Shift-left in your fight against supply chain fraud

Norman Katz
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Norman Katz: President, Katzscan, USA

Journal of Supply Chain Management, Logistics and Procurement, 2024, vol. 7, issue 1, 86-100

Abstract: Supply chain operations rely upon various supply chain software systems, centred around the enterprise resource planning (ERP) system. Traditional and still widely utilised and relied-upon audit techniques have addressed the issue of finding problems — particularly fraud — typically too late after they have happened. Inasmuch as the ERP system is considered the business system of record, it may not be the system of origination for every supply chain transaction, meaning that fraud examination needs to look beyond the ERP system and notably before the ERP general ledger. The closer to a transaction’s point of origin the unusual behaviour can be detected, the sooner the outlier issue can be fixed, and ideally averted in the future with the right corrective actions taken then and there. This all helps to prevent the problem — the bad data, the offending transaction, and possibly the incorrect goods — from travelling through the supply chain and manifesting into something worse. Ramifications can include knock-on effects to data analysis, impacts to decisions, passing bad information to supply chain partners, conveying the wrong goods and material effects on financial statements. This paper presents a supply chain perspective that reveals just how much control an enterprise really does have over its supply chain transactions, showcases how reactive fraud discovery methodologies remain firmly in place, and offers a more proactive business model that leverages what most companies already have to improve internal controls and decrease incidences of fraud.

Keywords: artificial intelligence (AI); supply chain; fraud; enterprise resource planning (ERP); electronic data interchange (EDI); barcode; automatic identification; radio frequency identification (RFID) (search for similar items in EconPapers)
JEL-codes: L23 M11 (search for similar items in EconPapers)
Date: 2024
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