The Impact of AI-Driven Fraud Detection on Financial Inclusion in India: Opportunities and Challenges

This research paper examines the intricate relationship between AI-driven fraud detection systems and financial inclusion efforts in India. As the country strives to bring more citizens into the formal banking sector, the implementation of advanced technologies like Artificial Intelligence (AI) in fraud prevention presents both opportunities and challenges. This study explores how AI-based fraud detection mechanisms can potentially enhance trust in financial institutions, reduce operational costs, and improve access to credit for underserved populations. Conversely, it also investigates the potential barriers these technologies may create, such as exacerbating the digital divide or introducing algorithmic biases. Through a comprehensive analysis of current literature, case studies, and expert interviews, this paper aims to provide insights into the complex interplay between technological advancements in banking security and the broader goal of financial inclusion. The findings suggest that while AI-driven fraud detection has the potential to significantly boost financial inclusion efforts, its implementation must be carefully managed to ensure equitable access and prevent unintended exclusion. The study concludes with policy recommendations and directions for future research to optimize the use of AI in fraud detection while promoting inclusive financial growth in India.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-25
DOI
https://doi.org/10.5281/zenodo.15513362
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
0.00
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article

The Impact of AI-Driven Fraud Detection on Financial Inclusion in India: Opportunities and Challenges

Zenodo (CERN European Organization for Nuclear Research)
FinTech, Crowdfunding, Digital Finance
article

The Impact of AI-Driven Fraud Detection on Financial Inclusion in India: Opportunities and Challenges

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Abstract

This research paper examines the intricate relationship between AI-driven fraud detection systems and financial inclusion efforts in India. As the country strives to bring more citizens into the formal banking sector, the implementation of advanced technologies like Artificial Intelligence (AI) in fraud prevention presents both opportunities and challenges. This study explores how AI-based fraud detection mechanisms can potentially enhance trust in financial institutions, reduce operational costs, and improve access to credit for underserved populations. Conversely, it also investigates the potential barriers these technologies may create, such as exacerbating the digital divide or introducing algorithmic biases. Through a comprehensive analysis of current literature, case studies, and expert interviews, this paper aims to provide insights into the complex interplay between technological advancements in banking security and the broader goal of financial inclusion. The findings suggest that while AI-driven fraud detection has the potential to significantly boost financial inclusion efforts, its implementation must be carefully managed to ensure equitable access and prevent unintended exclusion. The study concludes with policy recommendations and directions for future research to optimize the use of AI in fraud detection while promoting inclusive financial growth in India.

Zenodo (CERN European Organization for Nuclear Research)
NIMS University (IN)
Reduced inequalities
Openalex Percentile: Top 37%
FinTech, Crowdfunding, Digital Finance
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The Impact of AI-Driven Fraud Detection on Financial Inclusion in India: Opportunities and Challenges · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS