Big Data Analytics & Fraud Detection
Fraud Summit - San Francisco 2014 - Banking institutions create and store volumes of data, but integrating and applying that information in a meaningful way has proved challenging. Register for this session to learn first-hand from bit data and analytics experts:
See Also: Mitigate Risks and Protect Your Users from Cyberattacks, Avoid the Yahoo Data Breach
- How big data is being used to analyze and detect fraud trends;
- The new strategies and skills needed for big data analytics;
- The latest technology solutions and how they can serve your business needs.
Organizations today suffer from data overload. Multiple information systems deliver mountains of data about the latest threats, anomalous activities and potential security incidents. But without the proper capabilities, organizations are unable to correlate and analyze this data, then put it to use in a quick, responsive manner.
In fact, in ISMG's latest Faces of Fraud survey, 36% of respondents say difficulty integrating data is their biggest challenge to fraud prevention. And big data analytics is #3 among top anti-fraud investments planned for next year.
But it isn't just a matter of lacking the latest and greatest tools. To analyze big data properly, organizations also need the right mix of strategies, policies and skills.
Allison Miller of Electronic Arts and Russell Thomas of Zions Bank are two pioneers in the emerging field of big data analytics. They are joined here by Andreas Baumhof, Chief Technology Officer of ThreatMetrix, to discuss:
- Hype vs. Reality of Big Data - A business perspective on how to get started
and how to succeed;
- Operating with Big Data - Implementing a Big Data-driven fraud prevention strategy;
- The Importance of Automated Models - Without a well-thought model, the data is meaningless.
ISMG's Fraud Summits are one-day events focused exclusively on the top fraud trends impacting organizations and the mitigation strategies to overcome those challenges.
All 2014 Fraud Summit San Francisco recordings:
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