Part 3 in our series on Insights from the Vision 2016 fraud and identity track
Our Vision 2016 fraud track session titled “Deployment Made Easy — solving new fraud problems by Adapting Legacy Solutions” offered insights into the future of analytics and the mechanisms for delivering them. The session included two case studies, the first of which highlighted a recently completed project in which an Experian client struggling with rising application fraud losses had to find a way to deploy advanced analytics without any IT resources.
To assist the customer, data passing through an existing customer interface was reformatted and redirected to our Precise ID® platform. Upon arrival in Precise ID, a custom-built fraud scoring model was invoked. The results were then translated back into the format used by the legacy interface so that they could be ingested by the customer’s systems. This case study illustrates the key value proposition of Experian’s new CrossCoreTM fraud and identity platform. CrossCore features a similar “translation layer” for inquiries coming into Experian’s fraud and identity tools that will allow customers to define fraud-screening workflows that call a variety of services. The IT burden for connecting the inquiry to various Experian and non-Experian services will fall on Experian — sparing the customer from the challenge of financing and prioritizing IT resources. Similarly, the output from CrossCore will provide a ready-to-consume response that integrates directly with our customers’ host systems. The audience showed keen interest in the “here and now” illustration of what CrossCore will enable.
Our second case study was provided by Eric Heikkila at Amazon Web Services™ and focused on the future of analytics. For an audience accustomed to the constraints of developing advanced analytics in a rigid data-structure, Amazon’s description of a “data lake” was a fascinating picture of what’s possible. The data lake offers the simultaneous ability to accommodate existing structured customer data along with new unstructured data in an infinitely scalable data set. Equally important is the data lake’s ability to accommodate an unlimited array of data mining and analytical tools. Amazon’s message was clear and simple — the fraud industry’s trepidation around the use of big data is misplaced. The fear of making the wrong choice of data storage and analytical tools is unnecessary.
To illustrate this point, Eric shared an Amazon Web Services case study that used FINRA (Financial Industry Regulatory Authority). FINRA is responsible for overseeing U.S. securities markets to ensure that rules are followed and integrity is maintained. Amid a bewildering set of ever-changing regulations and peak volumes of 35 trillion per day — yes, trillion — Amazon’s data lake supports both the scale and analytical demands of a complex industry.
As the delivery and access to fraud products is made easy by CrossCore, the data and analytics will expand through the use of services like Amazon’s data lake. As the participants will agree, the future of fraud technology is closer than you think!