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Reseach Article

Real-Time Analysis and Decision on Fraud Detection using Pega

by Praveen Kumar Tammana
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 3
Year of Publication: 2024
Authors: Praveen Kumar Tammana
10.5120/ijca2024923362

Praveen Kumar Tammana . Real-Time Analysis and Decision on Fraud Detection using Pega. International Journal of Computer Applications. 186, 3 ( Jan 2024), 14-21. DOI=10.5120/ijca2024923362

@article{ 10.5120/ijca2024923362,
author = { Praveen Kumar Tammana },
title = { Real-Time Analysis and Decision on Fraud Detection using Pega },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2024 },
volume = { 186 },
number = { 3 },
month = { Jan },
year = { 2024 },
issn = { 0975-8887 },
pages = { 14-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number3/33052-2024923362/ },
doi = { 10.5120/ijca2024923362 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:29:36.679939+05:30
%A Praveen Kumar Tammana
%T Real-Time Analysis and Decision on Fraud Detection using Pega
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 3
%P 14-21
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the rapidly evolving digital landscape, the threat of financial fraud has escalated, posing significant challenges for businesses and financial institutions. Traditional methods of fraud detection often lag behind the sophisticated tactics employed by fraudsters, leading to increased financial losses and compromised customer trust. This paper delves into the transformative potential of Pega Process AI in revolutionizing fraud detection through real-time analysis and decisioning. Pega Process AI, with its advanced artificial intelligence and machine learning capabilities, offers a proactive and efficient approach to identifying and mitigating fraudulent activities. This study explores the mechanism by which Pega Process AI processes vast volumes of transactional data in real-time, employing predictive analytics, dynamic rule adjustment, and context-aware decisioning to detect and prevent fraud. By highlighting the system's ability to adapt to evolving fraud patterns and integrate seamlessly with existing transaction systems, the paper underscores the enhanced accuracy, reduced false positives, and operational efficiency afforded by this technology. The implications of implementing Pega Process AI in real-world scenarios are examined, showcasing its effectiveness in safeguarding assets while ensuring a positive customer experience. This research contributes to the understanding of how real-time AI-driven systems like Pega Process AI are pivotal in the modern fight against financial fraud, marking a significant leap over traditional fraud detection methodologies.

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Index Terms

Computer Science
Information Sciences

Keywords

Real-Time Analysis Fraud Detection Decision Making Pega Platform Predictive Analytics