Strategic Integration of AI and Cloud Computing for Fraud Prevention and Its Implications for Business Performance and Operational Risk

The convergence of artificial intelligence and cloud computing has revolutionized fraud prevention strategies across global enterprises. This review examines the strategic integration of these technologies, analyzing their synergistic impact on detecting, preventing, and mitigating fraudulent activities. We explore how AI-powered algorithms leverage cloud infrastructure to process massive datasets in real-time, enabling predictive analytics and adaptive threat responses. The paper investigates implications for business performance metrics, operational risk management, and organizational resilience. Through comprehensive analysis of implementation frameworks, security considerations, and performance outcomes, we demonstrate that organizations adopting integrated AI-cloud solutions achieve superior fraud detection rates, reduced false positives, and enhanced operational efficiency. Critical challenges including data privacy, algorithmic bias, and integration complexity are also examined.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-31
DOI
https://doi.org/10.5281/zenodo.18336177
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Strategic Integration of AI and Cloud Computing for Fraud Prevention and Its Implications for Business Performance and Operational Risk

Toyosi Mustapha, Abdulateef Oluwakayode Disu, Azeez Rabiu, Oluwaseun Joseph Adeola
Zenodo (CERN European Organization for Nuclear Research)
Big Data and Business Intelligence
article

Strategic Integration of AI and Cloud Computing for Fraud Prevention and Its Implications for Business Performance and Operational Risk

Toyosi Mustapha, Abdulateef Oluwakayode Disu, Azeez Rabiu, Oluwaseun Joseph Adeola
article en

Abstract

The convergence of artificial intelligence and cloud computing has revolutionized fraud prevention strategies across global enterprises. This review examines the strategic integration of these technologies, analyzing their synergistic impact on detecting, preventing, and mitigating fraudulent activities. We explore how AI-powered algorithms leverage cloud infrastructure to process massive datasets in real-time, enabling predictive analytics and adaptive threat responses. The paper investigates implications for business performance metrics, operational risk management, and organizational resilience. Through comprehensive analysis of implementation frameworks, security considerations, and performance outcomes, we demonstrate that organizations adopting integrated AI-cloud solutions achieve superior fraud detection rates, reduced false positives, and enhanced operational efficiency. Critical challenges including data privacy, algorithmic bias, and integration complexity are also examined.

Zenodo (CERN European Organization for Nuclear Research)
University of Ibadan (NG), Babcock University (NG), Southern New Hampshire University (US), London Business School (GB)
Openalex Percentile: Top 21%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.