Mercator Advisory Group members first heard about GANs and synthetic data reading Mercator’s machine learning primer published in April 2017. I discussed this in some depth with Arm Insights (now Facteus) in a podcast in July last year. Anyone interested in creating a deepfake using this technology can follow the simple instructions here; the results are amateurish but easy.
Synthetic data and the GAN technology has continued to improve over time and in this article from Fortune, we learn that Amex is creating payment transaction training data using the technique:
“American Express researchers, on the other hand, trained their GANs on internal data that is normally used for tasks like calculating consumer credit scores, so that the software could create its own financial data.
The goal was for the GANs to create fake transactions “that look normal,” said Dmitry Efimov, the vice president of machine learning research for American Express. Data with obvious anomalies, such as multiple purchases of toilet paper in New York City on one day, followed by a lawnmower purchase in Bakersfield, Calif., the next, would be less effective.
Efimov declined to comment about how American Express could specifically use synthetic financial data to improve fraud detection, citing the risk that criminals could use the information for their benefit. But, generally speaking, the more financial data the company has, the more it can improve its cybersecurity systems.
Other organizations that are researching using GANs to create synthetic financial data include online retailing giant Amazon. In 2018, Amazon published a paper about using the software to create synthetic e-commerce transactions so that the data could eventually be used for “product recommendation, targeting deals, and simulation of future events.”
Researchers at the University of Michigan have also published a paper about using GANs to create fake stock market orders. That information could be used to help uncover stock market manipulation schemes, explained Xintong Wang, a Ph.D. candidate in the University of Michigan’s computer science department.”
Overview by Tim Sloane, VP, Payments Innovation at Mercator Advisory Group