Incorporating AI into payroll systems can significantly enhance fraud detection, offering businesses more reliable and efficient solutions to protect their operations. “
Human Error : Humans are prone to oversight. For instance, auditors may miss irregularities,
Labour-Intensive : Manual checks can be labour-intensive, requiring significant resources and time, adding to the existing operational costs. Given these limitations, many businesses are turning to more advanced and proactive approaches, particularly AI-powered systems, to strengthen their fraud prevention strategies.
detection relies heavily on manual reviews which are time-consuming and rule-based systems that are not equipped well enough to handle the complexity and volume of data in modern payroll systems. Traditional methods can identify fraud only after it has occurred, leading to significant financial losses, and they cannot prevent fraud. While effective to some degree, these methods have several limitations:
especially in large volumes of payroll data.
Limited Scope : Traditional fraud detection processes are not proactive, leaving organisations vulnerable to fraud that is not immediately obvious.
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ISSUE 10 GLOBAL PAYROLL MAGAZINE
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