The financial sector faces a lot of challenges when it comes to fraud detection. Artificial Intelligence can help curb such frauds.
FREMONT, CA: Fraud is the oldest challenge for financial services institutions. Global transactions have increased with growth; the danger of fraud has increased. Artificial intelligence has the potential to reduce financial fraud as automated fraud detection tools are getting smarter, and machine learning is becoming more powerful. According to the latest report by McAfee, the global economy loses approximately 600 billion USD due to cybercrime. The most common and preventable cybercrime is credit card fraud, which is the result of online transactions. The increasing speed of credit card fraud makes intelligent fraud detection techniques important. Due to large volumes of customer and transactional data, AI can be effectively used to identify credit card behavior patterns.
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With traditional rule-based anti-fraud measures, false positives occur regularly where the system alerts anything that falls outside the given set of parameters. For instance, a false fraud warning may be triggered when a customer is buying airline tickets and accommodation abroad. A smarter system can better understand the underlying patterns of human behavior, use new customer data to match it with a bunch of users. Further, it can test the behavior typical to new users before alerting a fraud in the account. This could result in customer satisfaction by limiting the number of incorrect flaggings to reduce operational costs through unnecessary interactions with customers. With advanced technology, the potential risk of electronic fraud is getting bigger, and adding the newfound ability of cybercriminals to use unregulated cryptocurrency makes it essential to use the most advanced technology to fight cyber attacks.
The finance sector is witnessing new algorithms that are based on the way people think to reduce fraudulent activity. Such algorithms are called Convolutional Neural Networks based on the visual cortex, a small segment of cells sensitive to specific regions of the human visual field. These neural networks use images directly as input functioning similar to a visual cortex, which extracts elementary visual features like end-points, oriented edges, and corners. These new developments make AI infinitely smarter. The added advantage of this model is to use a wide variety of data points to fit different customers and transactions into best-suited clusters. Thus, as the spending habits of the customers change, the model would automatically adjust.
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