Posted 2/17/2016 9:05:32 AM by RICHARD HARRIS, Executive Editor
Hewlett Packard Enterprise (HPE) had released HPE Investigative Analytics, a new hosted software solution that enables highly regulated organizations to identify and analyze risk events, and take action to prevent them.
HPE Investigative Analytics helps identify and stop fraudulent and non-compliant behavior. It utilizes HPE's software assets in archiving, compliance, and machine learning to automatically detect patterns and anomalies in structured and unstructured data, in order for an organization to shut down bad behavior before it becomes an issue.
The key capabilities of HPE Investigative Analytics include:
- Unique Assets in Archiving, Big Data, Compliance, and Machine Learning Software: HPE Investigative Analytics brings together HPE Digital Safe, HPE Supervisor, HPE IDOL and HPE Vertica to automatically detect patterns and anomalies by analyzing both structured (e.g. trading systems, risk systems, pricing systems, directories, HR systems, etc.) and unstructured data (e.g. voice, chat, email).
- Curated Data Lake: Enriches information from disparate data sources (i.e. email, IM and voice archives, etc.) as well as structured data from trading, risk, market, and surveillance systems to provide a single view across both structured and unstructured information -- regardless of source.
- Machine Learning-Based Analytics: Leverages investigative analytic human behavior models to measure risks and flag potential problems identified by connecting to business and market activity feeds and scores information against these events using a series of Key Risk Indicators (KRIs).
- Secure Access with Rationalized Results: Secures, audits and streamlines access to every drop of the data lake while utilizing the capabilities of HPE IDOL and HPE Vertica to synthesize, analyze and produce actionable insights.
- Models Human Behavior to Measure Risk & Raise Alerts: Connects to business and market activity feeds, such as trade alerts, market events, or research publications, and retroactively scores content against these events using a series of KRIs. HPE Investigative Analytics uses a variety of out-of-the-box or user-defined KRIs, which vary from a lexical analysis of terms such as mentions of the company near opinions derived from sentiment analysis - "I'm bullish on the bond market" - to more complex language models looking for potentially manipulative language.
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