"The issue around identifying targeted analysis for anti-corruption is you just can't look at one data source," says Vince Walden, a partner at Ernst & Young with responsibility for fraud investigation and dispute services. "When you're looking for potentially improper payments that could be
With big data financial and transactional data no longer in silos, we can now look at them together. Vince Walden, Ernst and Young partner, says that big data technologies allow them to look at data from all angles.
The organization that can quickly extract insight from their data AND leverage the data achieves an advantage. Rick Clements, IBM's director of marketing for Big Data says, "we are moving from the notion of big data to fast data, where what really matters is speed...and real-time actionable insight
Ernst & Young (EY) uses IBM BigInsights platform to leverage big data and analytics to combat fraud. By running test queries across multiple transactions they can identify fraudulent transactions and mitigate risk for its customers.
Seeing is believing. In this short demonstration, you will see the innovations announced in the prior session in action. You will see integration and governance applied to one of the most popular big data use cases: an extended 360 degree view of the customer.
The era of big data is the era of messy data. This is the big data paradox: larger volumes and variety of new sources are inherently complex, and that complexity can actually lower confidence. Organizations have created an entire role to raise confidence in big data: the chief data officer.
Are you confident in the analytic insights that drive your business? Do you trust big data? Can you protect it? IBM can help with new innovative information integration and governance (IIG) capabilities to build confidence in big data.
Success with big data comes down to confidence. Without confidence in the underlying data, decision makers may not trust and act on analytic insight. Without confidence in your ability to deploy new big data technology and the skills to exploit it, you might defer on big data projects.
The promise of big data and analytics is revolutionary and exciting. But, to truly make big data a big deal requires confidence in your data. Learn how two teams tried to use analytics to fund a an enterprise project with dramatically different results. Discover how one went wrong and how the other