Developing Advanced Fraud Prevention Techniques using Data Analytics and ERP Systems

Pavan Navandar

Abstract: Financial fraud poses a significant threat to organizations across industries, resulting in substantial financial losses, reputational damage, and erosion of stakeholder trust. Traditional fraud prevention methods often prove inadequate in the face of evolving tactics and sophisticated schemes. This paper explores the potential of data analytics and Enterprise Resource Planning (ERP) systems in developing advanced fraud prevention techniques. By harnessing the power of data analysis, machine learning, and artificial intelligence, organizations can proactively identify, detect, and mitigate fraud risks, safeguarding their financial assets and ensuring business continuity.

Keywords: Fraud Prevention, Data Analytics, ERP Systems, Machine Learning, Artificial Intelligence, Predictive Modeling, Behavioral Analytics, Risk Management, Compliance, Cybersecurity

How to Cite?: Pavan Navandar, "Developing Advanced Fraud Prevention Techniques using Data Analytics and ERP Systems", Volume 10 Issue 5, May 2021, International Journal of Science and Research (IJSR), Pages: 1326-1329, https://www.ijsr.net/getabstract.php?paperid=SR24418104835, DOI: https://dx.doi.org/10.21275/SR24418104835