American Journal of Advanced Multidisciplinary Research and Innovation

E-ISSN: XXXX-XXXX   •   Impact Factor: -

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

Call for Paper Volume 8, Issue 5 (September-October 2026) Submit your research before last 3 days of October to publish your research paper in the issue of September-October.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 8 Issue 5
September-October 2026

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

AI-Powered Financial Analytics for Risk Management and Investment Decision-Making

Author(s) Hari Balakrishnan
Country United States
Abstract The rapid development of Artificial Intelligence (AI), Machine Learning (ML), big data analytics, and computational finance is transforming financial risk management and investment decision-making. Traditional financial analysis often relies on historical information, predefined statistical models, and human judgment, whereas AI-powered financial analytics can process large and complex datasets in real time and identify nonlinear patterns that may be difficult to detect through conventional approaches. This study examines the application of AI-powered financial analytics in risk identification, credit risk assessment, fraud detection, market forecasting, portfolio optimisation, investment analysis, and decision support. A qualitative and analytical research methodology based on secondary literature and financial technology research is adopted. The analysis identifies predictive analytics, machine learning, natural language processing, deep learning, and reinforcement learning as important technologies supporting modern financial decision-making. The study indicates that AI can improve the speed of analysis, enhance risk monitoring, automate repetitive processes, and provide data-driven insights for investment decisions. However, challenges involving model explainability, data quality, algorithmic bias, cybersecurity, model risk, regulatory compliance, and excessive dependence on automated predictions remain significant. The study concludes that AI should function as an augmentation mechanism for financial professionals rather than an unrestricted replacement for human judgment. Effective implementation requires strong governance, high-quality data, continuous model validation, explainability, human oversight, and robust risk controls.
Keywords Artificial Intelligence, Financial Analytics, Risk Management, Investment Decision-Making, Machine Learning, Portfolio Management, FinTech, Predictive Analytics.
Field Engineering
Published In Volume 4, Issue 2, March-April 2022
Published On 2022-04-29
View / Download PDF File

Share this



E-ISSN XXXX-XXXX
CrossRef

CrossRef DOI prefix of AJAMRI is 10.00000/AJAMRI

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form

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 AJAMRI
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 +1-872-302-3851 editor@ajamri.com