The forensic professional’s perspective on fraud and fraud detection

Timothy P. Hedley and Richard H. Girgenti
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Timothy P. Hedley: Senior Adviser at K2 Integrity, Fordham University, USA
Richard H. Girgenti: Vice-Chairman, K2 Integrity, USA

Journal of Financial Compliance, 2021, vol. 5, issue 1, 85-93

Abstract: As banks and other financial institutions become increasingly complex and rely more heavily on remote and online services, they face an ongoing and ever-changing challenge presented by fraudsters who also have devised increasingly sophisticated methods to commit fraud. An effective compliance and fraud risk management programme must incorporate better and more sophisticated ways to meet the challenge of fraud. To this end, most organisations are increasingly turning to data analytics to help devise better methods to prevent and detect fraudulent activities. At the core of this effort to develop technology solutions to combat fraud are the skills, experience and competencies of forensic professionals. It is essential that any fraud risk management programme rely upon and leverages the diverse expertise of forensic professionals who will have the industry expertise, understanding of regulatory mandates, knowledge of fraud and their red flags and the various schemes devised to commit fraud. These professionals must also possess the investigative and forensic accounting acumen to detect fraud and the data analytic competency to help programmers and data scientists devise the rules and algorithms required to detect fraud and, ultimately, the ability to identify and investigate the data anomalies that will result and require further analysis. This paper discusses the unique perspective and expertise of the forensic professional, the nature of fraud, the forensic fraud detection process, sample banking fraud schemes and how the forensic competencies inform and enhance the power of data analytic processes from rules-based to artificial intelligence (AI) and predictive analytics.

Keywords: fraud; forensic; scheme; analytic; risk factors; red flags (search for similar items in EconPapers)
JEL-codes: E5 G2 K2 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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