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This article is part of an ongoing series on the uses for artificial intelligence (AI) in manufacturing, starting with our article introducing machine learning and AI, and their relevance to manufacturing and supply chain operations. 

This article will cover how AI can be used by a manufacturer looking to detect fraud from within and without its company. Artificial intelligence solutions allow for quicker detection rates, allowing manufacturers to “nip it in the bud,” so to speak, and to save money. 

Fraudsters Love to Target Manufacturers

Among the most widely-chosen targets for cybercriminals and fraudsters are manufacturers. 

This is because the cost of doing business is so high for manufacturers that a shutdown caused by hackers could lead to a hefty ransom payday.

Additionally, so much money is spent on all aspects of the process, such as transportation and ordering raw materials through suppliers. With so many aspects to the process, it is easy for a fraudster, within or without the company, to find a link in the supply chain to exploit. 

According to this report, the median loss in fraud cases, across all industries, is $200,000. That tends to run higher in manufacturing, where, as mentioned, even a short shutdown can lead to high costs. 

That same report mentions that in a little under half of these cases of fraud, employees are the culprit. 

In manufacturing, there are so many internal opportunities for fraud, such as asset misappropriation (read: theft) that it is near impossible for humans alone to monitor. This is where AI comes in. 

AI Accurately Detects and Predicts Fraud

There are many forms of scams that are used by fraudsters, some of them well-known because of their use in other cases, while some could be newer and less-known, such as malware recently created and never used before. 

What AI is adept at is finding patterns across large data sets, and noticing even the most subtle differences across many data sets. 

AI can analyze historical cases of fraud, especially those that occur in the manufacturing industry, and see how changes in inventory, reported profits on financial statements, the times of these changes and reports, etc. These are contrasted with “healthy” data sets, where no fraud is occurring, to find how things even as small as the time with which financial statements are reported can lead to major insights. 

As a result, AI can both predict, and detect, signs of fraud as soon as they appear. A key aspect of the pattern-finding practice is that relations between many different aspects of the manufacturing process can be discovered, and how, say, a small but unusual change in inventory can lead to a suspicious financial statement down the line. 

Noticing these changes can be incredibly important for predicting the case of a fraud, and AI can make more accurate predictions than humans can, because of AI’s ability to speedily, but effectively, analyze data sets that are so large that it would take a human, or multiple humans, so much time to analyze that the fraud would be long over before it is detected. 

Though human intuition is a powerful tool, the hard data-backed analysis given by AI can be a powerful assistance in the efforts for management to detect any suspicious activity across the supply chain. 

Conclusion

Through a low-cost, highly efficient AI  system, management can up their fraud prevention efforts across the entire supply chain, stopping offenders from accessing the company’s valuable assets. Whether it is from outside or orchestrated by drivers, customers, or manufacturers themselves, a fraud scheme can be detected before it becomes a major threat, that is, when AI is employed to detect it. 

Scams come in many forms, and fraudsters are always trying out new tricks, so it pays to have a 24/7, tireless AI agent on hand to predict and detect fraud within your company. 

For other helpful AI-powered manufacturing solutions, reach out to Findability Sciences.

 

More Articles in Our Machine Learning for Manufacturers Series: