UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 13 | Issue 2 | February 2026

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Published in:

Volume 10 Issue 12
December-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2312816


Registration ID:
555830

Page Number

i123-i136

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Title

PILOT STUDY ON AI APPLICATIONS IN PREVENTING FINANCIAL FRAUD IN JAMSHEDPUR’S BANKING AND FINTECH ECOSYSTEM

Authors

Abstract

Financial fraud is a growing challenge in the banking and fintech sectors, particularly in emerging economies where digital financial services are expanding. Jamshedpur, a rapidly growing industrial city in India, has witnessed a rise in banking transactions and fintech adoption, necessitating advanced fraud prevention mechanisms. This study explores the role of Artificial Intelligence (AI) in mitigating financial fraud within Jamshedpur’s banking and fintech ecosystem. It evaluates AI-driven solutions, examines their effectiveness, and discusses challenges and opportunities for further implementation. The study aims to provide insights for policymakers, financial institutions, and fintech companies in leveraging AI for fraud prevention. Financial fraud is a growing concern in the banking and fintech sectors, with digital transactions becoming increasingly susceptible to cyber threats. This study explores the role of Artificial Intelligence (AI) in preventing financial fraud within Jamshedpur’s banking and fintech ecosystem. AI-driven fraud detection systems, including machine learning algorithms, biometric authentication, and blockchain integration, have emerged as effective tools for identifying fraudulent transactions in real time. Through surveys, interviews, and case studies, this research analyzes AI’s effectiveness, customer trust, implementation challenges, and regulatory considerations. The findings indicate that 72% of surveyed customers are aware of AI-driven fraud prevention, with 60% trusting AI for enhanced security. However, challenges such as data privacy concerns, high implementation costs, AI biases, and regulatory compliance remain significant barriers to widespread AI adoption. The study highlights the future prospects of AI in fraud detection, emphasizing the need for continuous algorithm updates, enhanced regulatory frameworks, AI-blockchain synergy, and improved customer education programs. A hybrid approach combining AI with traditional fraud prevention mechanisms is recommended for a more secure and resilient financial ecosystem. This research contributes to the ongoing discussion on leveraging AI for fraud prevention, offering insights for banks, fintech companies, and policymakers in Jamshedpur and beyond.

Key Words

PILOT STUDY ON AI APPLICATIONS IN PREVENTING FINANCIAL FRAUD IN JAMSHEDPUR’S BANKING AND FINTECH ECOSYSTEM

Cite This Article

"PILOT STUDY ON AI APPLICATIONS IN PREVENTING FINANCIAL FRAUD IN JAMSHEDPUR’S BANKING AND FINTECH ECOSYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 12, page no.i123-i136, December-2023, Available :http://www.jetir.org/papers/JETIR2312816.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"PILOT STUDY ON AI APPLICATIONS IN PREVENTING FINANCIAL FRAUD IN JAMSHEDPUR’S BANKING AND FINTECH ECOSYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 12, page no. ppi123-i136, December-2023, Available at : http://www.jetir.org/papers/JETIR2312816.pdf

Publication Details

Published Paper ID: JETIR2312816
Registration ID: 555830
Published In: Volume 10 | Issue 12 | Year December-2023
DOI (Digital Object Identifier):
Page No: i123-i136
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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