Automating Vendor Fraud Detection in Enterprise Systems

Fraud is a multi-billion dollar industry that continues to grow annually. Many organizations are poorly prepared to prevent and detect fraud. Fraud detection strategies are intended to quickly and efficiently identify fraudulent activities that circumvent preventative measures. In this paper, we adopt a DesignScience methodological framework to develop a model for detection of vendor fraud based on analysis of patterns or signatures identified in enterprise system audit trails. The concept is demonstrated by developing prototype software. Verification of the prototype is achieved by performing a series of experiments. Validation is achieved by independent reviews from auditing practitioners. Key findings of this study are: (a) automating routine data analytics improves auditor productivity and reduces time taken to identify potential fraud; and (b) visualizations assist in promptly identifying potentially fraudulent user activities. The study makes the following contributions: (a) a model for proactive fraud detection; (b) methods for visualizing user activities in transaction data; and (c) a stand-alone Monitoring and Control Layer (MCL) based prototype

Automating Vendor Fraud Detection in Enterprise Systems

Fraud is a multi-billion dollar industry that continues to grow annually. Many organisations are poorly prepared to prevent and detect fraud. Fraud detection strategies are intended to quickly and efficiently identify fraudulent activities that circumvent preventative measures. In this paper we adopt a Design-Science methodological framework to develop a model for detection of vendor fraud based on analysis of patterns or signatures identified in enterprise system audit trails. The concept is demonstrated be developing prototype software. Verification of the prototype is achieved by performing a series of experiments. Validation is achieved by independent reviews from auditing practitioners. Key findings of this study are: i) automating routine data analytics improves auditor productivity and reduces time taken to identify potential fraud, and ii) visualisations assist in promptly identifying potentially fraudulent user activities. The study makes the following contributions: i) a model for proactive fraud detection, ii) methods for visualising user activities in transaction data, iii) a stand-alone MCL-based prototype.</p

Developing a Forensic Continuous Audit Model

Despite increased attention to internal controls and risk assessment, traditional audit approaches do not seem to be highly effective in uncovering the majority of frauds. Less than 20 percent of all occupational frauds are uncovered by auditors. Forensic accounting has recognized the need for automated approaches to fraud analysis yet research has not examined the benefits of forensic continuous auditing as a method to detect and deter corporate fraud. The purpose of this paper is to show how such an approach is possible. A model is presented that supports the acceptance of forensic continuous auditing by auditors and management as an effective tool to support the audit function, meet management’s regulatory objectives, and to combat fraud. An approach to developing such a system is presented

A conceptual model for proactive detection of potential fraud enterprise systems: exploiting SAP audit trails to detect asset misappropriation

Fraud costs the Australian economy approximately $3 billion annually, and its frequency and financial impact continues to grow. Many organisations are poorly prepared to prevent and detect fraud. Fraud prevention is not perfect therefore fraud detection is crucial. Fraud detection strategies are intended to quickly and efficiently identify frauds that circumvent preventative measures so that an organisation can take appropriate corrective action. Enhancing the ability of organisations to detect potential fraud may have a positive impact on the economy. An effective model that facilitates proactive detection of potential fraud may potentially save costs and reduce the propensity of future fraud by early detection of suspicious user activities. Enterprise systems generate millions of transactions annually. While most of these are legal and routine transactions, a small number may be fraudulent. The enormous number of transactions makes it difficult to find these few instances among legitimate transactions. Without the availability of proactive fraud detection tools, investigating suspicious activities becomes overwhelming. This study explores and develops innovative methods for proactive detection of potential fraud in enterprise systems. The intention is to build a model for detection of potential fraud based on analysis of patterns or signatures building on theories and concepts of continuous fraud detection. This objective is addressed by answering the main question; can a generalised model for proactive detection of potential fraud in enterprise systems be developed? The study proposes a methodology for proactive detection of potential fraud that exploits audit trails in enterprise systems. The concept of proactive detection of otential fraud is demonstrated by developing a prototype. The prototype is a near real-time web based application that uses SAS for its analytics processes. The aim of the prototype is to confirm the feasibility of implementing proactive detection of potential fraud in practice. Verification of the prototype is achieved by performing a series of tests involving simulated activity, followed by a full scale case study with a large international manufacturing company. Validation is achieved by obtaining independent reviews from the case study senior staff, auditing practitioners and a panel of experts. Timing experiments confirm that the prototype is able to handle real data volumes from a real organisation without difficulty thereby providing evidence in support of enhancement of auditor productivity. This study makes a number of contributions to both the literature and auditing practice

Developing a Forensic Continuous Audit Model

Despite increased attention to internal controls and risk assessment, traditional audit approaches do not seem to be highly effective in uncovering the majority of frauds. Less than 20 percent of all occupational frauds are uncovered by auditors. Forensic accounting has recognized the need for automated approaches to fraud analysis yet research has not examined the benefits of forensic continuous auditing as a method to detect and deter corporate fraud. The purpose of this paper is to show how such an approach is possible. A model is presented that supports the acceptance of forensic continuous auditing by auditors and management as an effective tool to support the audit function, meet management’s regulatory objectives, and to combat fraud. An approach to developing such a system is presented

Optimizing Anti-Phishing Solutions Based on User Awareness, Education and the Use of the Latest Web Security Solutions

Phishing has grown significantly in volume over the time, becoming the most usual web threat today. The present economic crisis is an added argument for the great increase in number of attempts to cheat internet users, both businesses and private ones. The present research is aimed at helping the IT environment get a more precise view over the phishing attacks in Romania; in order to achieve this goal we have designed an application able to retrieve and interpret phishing related data from five other trusted web sources and compile them into a meaningful and more targeted report. As a conclusion, besides making available regular reports, we underline the need for a higher degree of awareness related to this issue.Security, Phishing, Ev-SSL, Security Solutions

AI-DRIVEN PAYMENT ORCHESTRATION PLATFORMS: PERFORMANCE METRICS, SCALABILITY, AND INTEROPERABILITY

Payment orchestration platforms powered by artificial intelligence (AI) are rapidly transforming the global payments landscape. These innovative solutions enable businesses to streamline and optimize their payment processes, leading to improved operational efficiency, enhanced customer experience, and increased revenue growth. This research article explores the key performance metrics, scalability considerations, and interoperability challenges associated with AI-driven payment orchestration platforms. By examining these critical aspects, we aim to provide valuable insights for businesses seeking to leverage these cutting-edge technologies and stay competitive in the ever-evolving digital payments ecosystem

Risky business: managing electronic payments in the 21st Century

On June 20 and 21, 2005, the Payment Cards Center of the Federal Reserve Bank of Philadelphia, in conjunction with the Electronic Funds Transfer Association (EFTA), hosted a day-and-a-half forum, “Risky Business: Managing Electronic Payments in the 21st Century.” The Center and EFTA invited participants from the financial services and processing sectors, law enforcement, academia, and policymakers to explore key topics associated with the challenge of effectively managing risk in a payments environment that is increasingly electronic. The meeting’s goal was to identify areas of potential risk and explore interindustry solutions. This paper provides highlights from the forum presentations and ensuing conversations.