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HPE launches Investigative Analytics, using AI and big data to identify risk
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February 12, 2016 Blogs big data

This article was originally published by techrepublic.com and can be viewed in full here

HPE recently announced a new software solution to identify risk and prevent fraudulent behavior within financial services and other industries. Here are the details.

On Tuesday, at the LegalTech Conference in New York City, Hewlett Packard Enterprise (HPE) announced a new software product called HPE Investigative Analytics, which enables businesses to identify risks and prevent fraud.

The software is initially geared toward financial services organizations, and it combines existing HPE products like Digital Safe, IDOL, and Vertica all on one platform. By using big data analytics and artificial intelligence, it can analyze a large amount of data and help pinpoint potential risks of fraudulent behavior.

According to HPE, the new software provides four key values to customers in the space:

  • Curated data lake
  • Machine learning-based analytics
  • Secure access with rationalized results
  • Models human behavior to measure risk and raise alerts

Robert Patrick, product manager for HPE, said that finding data on fraudulent activity, like LIBOR manipulation for example, was possible but challenging. 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.

Finding the big stuff is easy, Patrick said. In fact, he jokingly said they had gotten very good at finding customer complaints or employees having affairs. But, they wanted to find the smaller communication clues and connect the dots with problems that could arise. So, they’ve been working with a top tier US investment bank to look at identifying those issues.

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. It then applies analysis to query “aggressively and intelligently across all those data sources,” Patrick said.

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.

“Where are those needles in that haystack? Looking back through time, can I see behaviors that I have identified as anomalous as opposed to a baseline behavior going forward,” Patrick said.

All of this can be done in giant projects, but HPE wanted to make a tool that was able to be used regularly and not break the bank for the customers using it. Often, certain firms can provide this type of service, but they’ll charge by individual report and might not be available at the time customers need them.

According to an HPE press release, Investigative Analytics has a “200x greater hit rate on potentially risky information compared to any other compliance and risk management system of record.”

Investigative Analytics can be used to identify fraudulent behavior such as people acting on non-public information (like that regarding M&A activity), language around market manipulation, and employees spreading false information.

Patrick said it could be used to answer questions such as: “Are employees stealing information from your firm? Are they siphoning information before they move to a new firm?”

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