Resisting Financial Fraud using AI and ML

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Photo by Matthew Guay on Unsplash

Technologies play a significant role in streamlining all aspects of businesses. Artificial Intelligence (AI) and Machine Learning (ML) are powerful technologies that companies are using to achieve increased efficiencies and provide innovative solutions to consumers. When it comes to the banking and financial sector, along with making services better, these technologies are proving as excellent weapons in the fight against online threats.

Frauds are dangerous because they threaten to disrupt banks and steal sensitive customer accounts information. To be in a position to mitigate these attacks, the financial sector requires solutions that are offered aplenty by AI and ML. The algorithms used in these technologies analyze a vast amount of data and a bulk of transaction information in real time. This enables a system where fraudulent transactions can be detected, with a lot of accuracies by considering various factors like location, time, and device used. Human beings working as analysts cannot match this level of efficiency. Organizations can hence, curb suspicious activities and prevent frauds. The accuracy of fraud detection also reduces the case of false positives and the instances where banks flag authentic transactions, suspicious also decrease.

AI and ML scan through vast amounts of data which they subsequently analyze. The larger the data, the more accurate, is the analysis. The analysis generates trends, which prove to be extremely useful while combing through data generated during the transaction. These algorithms can easily recognize anomalies and send signals to prevent threat scenarios, giving more power to the banks and making them safer.

To regulate the functioning of organizations, a set of regulatory policies are in place. These manually defined policies are no longer capable of keeping up with the security situation. Financial Fraud using AI…

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I am a technology blogger, who loves to read and write on the latest in technology.

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