How AI can Crack Down on Employee Theft

Artificial Intelligence (AI), also known as machine learning, is no longer a far-flung fixture of science fiction. While media often presents AI as an imminent threat poised to take over the world, the reality is that AI has already taken over the business landscape.

In fact, AI is now commonplace in tracking credit scores, detecting credit card fraud, and preventing identity fraud. By using examples and prior data models, machine learning algorithms continually improve themselves by refining their processes to become more efficient and effective.

A Revolution in Loss Prevention

Now that AI technology has become cost effective and readily available, its wide array of applications is just now being realized. Currently, loss prevention is at the beginning of an AI revolution similar to that of financial institutions in the 1990s.

Early evaluations of loss prevention AI programs show promising results. When seeded with an organization’s employee theft data, these programs have been able to detect 25% more cases of employee fraud in 25% less time. As these programs refine their detection algorithms, they will be able interpret more variables and operate without needing organization-specific data.

These sophisticated employee theft detection programs have a distinct advantage over traditional detection methods. With their capacity to process thousands of complex variables, an organization practically gains an in-house data professional by implementing AI detection.

Given this potential, use of AI in employee theft detection is estimated to increase from its current 20% of the detection model to a staggering 80%. Rather than causing a tech-pocalypse, companies choosing to incorporate AI detection software may be able to mitigate and prevent instances of employee theft.

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