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

Artificial Intelligence Applications in Financial Risk Prediction and Fraud Detection

Author(s) Ruzena Bajcsy
Country United States
Abstract The rapid digitalisation of the global financial sector has transformed banking, insurance, investment management, digital payments, and financial services through the adoption of Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Big Data Analytics, Blockchain Technology, Cloud Computing, Internet of Things (IoT), Natural Language Processing (NLP), Explainable Artificial Intelligence (XAI), Graph Neural Networks (GNNs), Federated Learning, Robotic Process Automation (RPA), Financial Technology (FinTech), Behavioural Analytics, and Predictive Analytics. These intelligent technologies enable financial institutions to improve credit risk assessment, detect fraudulent transactions, predict financial distress, optimise investment decisions, strengthen regulatory compliance, and enhance customer trust.
This study presents a comprehensive analysis of Artificial Intelligence Applications in Financial Risk Prediction and Fraud Detection. A qualitative analytical research methodology based on secondary data is employed to examine AI-based financial risk models, fraud detection techniques, intelligent decision-support systems, implementation challenges, and future technological developments. The research investigates how AI enhances financial security, operational efficiency, customer experience, and regulatory compliance across banking, insurance, capital markets, digital payment systems, and FinTech ecosystems.
The findings indicate that AI significantly improves credit scoring, anti-money laundering (AML), fraud detection, customer authentication, portfolio risk management, algorithmic trading, and financial forecasting. Machine learning algorithms accurately identify suspicious transaction patterns, while deep learning models detect complex fraud networks that traditional rule-based systems often fail to recognise. Explainable AI improves transparency in automated financial decisions, and blockchain technology enhances transaction integrity and secure identity management. Furthermore, AI-powered predictive analytics enables early identification of credit defaults, market volatility, liquidity risks, and operational threats.
Despite these advantages, challenges remain concerning data privacy, algorithmic bias, cybersecurity risks, regulatory compliance, model interpretability, ethical concerns, and evolving financial fraud techniques. Future research should focus on explainable financial AI, quantum machine learning, privacy-preserving federated learning, autonomous fraud detection systems, blockchain-integrated AI frameworks, and sustainable AI governance for intelligent financial ecosystems.
The study concludes that Artificial Intelligence provides a strategic foundation for intelligent financial risk prediction and fraud detection by integrating advanced analytics, intelligent automation, responsible AI governance, and secure digital financial infrastructures to support resilient, transparent, and sustainable financial systems.
Keywords Artificial Intelligence, Financial Risk Prediction, Fraud Detection, Machine Learning, FinTech, Credit Risk, Anti-Money Laundering, Explainable AI, Predictive Analytics, Financial Security.
Field Engineering
Published In Volume 2, Issue 6, November-December 2020
Published On 2020-11-12
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