Citation:

Surya Veera Brahmaji Rao Sunnam , 2023. "A Comprehensive Survey of Compliance-Aware AI Infrastructure in Financial Big Data Ecosystems ", ESP Journal of Engineering & Technology Advancements  3(4): 198-208.

Abstract:

The rapid emergence of financial big data landscapes and increased utilization of advanced digital technologies have transformed financial regulatory compliance radically. Traditional, paper-based managing compliance practices are no longer appropriate to react to the quantity, frequency, and sophisticated Ness of modern financial dealings and are carrying increasing expenses, protracted risk recognition, and an expanded regulatory risk. It is this paper that discusses the significance of compliance and how compliance aware artificial intelligence (AI) infrastructure can address the flaws of conventional compliance systems. It analyzes some of the key problems in standard compliance in a highly-populated data-driven financial world, and identifies the strategic advantages of artificial intelligence-based compliance systems, including real-time monitoring, predictive risk processing, scale, and reduced human error. The regulatory frameworks driving AI-based compliance are also discussed in the paper and comparative research of traditional and AI-based compliance systems is made to present their contribution and limitations respectively. The synthesis of existing studies, regulatory approaches, as well as practical implementation demonstrates that AI-mediated compliance, in addition to increasing regulatory compliance, contributes to increasing financial resilience, operational efficiency, and trust among institutions, all of which the paper presents. The results highlight the significance of implementing AI as a component of compliance strategies to enable sustainable, transparent, and agile financial systems in a continuously changing regulatory environment.

References:

[1] L. McMillan and L. Varga, “A review of the use of artificial intelligence methods in infrastructure systems,” Engineering Applications of Artificial Intelligence. 2022. doi: 10.1016/j.engappai.2022.105472.

[2] A. Parupalli, “The Evolution of Financial Decision Support Systems : From BI Dashboards to Predictive Analytics,” KOS J. Bus. Manag., vol. 1, no. 1, pp. 1–8, 2023.

[3] F. S. Shiyyab, A. B. Alzoubi, Q. M. Obidat, and H. Alshurafat, “The Impact of Artificial Intelligence Disclosure on Financial Performance,” Int. J. Financ. Stud., vol. 11, no. 3, p. 115, Sep. 2023, doi: 10.3390/ijfs11030115.

[4] V. Verma, “Deep Learning-Based Fraud Detection in Financial Transactions: A Case Study Using Real-Time Data Streams,” ESP J. Eng. Technol. Adv., vol. 3, no. 4, pp. 149–157, 2023, doi: 10.56472/25832646/JETA-V3I8P117.

[5] H. Shahin, “Pilot Study on AI Applications in Preventing Financial Fraud in Jamshedpur’s Banking and Fintech Ecosystem,” J. Emerg. Technol. Innov. Res., vol. 10, no. 12, 2023.

[6] J. Truby, R. Brown, and A. Dahdal, “Banking on AI: mandating a proactive approach to AI regulation in the financial sector,” Law Financ. Mark. Rev., vol. 14, no. 2, pp. 110–120, Apr. 2020, doi: 10.1080/17521440.2020.1760454.

[7] H. H. H. Aldboush and M. Ferdous, “Building Trust in Fintech: An Analysis of Ethical and Privacy Considerations in the Intersection of Big Data, AI, and Customer Trust,” Int. J. Financ. Stud., vol. 11, no. 3, 2023, doi: 10.3390/ijfs11030090.

[8] L. Grassi and D. Lanfranchi, “RegTech in public and private sectors: the nexus between data, technology and regulation,” J. Ind. Bus. Econ., vol. 49, no. 3, pp. 441–479, Sep. 2022, doi: 10.1007/s40812-022-00226-0.

[9] Bisola Beatrice Oguejiofor et al., “A REVIEW ON DATA-DRIVEN REGULATORY COMPLIANCE IN NIGERIA,” Int. J. Appl. Res. Soc. Sci., vol. 5, no. 8, pp. 231–243, Oct. 2023, doi: 10.51594/ijarss.v5i8.571.

[10] X. Chao, Q. Ran, J. Chen, T. Li, Q. Qian, and D. Ergu, “Regulatory technology (Reg-Tech) in financial stability supervision: Taxonomy, key methods, applications and future directions,” International Review of Financial Analysis. 2022. doi: 10.1016/j.irfa.2022.102023.

[11] J. Li, A. Maiti, and J. Fei, “Features and Scope of Regulatory Technologies: Challenges and Opportunities with Industrial Internet of Things,” Future Internet. 2023. doi: 10.3390/fi15080256.

[12] H. E and B. V, “RegTech and Financial Compliance in India: Innovations, Challenges, and Prospects,” J. Emerg. Technol. Innov. Res., vol. 10, no. 12, 2023.

[13] C. C. Cantarelli, B. Flyvbjerg, E. J. E. Molin, and B. van Wee, “Cost Overruns in Large-scale Transportation Infrastructure Projects: Explanations and Their Theoretical Embeddedness,” Eur. J. Transp. Infrastruct. Res., vol. 10, no. 1, pp. 5–18, 2010, doi: 10.18757/EJTIR.2010.10.1.2864.

[14] C. Patel, “A Review of Multi-Channel CRM Strategies Using Big Data and Cloud Integration,” Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol., vol. 8, no. 1, pp. 577–588, 2022.

[15] S. Mishra, “Exploring the Impact of AI-Based Cyber Security Financial Sector Management,” Appl. Sci., vol. 13, no. 10, p. 5875, May 2023, doi: 10.3390/app13105875.

[16] M. Hassan, L. A.-R. Aziz, and Y. Andriansyah, “The Role Artificial Intelligence in Modern Banking: An Exploration of AI-Driven Approaches for Enhanced Fraud Prevention, Risk Management, and Regulatory Compliance,” Rev. Contemp. Bus. Anal., vol. 6, no. 1, pp. 110–132, 2023.

[17] H. H. Al-Baity, “The Artificial Intelligence Revolution in Digital Finance in Saudi Arabia: A Comprehensive Review and Proposed Framework,” Sustainability, vol. 15, no. 18, p. 13725, Sep. 2023, doi: 10.3390/su151813725.

[18] J. K. Hentzen, A. Hoffmann, R. Dolan, and E. Pala, “Artificial intelligence in customer-facing financial services: a systematic literature review and agenda for future research,” Int. J. Bank Mark., vol. 40, no. 6, pp. 1299–1336, Sep. 2022, doi: 10.1108/IJBM-09-2021-0417.

[19] H. U. Khan et al., “Transforming the Capabilities of Artificial Intelligence in GCC Financial Sector: A Systematic Literature Review,” Wirel. Commun. Mob. Comput., vol. 2022, no. 1, Jan. 2022, doi: 10.1155/2022/8725767.

[20] Y. Han, J. Chen, M. Dou, J. Wang, and K. Feng, “The Impact of Artificial Intelligence on the Financial Services Industry,” Acad. J. Manag. Soc. Sci., vol. 2, no. 3, pp. 83–85, May 2023, doi: 10.54097/ajmss.v2i3.8741.

[21] A. Fazal, A. Ahmed, and S. Nisar, “Artificial Intelligence and Financial Inclusion: A Systematic Literature Review,” J. Asian Dev. Stud., vol. 12, no. 3, pp. 158–168, 2023.

[22] V. Shah, “Managing Security and Privacy in Cloud Frameworks: A Risk with Compliance Perspective for Enterprises,” Int. J. Curr. Eng. Technol., vol. 12, no. 06, pp. 1–13, 2022, doi: 10.14741/ijcet/v.12.6.16.

[23] N. Haefner, V. Parida, O. Gassmann, and J. Wincent, “Implementing and scaling artificial intelligence: A review, framework, and research agenda,” Technol. Forecast. Soc. Change, vol. 197, p. 122878, Dec. 2023, doi: 10.1016/j.techfore.2023.122878.

[24] J. Schneider, R. Abraham, C. Meske, and J. Vom Brocke, “Artificial Intelligence Governance For Businesses,” Inf. Syst. Manag., vol. 40, no. 3, pp. 229–249, Jul. 2023, doi: 10.1080/10580530.2022.2085825.

[25] P. G. R. de Almeida, C. D. dos Santos, and J. S. Farias, “Artificial Intelligence Regulation: a framework for governance,” Ethics Inf. Technol., vol. 23, no. 3, pp. 505–525, Sep. 2021, doi: 10.1007/s10676-021-09593-z.

[26] A. Lukács and S. Váradi, “GDPR-compliant AI-based automated decision-making in the world of work,” Comput. Law Secur. Rev., vol. 50, p. 105848, Sep. 2023, doi: 10.1016/j.clsr.2023.105848.

[27] A. Yadava, “Ethical and regulatory challenges of AI adoption in the financial services sector: A global perspective,” Int. J. Sci. Res. Arch., vol. 10, no. 1, pp. 1222–1235, Oct. 2023, doi: 10.30574/ijsra.2023.10.1.0826.

[28] E. Vyhmeister, G. Gonzalez-Castane, and P.-O. Östbergy, “Risk as a driver for AI framework development on manufacturing,” AI Ethics, vol. 3, no. 1, pp. 155–174, Feb. 2023, doi: 10.1007/s43681-022-00159-3.

[29] M. Viljanen and H. Parviainen, “AI Applications and Regulation: Mapping the Regulatory Strata,” Front. Comput. Sci., vol. 3, Jan. 2022, doi: 10.3389/fcomp.2021.779957.

[30] R. Tillu, M. Muthusubramanian, and V. Periyasamy, “Transforming Regulatory Reporting with AI/ML: Strategies for Compliance and Efficiency,” J. Knowl. Learn. Sci. Technol. ISSN 2959-6386, vol. 2, no. 1, pp. 145–157, Jun. 2023, doi: 10.60087/jklst.vol2.n1.p157.

[31] S. T. Nuka, “The Role of AI Driven Clinical Research in Medical Device Development: A Data Driven Approach to Regulatory Compliance and Quality Assurance,” Glob. J. Med. Case Reports, vol. 2, no. 1, pp. 47–57, Dec. 2022, doi: 10.31586/gjmcr.2022.1275.

[32] E. Vyhmeister, G. Gonzalez-Castane, and P. Östbergy, “Risk as a driver for AI framework development on manufacturing,” AI Ethics, vol. 3, no. 1, pp. 155–174, Feb. 2023, doi: 10.1007/s43681-022-00159-3.

[33] Y. Macha, “Cloud-Based CRM for Healthcare Data Management: A Review of HIPAA Compliance and Validation Rules,” TIJER - Int. Res. J., vol. 10, no. 11, pp. 1–6, 2023.

[34] M. Mubarkoot, J. Altmann, M. Rasti-Barzoki, B. Egger, and H. Lee, “Software Compliance Requirements, Factors, and Policies: A Systematic Literature Review,” Comput. Secur., vol. 124, p. 102985, Jan. 2023, doi: 10.1016/j.cose.2022.102985.

[35] J. Blaze, “A Comparison of Current Regulatory Frameworks for Nutraceuticals in Australia, Canada, Japan, and the United States.,” Inov. Pharm., vol. 12, no. 2, p. 8, Apr. 2021, doi: 10.24926/iip.v12i2.3694.

[36] L. Robb, T. Candy, and F. Deane, “Regulatory overlap: A systematic quantitative literature review,” Regul. Gov., vol. 17, no. 4, pp. 1131–1151, Oct. 2023, doi: 10.1111/rego.12504.

[37] V. Bitkuri, R. Kendyala, J. Kurma, J. V. Mamidala, S. J. Enokkaren, and A. Attipalli, “Systematic Review of Artificial Intelligence Techniques for Enhancing Financial Reporting and Regulatory Compliance,” Int. J. Emerg. Trends Comput. Sci. Inf. Technol., vol. 2, no. 4, 2021.

[38] J. Singireddy, A. Dodda, J. K. R. Burugulla, S. Paleti, and K. Challa, “Innovative Financial Technologies: Strengthening Compliance, Secure Transactions, and Intelligent Advisory Systems Through AI-Driven Automation and Scalable Data Architectures,” Univers. J. Financ. Econ., vol. 1, no. 1, pp. 123–143, Dec. 2021, doi: 10.31586/ujfe.2021.1298.

[39] J. Lee, “Access to Finance for Artificial Intelligence Regulation in the Financial Services Industry,” Eur. Bus. Organ. Law Rev., vol. 21, no. 4, pp. 731–757, Dec. 2020, doi: 10.1007/s40804-020-00200-0.

[40] L. D. Wall, “Some financial regulatory implications of artificial intelligence,” J. Econ. Bus., vol. 100, pp. 55–63, Nov. 2018, doi: 10.1016/j.jeconbus.2018.05.003.

Keywords:

Artificial Intelligence, Regulatory Compliance, Financial Big Data, Risk Management, Financial Stability.