Fraud involves deception with the intent to illegally or unethically gain at the expense of another. It can take a variety of forms, from false insurance claims to stock manipulation to mortgage fraud. The criminal schemes vary, but they all share common elements: false suggestions or suppression of facts that are believed and relied upon by others; and depriving an institution of property it possesses or to which it is legally entitled.
Fraud is difficult to prevent and manage because criminals are agile and creative, and new threats emerge all the time. There is no one-size-fits-all approach to fraud prevention, but it is important for businesses to educate their employees on the dangers of sharing personal information over the phone or internet and to encourage them to ask questions before giving out information that could be used to commit a fraud scheme.
There is also an opportunity for business leaders to leverage technology, and specifically artificial intelligence to detect patterns that are indicative of fraudulent activity. Neural networks, for example, can be used to identify fraud-like behavior in data and predict whether it will occur again. This is particularly useful for large data sets where individual signals may be difficult to discern.
Unfortunately, fraud is a pervasive threat that can have huge costs for businesses. The ACFE reports that an average organization loses 3% of its profits to fraud and global losses reach over 6% of GDP. Fraud costs can be incurred in a variety of ways, including direct losses from theft and misappropriation, and indirect losses like reputational damage, loss of future opportunities, low employee morale, lawsuits, and the cost of fraud prevention.