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Role of Machine Learning in Financial Transactions

Since lockdown, online transactions have shot up. And online fraud has also shot up. It has become quite impossible for banks to detect frauds.  But by applying machine learning, fraud detection has become easy for financial organization. Machine learning is detecting email spam,  product recommendation, accurate medical diagnosis etc. Machine learning can also authenticate transactions using machine learning and predictive analytics. Read more at:



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Detecting online frauds

As the frequency of credit card fraud is increasing, so are the costs associated with these bad transactions that include, lost merchandise, lost profit, transportation costs, etc. Hence, enter fraud analysts, who are continuously updated through automated machine learning, about any sort of fraudulent activities, spotted by customers, online. Five ways to spot and prevent online fraud:
1. Users with no shopping history can be suspected, who may create new accounts only to test stolen credit card information.
2. Bulk orders of multiple costly items are to be suspected.
3. Hastening up a delivery process is to be suspected, as imposters try to get benefited as much as possible, before getting detected.
4. Multiple accounts or multiple shipping or billing addresses, with any one common factor, out of the three, should be cross-checked.
5. Accounts with multiple credit cards should also be cross-checked.
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