A method for stochastic optimization. arXiv preprint, 1-13, International Conference on Learning Representations, May 7-9, 2015, San Diego

  • Kochetkov D, Vuković D, Sadekov N, Levkiv H (2019) Smart cities and 5G networks: An emerging technological area? J Geograph Inst “Jovan Cvijić” SASA 69(3):289–295

    Article 

    Google Scholar 

  • Kohtamäki M, Parida V, Patel PC, Gebauer H (2020) The relationship between digitalization and servitization: The role of servitization in capturing the financial potential of digitalization. Technol Forecast Soc Change 151:119804

    Article 

    Google Scholar 

  • Kosala R (2017) Predicting the likelihood of dividend payment from Indonesian public companies with data mining methods. Int J Bus Inf Syst 26(2):139–150

    Google Scholar 

  • Kshetri N (2021) The role of artificial intelligence in promoting financial inclusion in developing countries, vol. 24, Taylor & Francis

  • Kumar BS, Ravi V (2016) A survey of the applications of text mining in financial domain. Knowl -Based Syst 114:128–147

    Article 

    Google Scholar 

  • Kurshan E, Shen H, Chen J (2020) Towards self-regulating AI: Challenges and opportunities of AI model governance in financial services. In Proceedings of the First ACM International Conference on AI in Finance, p. 1–8

  • Kushwaha AK, Kar AK, Dwivedi YK (2021) Applications of big data in emerging management disciplines: A literature review using text mining. Int J Inf Manag Data Insights 1(2):100017

    Google Scholar 

  • La Croce C (2023) Genai solutions help European AI market thrive in an uncertain economic environment, says IDC. IDC: The Premier Global Market Intelligence Company. Retrieved from https://www.idc.com/getdoc.jsp?containerId=prEUR251222623

  • Lakonishok J, Maberly E (1990) The weekend effect: Trading patterns of individual and institutional investors. J Financ 45(1):231–243

    Article 

    Google Scholar 

  • Le TL, Abakah EJA, Tiwari AK (2021) Time and frequency domain connectedness and spill-over among fintech, green bonds and cryptocurrencies in the age of the fourth industrial revolution. Technol Forecast Soc Change 162:120382

    Article 
    PubMed 

    Google Scholar 

  • LeBaron B, Arthur WB, Palmer R (1999) Time series properties of an artificial stock market. J Econ Dyn Control 23(9-10):1487–1516

    Article 

    Google Scholar 

  • LeBaron B (2006) Agent-based computational finance. Handbook of computational economics 2:1187–1233

  • Lee I, Shin YJ (2018) Fintech: Ecosystem, business models, investment decisions, and challenges. Bus Horiz 61(1):35–46

    Article 

    Google Scholar 

  • Lee J (2020) Access to finance for artificial intelligence regulation in the financial services industry. Eur Bus Organ Law Rev 21:731–757

    Article 

    Google Scholar 

  • Leone V, de Medeiros OR (2015) Signalling the dotcom bubble: A multiple changes in persistence approach. Q Rev Econ Financ 55:77–86

    Article 

    Google Scholar 

  • Leong C, Tan B, Xiao X, Tan FTC, Sun Y (2017) Nurturing a FinTech ecosystem: The case of a youth microloan startupin China. Int J Inf Manag 37(2):92–97

  • Li Z, Han J, Song Y (2020) On the forecasting of high‐frequency financial time series based on ARIMA model improved by deep learning. J Forecast 39(7):1081–1097

  • Lim T (2024) Environmental, social, and governance (ESG) and artificial intelligence in finance: State-of-the-art and research takeaways. Artif Intell Rev 57(4):76

    Article 

    Google Scholar 

  • Linnenluecke MK, Marrone M, Singh AK (2020) Conducting systematic literature reviews and bibliometric analyses. Aust J Manag 45(2):175–194

    Article 

    Google Scholar 

  • Lior A (2021) Insuring AI: The role of insurance in artificial intelligence regulation. Harv JL Tech 35:467

    Google Scholar 

  • Litman T (2020) Autonomous vehicle implementation predictions: Implications for transport planning. Victoria Transport Policy Institute. Available at https://www.bilbloggen.dk/wp-content/uploads/2023/04/Autonomous-Vehicle-Implementation-Predictions.pdf

  • Lopez BS, Alcaide A (2020) Blockchain, AI and IoT to improve governance, financial management and control of crisis: Case study COVID-19

  • Loughran T, McDonald B (2011) When is a liability not a liability? Textual analysis, dictionaries, and 10‐Ks. J Financ 66(1):35–65

    Article 

    Google Scholar 

  • Lu K, Wolfram D (2012) Measuring author research relatedness: A comparison of word-based, topic-based, and author co-citation approaches. J Am Soc Inf Sci Technol 63(10):1973–1986

    Article 

    Google Scholar 

  • Lui A, Lamb GW (2018) Artificial intelligence and augmented intelligence collaboration: regaining trust and confidence in the financial sector. Inf Commun Technol Law 27(3):267–283

    Article 

    Google Scholar 

  • Luo S, Xing M, Zhao J (2022) Construction of artificial intelligence application model for supply chain financial risk assessment. Sci Program 2022(1):4194576

    Google Scholar 

  • Ma X, Sha J, Wang D, Yu Y, Yang Q, Niu X (2018) Study on a prediction of P2P network loan default based on the machine learning LightGBM and XGboost algorithms according to different high dimensional data cleaning. Electron Commer Res Appl 31:24–39

    Article 

    Google Scholar 

  • Madakam S, Holmukhe RM, Jaiswa, DK (2019) The Future Digital Work Force: Robotic Process Automation (RPA). JISTEM – Journal of Information Systems and Technology Management, 16 Retrieved from https://www.scielo.br/j/jistm/a/m7cqFWJPsWSk8ZnWRN6fR5m/

  • Maiti M, Grubisic Z, Vukovic DB (2020) Dissecting tether’s nonlinear dynamics during Covid-19. J Open Innov: Technol, Mark, Complex 6(4):161

    Article 

    Google Scholar 

  • Maiti M, Vukovic DB, Frömmel M (2023) Quantifying the asymmetric information flow between Bitcoin prices and electricity consumption. Financ Res Lett 57:104163

    Article 

    Google Scholar 

  • Malo P, Sinha A, Korhonen P, Wallenius J, Takala P (2014) Good debt or bad debt: Detecting semantic orientations in economic texts. J Assoc Inf Sci Technol 65(4):782–796

    Article 

    Google Scholar 

  • Max R, Kriebitz A, Von Websky C (2021) Ethical considerations about the implications of artificial intelligence in finance. In: San-Jose L, Retolaza J, van Liedekerke L (eds) Handbook on ethics in finance (pp. 577–592) Springer, Cham

  • Meyer JW, Rowan B (1977) Institutionalized organizations: Formal structure as myth and ceremony. Am J Sociol 83(2):340–363

    Article 

    Google Scholar 

  • Mhlanga D (2020) Industry 4.0 in finance: the impact of artificial intelligence (ai) on digital financial inclusion. Int J Financ Stud 8(3):45

    Article 
    MathSciNet 

    Google Scholar 

  • Montevechi AA, de Carvalho Miranda R, Medeiros AL, Montevechi JAB (2024) Advancing credit risk modelling with Machine Learning: A comprehensive review of the state-of-the-art. Eng Appl Artif Intell 137:109082

    Article 

    Google Scholar 

  • More D, Basu P (2013) Challenges of supply chain finance: A detailed study and a hierarchical model based on the experiences of an Indian firm. Bus Process Manag J 19(4):624–647

  • Nassirtoussi AK, Aghabozorgi S, Wah TY, Ngo DCL (2015) Text mining of news-headlines for FOREX marketprediction: A Multi-layer Dimension Reduction Algorithm with semantics and sentiment. Expert Syst Appl 42(1):306–324

  • Netzer O, Lemaire A, Herzenstein M (2019) When words sweat: Identifying signals for loan default in the text of loan applications. J Mark Res 56(6):960–980

    Article 

    Google Scholar 

  • Newman ME, Girvan M (2004) Finding and evaluating community structure in networks. Phys Rev E 69(2):026113

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Ngai EW, Hu Y, Wong YH, Chen Y, Sun X (2011) The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature. Decis support Syst 50(3):559–569

    Article 

    Google Scholar 

  • Olawumi TO, Saka AB, Chan DW, Jayasena NS (2021) 11 scientometric review and analysis. Secondary research methods in the built environment, 147

  • Oliveira N, Cortez P, Areal N (2016) Stock market sentiment lexicon acquisition using microblogging data and statistical measures. Decis Support Syst 85:62–73

    Article 

    Google Scholar 

  • Oliveira B, Leal CC (2024) Leading the way toward a sustainable future: the role of sustainable finance and environmental, social, and governance investing. Circular Economy Manufact 53–82

  • Osterrieder J, GPT C (2023) A primer on deep reinforcement learning for finance. Available at SSRN 4316650

  • Palmié M, Wincent J, Parida V, Caglar U (2020) The evolution of the financial technology ecosystem: An introduction and agenda for future research on disruptive innovations in ecosystems. Technol Forecast Soc Change 151:119779

    Article 

    Google Scholar 

  • Paltrinieri A, Hassan MK, Bahoo S, Khan A (2023) A bibliometric review of sukuk literature. Int Rev Econ Financ 86:897–918

    Article 

    Google Scholar 

  • Pan WT (2012) A new fruit fly optimization algorithm: taking the financial distress model as an example. Knowl-Based Syst 26:69–74

    Article 

    Google Scholar 

  • Park CY, Mercado Jr R (2018) Financial inclusion, poverty, and income inequality. Singap Econ Rev 63(01):185–206

    Article 

    Google Scholar 

  • Pattnaik D, Ray S, Raman R (2024) Applications of artificial intelligence and machine learning in the financial services industry: A bibliometric review. Heliyon

  • Paul J, Xu Q, Fei S, Veeravalli B, Aung KMM (2019) Practically realisable anonymisation of bitcoin transactions with improved efficiency of the zerocoin protocol. In Advances in Information and Communication Networks: Proceedings of the 2018 Future of Information and Communication Conference (FICC), vol. 2. Springer International Publishing, p 108–130

  • Paula EL, Ladeira M, Carvalho RN, Marzagão T (2016) Deep learning anomaly detection as support fraud investigation in brazilian exports and anti-money laundering. In 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA), IEEE, p. 954–960

  • Peters BG (2022) Institutional theory. In Handbook on theories of governance, Edward Elgar Publishing, p 323–335

  • Philippon T (2019) On fintech and financial inclusion (No. w26330). Natl Bureau Econ Research, Working Paper 26330. ink: https://www.nber.org/system/files/working_papers/w26330/w26330.pdf

  • Pisoni G, Díaz-Rodríguez N (2023) Responsible and human centric AI-based insurance advisors. Inf Process Manag 60(3):103273

    Article 

    Google Scholar 

  • Pithadia HJ (2021) Algorithmic Regulation using AI and Blockchain Technology (Unpublished doctoral dissertation)

  • Pizzi S, Corbo L, Caputo A (2021) Fintech and SMEs sustainable business models: Reflections and considerations for a circular economy. J Clean Prod 281:125217

    Article 

    Google Scholar 

  • Raman R, Pattnaik D, Hughes L, Nedungadi P (2024) Unveiling the dynamics of AI applications: A review of reviews using scientometrics and BERTopic modeling. J Innov Knowl 9(3):100517

    Article 

    Google Scholar 

  • Ranković M, Gurgu E, Martins OMD, Vukasović’ M (2023) Artificial Intelligence and the Evolution of Finance: Opportunities, Challenges and Ethical Considerations. EdTech Journal. Retrieved from https://doi.org/10.18485/edtech.2023.3.1.2

  • Ravisankar P, Ravi V, Rao GR, Bose I (2011) Detection of financial statement fraud and feature selection using data mining techniques. Decis support Syst 50(2):491–500

    Article 

    Google Scholar 

  • Razzaq A, Yang X (2023) Digital finance and green growth in China: Appraising inclusive digital finance using web crawler technology and big data. Technol Forecast Soc Change 188:122262

    Article 

    Google Scholar 

  • Rtayli N, Enneya N (2020) Enhanced credit card fraud detection based on SVM-recursive feature elimination and hyper-parameters optimization. J Inf Security Appl 55:102596

    Google Scholar 

  • Salchenberger LM, Cinar EM, Lash NA (1992) Neural networks: A new tool for predicting thrift failures. Decis Sci 23(4):899–916

  • Schniederjans D, Cao ES, Schniederjans M (2013) Enhancing financial performance with social media: An impression management perspective. Decis Support Syst 55(4):911–918

    Article 

    Google Scholar 

  • Scott C (2012) Regulating everything: From mega-to meta-regulation. Administration 60(1):61–89

    Google Scholar 

  • Serrano-Cinca C, Gutiérrez-Nieto B (2016) The use of profit scoring as an alternative to credit scoring systems in peer-to-peer (P2P) lending. Decis Support Syst 89:113–122

    Article 

    Google Scholar 

  • Shirazi F, Mohammadi M (2019) A big data analytics model for customer churn prediction in the retiree segment. Int J Inf Manag 48:238–253

    Article 

    Google Scholar 

  • Shiyyab FS, Alzoubi AB, Obidat QM, Alshurafat H (2023) The impact of artificial intelligence disclosure on financial performance. Int J Financ Stud 11(3):115

    Article 

    Google Scholar 

  • Smuha NA (2019) The EU approach to ethics guidelines for trustworthy artificial intelligence. Comput Law Rev Int 20(4):97–106

    Article 

    Google Scholar 

  • Soni G, Kumar S, Mahto RV, Mangla SK, Mittal ML, Lim WM (2022) A decision-making framework for Industry 4.0 technology implementation: The case of FinTech and sustainable supply chain finance for SMEs. Technol Forecast Soc Change 180:121686

    Article 

    Google Scholar 

  • Su C, Flew T (2021) The rise of Baidu, Alibaba and Tencent (BAT) and their role in China’s Belt and Road Initiative (BRI). Glob Media Commun 17(1):67–86

    Article 

    Google Scholar 

  • Tao R, Su C-W, Xiao Y, Dai K, Khalid F (2021) Robo advisors, algorithmic trading and investment management: Wonders of fourth industrial revolution in financial markets. Technol Forecast Social Change 163:120421

  • Truby J (2020) Governing artificial intelligence to benefit the UN sustainable development goals. Sustain Dev 28(4):946–959

    Article 

    Google Scholar 

  • Tsantekidis A, Passalis N, Tefas A, Kanniainen J, Gabbouj M, Iosifidis A (2017) Forecasting stock prices from the limit order book using convolutional neural networks. In 2017 IEEE 19th Conference on Business Informatics (CBI), vol. 1, IEEE, p 7–12

  • Tyagi AK, Tiwari S (2024) The future of artificial intelligence in blockchain applications. In Machine learning algorithms using scikit and tensorflow environments, IGI Global, p 346–373

  • Uthayakumar J, Metawa N, Shankar K, Lakshmanaprabu SK (2020) Financial crisis prediction model using ant colony optimization. Int J Inf Manag 50:538–556

    Article 

    Google Scholar 

  • Vahidov R, He X (2009) Situated DSS for personal finance management: Design and evaluation. Inf Manag 46(8):453–462

    Article 

    Google Scholar 

  • Van Eck N, Waltman L (2010) Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84(2):523–538

    Article 
    PubMed 

    Google Scholar 

  • Veale M, Zuiderveen Borgesius F (2021) Demystifying the Draft EU Artificial Intelligence Act—Analysing the good, the bad, and the unclear elements of the proposed approach. Comput Law Rev Int 22(4):97–112

    Article 

    Google Scholar 

  • Vukovic D, Lapshina KA, Maiti M (2019) European Monetary Union bond market dynamics: Pre & post crisis. Res Int Bus Financ 50:369–380

    Article 

    Google Scholar 

  • Vyklyuk Y, Vukovic D, Jovanovic A (2013) Forex prediction with neural network: USD/EUR currency pair. Actual Problems Econ (10):261–273

  • Waltman L, Boyack KW, Colavizza G, van Eck NJ (2020) A principled methodology for comparing relatedness measures for clustering publications. Quant Sci Stud 1(2):691–713

    Google Scholar 

  • Wang Y, Kim DK, Jeong D (2020) A survey of the application of blockchain in multiple fields of financial services. J Inf Process Syst 16(4):935–958

    Google Scholar 

  • Wang C, Wang Y, Ye Z, Yan L, Cai W, Pan S (2018) Credit card fraud detection based on whale algorithm optimized BP neural network. In 2018 13th International Conference on Computer Science & Education (ICCSE), IEEE, p 1–4

  • Wang Q, Kang K, Zhang Z, Cao D (2021). Application of LSTM and Conv1D LSTM network in stock forecasting model. Bilingual Publishing Co

  • West J, Bhattacharya M (2016) Intelligent financial fraud detection: a comprehensive review. Comput Secur 57:47–66

    Article 

    Google Scholar 

  • Woerner S, Egger DJ (2019) Quantum risk analysis. npj Quantum Inf 5(1):1–8

    Article 

    Google Scholar 

  • Wong BK, Selvi Y (1998) Neural network applications in finance: A review and analysis of literature (1990–1996). Inf Manag 34(3):129–139

    Article 

    Google Scholar 

  • Xing FZ, Cambria E, Welsch RE (2018) Natural language based financial forecasting: a survey. Artif Intell Rev 50(1):49–73

    Article 

    Google Scholar 

  • Yadav Y, & Brummer C (2019). Fintech and the innovation trilemma

  • Yang S, Yuan Q, Dong J et al. (2020) Are scientometrics, informetrics, and bibliometrics different? Data Sci Informetr 1(01):50

    Google Scholar 

  • Yang T, Zhang X (2022) Fintech adoption and financial inclusion: Evidence from household consumption in China. J Bank Financ 145:106668

    Article 

    Google Scholar 

  • Yuan S, Musibau HO, Genç SY, Shaheen R, Ameen A, Tan Z (2021) Digitalization of economy is the key factor behind fourth industrial revolution: How G7 countries are overcoming with the financing issues? Technol Forecast Soc Change 165:120533

    Article 

    Google Scholar 

  • Zavolokina L, Dolata M, Schwabe G (2016) The FinTech phenomenon: antecedents of financial innovation perceived by the popular press. Financ Innov 2:1–16

  • Zetzsche DA, Annunziata F, Arner DW, Buckley RP (2021) The Markets in Crypto-Assets regulation (MiCA) and the EU digital finance strategy. Cap Mark Law J 16(2):203–225

    Article 

    Google Scholar 

  • Zhang G, Hu MY (1998) Neural network forecasting of the British pound/USdollar exchange rate. Omega 26(4):495-506

  • Zhang J, Zhong S, Wang T, Chao HC, Wang J (2020) Blockchain-based systems and applications: a survey. J Internet Technol 21(1):1–14

    Google Scholar 

  • Zhang L, Pentina I, Fan Y (2021) Who do you choose? Comparing perceptions of human vs robo-advisor in the context of financial services. J Serv Mark 35(5):634–646

    Article 

    Google Scholar 

  • Zhu Y, Zhou L, Xie C, Wang GJ, Nguyen TV (2019) Forecasting SMEs’ credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach. Int J Prod Econ 211:22–33

    Article 

    Google Scholar 

  • Zupic I, Cater T (2015) Bibliometric methods in management and organization. Organ Res Methods 18(3):429–472

    Article 

    Google Scholar 

  • link

    Leave a Reply

    Your email address will not be published. Required fields are marked *