Manuscript Number : IJSRST16122271

Real-Time Fraud Detection Using AI on financial streaming Data

Authors(2) :-Nirup Kumar Reddy Pothireddy, Bipinkumar Reddy Algubelli

The exponential proliferation of digital financial transactions has once again opened up a new challenge for detecting and preventing fraud in real-time. Traditional methods, particularly rule-based systems, have invariably resisted the disparate evolving tactics of fraudsters. This paper introduces how artificial intelligence (AI) and machine learning (ML) algorithms can be deployed for real-time fraud detection in financial streaming data. An AI-based framework is hereby proposed using supervised learning models such as Random Forests, Support Vector Machines (SVM), and Artificial Neural Networks (ANNs) to identify high-accuracy detection of unauthorized activities. Furthermore, the paper delves into the different hurdles associated with real-time fraud detection, such as data quality, model scalability, and impact from false positives. Performance testing of these models has been carried on a dataset of financial transactions. Analysis shows their ability to predict their fraudulent transactions with high precision and minimal latency. Conclusively, the study states AI-based methods unlock considerable advancements against traditional techniques, providing a scalable and adaptable response to the challenge faced by financial institutions.

Authors and Affiliations

Nirup Kumar Reddy Pothireddy
Independent Researcher, USA
Bipinkumar Reddy Algubelli
Independent Researcher, USA

Fraud Detection, Financial Streaming Data, Machine Learning, Real-Time Analytics, Big Data, Anomaly Detection, Artificial Intelligence, Random Forests, Support Vector Machines, Precision, Scalability

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Publication Details

Published in : Volume 2 | Issue 6 | November-December 2016
Date of Publication : 2016-12-25
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 750-759
Manuscript Number : IJSRST16122271
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Nirup Kumar Reddy Pothireddy, Bipinkumar Reddy Algubelli, " Real-Time Fraud Detection Using AI on financial streaming Data", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 2, Issue 6 , pp.750-759, November-December-2016. Available at doi : https://doi.org/10.32628/IJSRST16122271    
Journal URL : https://ijsrst.com/IJSRST16122271
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