Argyle Data: Real-Time Analytics Mitigates Risk

CIO VendorTom Ryan, President & CEO
“When minutes mean millions; react in seconds when your data is most valuable”–Fighting risk is a continuous battle, and reducing the time window of opportunity transforms the possibilities for risk mitigation. Explaining about the new era in real-time analytics and data management, Tom Ryan, President & CEO, Argyle Data says, “We are building innovative technologies to help companies around the world gain faster insight and business value from their Big Data in real time.”

Argyle Data uses state-of-the-art machine learning on a Hadoop stack reducing the window for risk or fraud from hours to minutes

Traditional analytics approaches are batch oriented bringing together a patchwork quilt of database technologies, ETL, and BI tools. Most risk applications based on a previous generation stack, come with a high cost database infrastructure. This patchwork quilt often necessitates in a long wait for nightly ETL and transformation jobs to be completed to give insights that are hours or days out of date. Headquartered in San Mateo, CA, Argyle Data uses state-of-the-art machine learning on a Hadoop stack to deliver risk applications that can ingest data and analyze it in real time, reducing the window for risk or fraud from hours to minutes.
Data-driven companies have a common set of requirements for real time risk analytics. Argyle Data’s real-time data analytics transforms enterprises from a reactive to proactive state. The ingesting tool, ArgyleDB Ingest gets the whole story in real time by intelligently ingesting packets at the network level non-invasively. ArgyleDB Query is a native Hadoop real-time SQL database that queries the data lake in parallel across 1000’s of nodes and joins network data to business data interactively.ArgyleDB Search offers native Hadoop real-time full-text search across any key or value in the data lake without the need for a prior index table. The connected graph search in ArgyleDB Graph for instance, searches for related people involved in a fraud ring. ArgyleDB Machine Learning offers native Hadoop machine learning for anomaly detection, clustering, classification and regression.

Working with some of the biggest companies in the world from the fields of mobile communications, e-commerce, and finance, Argyle Data’s simple queries and machine learning at petabyte scale can guide a user to identify existing fraud and new fraud as it is emerging. The key factor in fighting risk in the mobile space is in reducing the time window risk coefficient. In 2013 the mobile communications industry saw a 15 percent increase in fraud from that of 2011, losing $46.3 billion in the process. Fraud occurs in many forms–Wangiri, SMS phishing, roaming, premium rate service, international revenue share, to name a few. For Argyle Data customers, the rationale behind the savings of more than $1 million per month in a typical operating company or country is the ability in detecting all kinds of frauds in real time as opposed to a day later.

“Risk and fraud is strategic to security on a global scale. We intend to take our unique approach to machine learning risk applications on a Big Data stack to additional customers in the U.S. and Europe and plan to continue our expansion throughout these regions and into Asia over the next few years,” adds Ryan.

Argyle Data

San Mateo, CA

Tom Ryan, President & CEO

Delivers insights and business value from Big Data in real time.