![]() ![]() Then, it creates a behavior model on top of that analysis to look at certain communication types and see if they can define a certain problematic behavior and map back to a particular historical event, so they can look out for that type of communication in the future. It then applies analysis to query “aggressively and intelligently across all those data sources,” Patrick said. Investigative Analytics starts by collecting both structured sources like trading systems, risk systems, pricing systems, directories, HR systems, and unstructured sources like email and chat. So, they’ve been working with a top tier US investment bank to look at identifying those issues. But, they wanted to find the smaller communication clues and connect the dots with problems that could arise. In fact, he jokingly said they had gotten very good at finding customer complaints or employees having affairs. ![]() Previous technology was centered around monitoring and surveilling what people were talking about, but it couldn’t identify many of the minor details that pointed to the fraud.įinding the big stuff is easy, Patrick said. Robert Patrick, product manager for HPE, said that finding data on fraudulent activity, like LIBOR manipulation for example, was possible but challenging. #Sookasa mac download how toSEE: Compliance could kill your cloud deployment: Here’s how to handle it
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