Payments On Fire

Fraud prevention today is about how quickly we can separate good customers from questionable ones and, for those doubtful transactions, use the right set of tools and data sources to optimize speed, costs, and fraud losses. When it comes to fraud prevention, it turns out that data is key. No revelation there, but how we manipulate it, gather it, and assure its provenance is undergoing major change. What would be a revelation to fraud managers of a decade ago is the unbelievable amount of data and the wide variety of sources that we have today. It’s a flood. The only means we have to make sense of this data deluge is through algorithmic examination. Rules engines and neural networks are staple approaches. In recent years, application of artificial intelligence and the newer incarnation of machine learning (“let the computer figure it out based on all the data it sees”) has become a hot, and effective, area for fraud prevention. Only machines can find correlations among all that data in order to identify potent