Some of the key issues and challenges associated with the current practices and potential future direction of research have also been identified.doi:10.1016/j.cose.2015.09.005Jarrod WestMaumita BhattacharyaElsevier Advanced Technology PublicationsComputers & Security...
Section III of this paper defines the anomaly while detailing a high-level summary of the associated detection task and provides an overview of the nature of the problem and its associated challenges. In section IV, background information on fraud in the financial domain is contextualized, with ...
Financial fraud negatively impacts organizational administrative processes, particularly affecting owners and/or investors seeking to maximize their profits. Addressing this issue, this study presents a literature review on financial fraud detection through machine learning techniques. The PRISMA and Kitchenham ...
The preponderance of threat risks—cybersecurity, ransomware, cryptocurrency, identity theft—are technology-driven.
Overview of fraud detection Fraud detection is a set of processes and analyses that allow firms to identify and prevent unauthorized activity. It has become one of the major challenges for most organizations, particularly those in banking, finance, retail, and e-commerce. ...
In SLR, research questions are key and decisive for the success of the study (Kitchenham and Stuart,2007). Therefore, analyzing the existing literature on financial fraud detection through ML techniques and its characteristics, problems, challenges, solutions, and research trends is crucial. Table1...
The resulting insights can mitigate challenges before they become larger, systemic issues. Learn More Why generative AI projects fail in highly regulated industries — and how yours can succeed Improve firmwide data management The rate of new regulations is increasing. Marketing requests are becoming ...
In this paper, we address these aforementioned challenges associated with financial data and introduce FinGPT, an endto-end open-source framework for financial large language models (FinLLMs). Adopting a data-centric approach, FinGPT underscores the crucial role of data acquisition, cleaning, and ...
How do you prevent payment fraud? How do you prevent money laundering (AML)? What are best practices for AML name screening systems? What are the key steps in AML transaction screening? What are the various types of AML transaction monitoring?
Finally, the current challenges and potential directions are outlined to provide some inspiring information on intelligent financial fraud detection in the post-pandemic era. The remainder of the paper is organized as follows. Section 2, financial fraud detection data evolution, presents the evolution ...