Visa to Add Supervised Machine Learning to Its Fraud Protection Portfolio

Complex algorithms utilized in data analytics are called unsupervised machine learning, but image recognition or besting the Go champion utilizes supervised machine learning; technology that utilizes neural networks. "The new platform is expected to test algorithms that use an advanced form of AI called deep learning, a technique that has the potential to identify more complex patterns than traditional machine-learning algorithms. "It's a massive breakthrough for us," Mr. Taneja said. Visa currently uses machine-learning algorithms to sift through data to identify anomalies, an effort that prevents billions of dollars in fraudulent transactions annually, Mr. Taneja said. One such Visa fraud-detection system, Advanced Authorization, prevented about $25 billion in fraud in the year ended April 30, according to the company. But the current models have limitations. Researchers must know the signals that might indicate fraud--such as a purchase taking place at an unusual time of day--and write the rules to tell the model what to do when it identifies suspicious activity. Criminal activity sometimes slips by unnoticed because hackers are getting more sophisticated at evading the warning signs that current machine-learning models are trying to detect. Deep-learning models can automatically identify more complex patterns by themselves. For example, if a customer uses his or her card in another country for the first time, deep-learning algorithms will be able to tell, with more accuracy and fewer false positives than traditional machine learning, whether it's a legitimate transaction. The algorithms will be able to take into account previous transactions at airlines and hotels, as long as they are made with Visa cards."