Businesses worldwide lose up to 10% of their annual revenue or $3.7 trillion on average to fraud. On the other hand, frauds are difficult to detect and organizations managed to find out who conducted the fraud in 17% of financial audits only. In most cases, frauds are conducted by employees, managers, and customers but there are also cases when the one to conduct a fraud is a business owner.
That is why companies have started exploring new ways to protect their assets and turned to data science and machine learning as the most powerful tech weapons of our age. Today, we are talking about how these technologies help with fraud detection, the benefits of machine learning, and how to actually use it to prevent fraud.
How Does Machine Learning Help With Fraud Detection?
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In order to detect fraud, you should train the machine learning engine first. That includes using historical data and creating rules artificial intelligence will use to detect potential flags. For instance, you can train it to detect and block fraudulent transactions or suspicious logins. However, you should also create non-fraud rules to ensure higher precision and accuracy.
Note that there is a difference between machine learning and AI. AI is a wider concept while machine learning is its subcategory and deep learning is a subset of machine learning. Machine learning, just like its name suggests, makes it possible for machines to learn from data.
3 Benefits of Machine Learning for Fraud Detection
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Swift detection
Unlike humans, machines can process large datasets and identify uncommon behaviors and patterns in milliseconds. AI and machine learning can truly put any process on speed and help with accelerating profound discoveries.
Less manual work and fewer costs
For the above-mentioned reasons, there is no need for human agents to review data manually anymore. Machines will do all the hard work, plus, they can run 24/7 without the need to take a break.
Businesses now don’t have to increase risk management costs when scaling since machine learning systems can replace multiple employees and handle literally any volume of data, even during the busiest periods.
Better Predictions
The longer the algorithm runs, the more accurate it gets. Machine learning engines can process large data assets, find similar patterns, and get easily trained, which is not the case with humans who would need months to identify suspicious behaviors or find similarities in different kinds of fraudulent behaviors. What’s more, according to studies, machine learning algorithms have a 96% success rate in detecting and preventing fraud.
Which Industries Are Using Data Science and Machine Learning for Fraud Detection?
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eCommerce Businesses
It is predicted that a myriad of eCommerce websites and online stores will lose up to $50 billion to fraud by 2024. That’s why some popular eCommerce brands have started using machine learning to protect valuable data, find out which products fraudsters target the most, which card payments to block, and to understand why the system flags some transactions as fraudulent.
Online Gaming and Gambling
Betting and gambling …….
Source: https://startup.info/using-data-science-and-machine-learnings-potential-for-fraud-detection/