International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 3 (May-June 2025) Submit your research before last 3 days of June to publish your research paper in the issue of May-June.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 7 Issue 3
May-June 2025

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Blockchain-Integrated MLOps for Financial Modeling

Author(s) Ms. Arya Kishor Chunne, Mr. Laxmikant Shashikant Deshpande
Country India
Abstract This research explores the transformative potential of integrating blockchain technology into Machine Learning Operations (MLOps) for financial modeling. Current MLOps pipelines face significant challenges, including centralized storage vulnerabilities and opaque decision-making processes, which compromise trust and compliance. To address these issues, this study proposes a blockchain-based MLOps framework that leverages decentralized storage, immutable ledgers, and smart contracts to enhance security, transparency, and regulatory adherence while mitigating operational risks.
Blockchain’s immutable ledger ensures that data and model outputs are tamper-proof, reducing the risk of data breaches and model manipulation. This is particularly crucial in financial services where data integrity is paramount. The decentralized architecture provides a transparent record of all transactions and model decisions, simplifying audits and regulatory reporting. This transparency fosters trust among stakeholders and enhances accountability. Additionally, smart contracts automate compliance checks, ensuring real-time adherence to evolving financial regulations. This reduces manual errors and streamlines regulatory reporting processes.
Despite these benefits, challenges persist. Blockchain networks struggle with large-scale ML workloads, necessitating more efficient consensus mechanisms to reduce latency and energy consumption. Moreover, decentralized architectures complicate liability assignment, requiring clearer regulatory guidelines to ensure compliance and legal clarity. This research underscores the potential of blockchain-ML Ops integration to revolutionize financial modeling by ensuring trustworthy and accountable AI systems. By addressing current limitations and exploring future developments, financial institutions can harness this synergy to enhance security, transparency, and compliance in machine learning workflows. The study provides a comprehensive analysis of blockchain’s role in transforming MLOps, offering insights into how financial institutions can leverage this technology to achieve more reliable and compliant analytics systems.
Keywords Blockchain, MLOps, Financial Modeling, Smart Contracts, Decentralized Storage, Compliance, Data Integrity
Field Computer Applications
Published In Volume 7, Issue 2, March-April 2025
Published On 2025-04-30
DOI https://doi.org/10.36948/ijfmr.2025.v07i02.42048
Short DOI https://doi.org/g9g738
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 7 Isu 3Cover Page Vol 7 Isu 2Cover Page Vol 7 Isu 1

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com