Artificial Intelligence Driven Fraud Detection in SAP for Retail and Healthcare

Fraud is a major concern for businesses, particularly in retail and healthcare, where it can lead to significant financial losses and damage to trust. Traditional fraud detection methods often fall short in addressing the sophisticated techniques used today. This article discusses how AI-driven fraud detection systems within SAP are making a difference, particularly for retail and healthcare. Using advanced machine learning and data analytics, AI offers better accuracy, real-time monitoring, and cost savings. We explore methods, real-world examples, comparisons, and future trends to show how AI-driven solutions effectively combat fraud. Through cases involving Walmart and Kaiser Permanente, this piece illustrates practical uses, challenges, and successes with AI in fraud detection.

Authors

Publication Details

Journal
International Journal of Science and Research (IJSR)
Published
2024-11-05
DOI
https://doi.org/10.21275/sr24119111713
Citations
1
Primary Topic
Imbalanced Data Classification Techniques
Type
article
Field-Weighted Citation Impact
0.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial Intelligence Driven Fraud Detection in SAP for Retail and Healthcare

Mukesh Saini, Chetan Sharma, Adarsh Vaid
1 citations
International Journal of Science and Research (IJSR)
Imbalanced Data Classification Techniques
0.35
article

Artificial Intelligence Driven Fraud Detection in SAP for Retail and Healthcare

Mukesh Saini, Chetan Sharma, Adarsh Vaid
article en
1 citations

Abstract

Fraud is a major concern for businesses, particularly in retail and healthcare, where it can lead to significant financial losses and damage to trust. Traditional fraud detection methods often fall short in addressing the sophisticated techniques used today. This article discusses how AI-driven fraud detection systems within SAP are making a difference, particularly for retail and healthcare. Using advanced machine learning and data analytics, AI offers better accuracy, real-time monitoring, and cost savings. We explore methods, real-world examples, comparisons, and future trends to show how AI-driven solutions effectively combat fraud. Through cases involving Walmart and Kaiser Permanente, this piece illustrates practical uses, challenges, and successes with AI in fraud detection.

International Journal of Science and Research (IJSR)Vol. 13(11)
Peace, Justice and strong institutions
Openalex Percentile: Top 32%
Imbalanced Data Classification Techniques
0.35
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.