IDEAS home Printed from https://ideas.repec.org/a/das/njaigs/v2y2024i1p71-90id98.html
   My bibliography  Save this article

Revolutionizing Regulatory Reporting through AI/ML: Approaches for Enhanced Compliance and Efficiency

Author

Listed:
  • Harish Padmanaban

Abstract

ISSN: 3006-4023 (Online), Vol. 2, Issue 1Journal of Artificial Intelligence General Science (JAIGS)journal homepage: https://ojs.boulibrary.com/index.php/JAIGSRevolutionizing Regulatory Reporting through AI/ML: Approaches forEnhanced Compliance and EfficiencyHarish Padmanaban Ph.D.Site Reliability Engineering lead and Independent Researcher.AbstractIn the intricate regulatory landscape of today, financial institutions encounter formidable hurdles in meeting reportingmandates while upholding operational efficacy. This study delves into the transformative capacity of ArtificialIntelligence (AI) and Machine Learning (ML) technologies in refining regulatory reporting procedures. Throughharnessing AI/ML, entities can streamline data aggregation, analysis, and submission, thus fostering enhancedcompliance and operational efficiency. Key strategies for integrating AI/ML into regulatory reporting frameworksare discussed, encompassing data standardization, predictive analytics, anomaly detection, and automation.Furthermore, the paper explores the advantages, obstacles, and optimal approaches associated with deploying AI/MLsolutions in regulatory reporting. Drawing on real-world illustrations and case studies, this study offers insights intohow AI/ML technologies can redefine regulatory reporting practices, empowering financial institutions to adeptlynavigate regulatory intricacies while optimizing resource allocation and decision-making processes.

Suggested Citation

  • Harish Padmanaban, 2024. "Revolutionizing Regulatory Reporting through AI/ML: Approaches for Enhanced Compliance and Efficiency," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 2(1), pages 71-90.
  • Handle: RePEc:das:njaigs:v:2:y:2024:i:1:p:71-90:id:98
    as

    Download full text from publisher

    File URL: https://newjaigs.com/index.php/JAIGS/article/view/98
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hassan Rehan, 2024. "AI-Driven Cloud Security: The Future of Safeguarding Sensitive Data in the Digital Age," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 1(1), pages 132-151.
    2. José Gabriel Carrasco Ramírez, 2024. "Constructing Executing and Overcoming Challenges in Distributed AI Systems: A Study of Federated Learning Framework," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 3(1), pages 197-216.
    3. Sohana Akter, 2024. "Harmonizing Compliance: Coordinating Automated Verification Processes within Cloud-based AI/ML Workflows," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 3(1), pages 292-302.
    4. Jeff Shuford, 2024. "Examining Ethical Aspects of AI: Addressing Bias and Equity in the Discipline," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 3(1), pages 262-280.
    5. FNU Jimmy, 2024. "Cyber security Vulnerabilities and Remediation Through Cloud Security Tools," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 2(1), pages 129-171.
    6. Amaresh Kumar, 2024. "Cybersecurity Threat Detection using Machine Learning and Network Analysis," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 1(1), pages 124-131.
    7. Md. Mafiqul Islam, 2024. "Exploring the Impact of Artificial Intelligence in Healthcare," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 2(1), pages 228-238.
    8. José Gabriel Carrasco Ramírez & Md.Mafiqul Islam, 2024. "Navigating the Terrain: Scaling Challenges and Opportunities in AI/ML Infrastructure," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 2(1), pages 241-250.
    9. Imran Khan, 2024. "Real-Time RIC/RAN Intelligent Controller: A Software Component for Open RAN Architecture," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 2(1), pages 207-216.
    10. Damián Tuset Varela, 2024. "Navigating Cyber Diplomacy in the Governance of Emerging AI Technologies: Lessons from Transatlantic Cooperation," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 2(1), pages 172-180.
    11. Muhammad Umair, 2024. "Protecting Data Access Liabilities in Cloud Computing," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 3(1), pages 323-340.
    12. Samadrita Ghosh, 2024. "Ensuring Compliance Integrity in AI ML Cloud Environments: The Role of Data Guardianship," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 3(1), pages 303-322.
    13. Harish Padmanaban, 2024. "Privacy-Preserving Architectures for AI/ML Applications: Methods, Balances, and Illustrations," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 3(1), pages 235-245.
    14. Hassan Rehan, 2024. "Revolutionizing America's Cloud Computing the Pivotal Role of AI in Driving Innovation and Security," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 2(1), pages 239-240.
    15. Md. Rashed Khan, 2024. "Role of AI in Enhancing Accessibility for People with Disabilities," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 3(1), pages 281-291.
    16. Harish Padmanaban, 2024. "Machine Learning Algorithms Scaling on Large-Scale Data Infrastructure," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 3(1), pages 171-196.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:das:njaigs:v:2:y:2024:i:1:p:71-90:id:98. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Open Knowledge (email available below). General contact details of provider: https://newjaigs.com/index.php/JAIGS/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.