Most fraudulent activity goes untried. In many cases, it goes undetected. The cost of that fraud is often passed on to customers, constituents or owners in the form of higher fees, increased taxes or lower margins. It doesn’t have to be that way.
Reliably predict the likelihood of fraud activity before it is authorized? In real time? John Geurts, the Executive General Manager for Group Security and Chief Security Officer for the Commonwealth Bank Group in Australia, will walk you through the processes and technology.
There are only about 1.5 billion people who have direct access to financial services, making m-payments an attractive alternative to brick and mortar banks. And those with no access are not the only ones who will be attracted: M-payments will be enticing to criminals and criminal organizations as a means to launder money and transfer illicit value.
A recent study conducted by the Coalition Against Insurance Fraud and SAS points out that a major challenge in detecting organized insurance fraud is ensuring claims are not viewed in isolation. Insurers need good data for this. Dennis Toomey discusses requirements for a technology-based fraud detection solution.
Representatives from property and casualty insurer CNA, Los Angeles County and health systems consultant OptumInsight painted a bleak picture about fraud in their industries. Numbers like $30 billion were suggested, and that was just insurance fraud.
Today’s fraudsters always seem to be one step ahead of investigators, so John York, Doris Wong and Dan Zaratsian from SAS wrote a SAS Global Forum paper to show that fraud investigators CAN get the upper hand. In this post, you get the paper and additional information from John York in a video interview.
Ellen Joyner says there are three ways banks can use analytics to identity and stop fraud while improving the customer experience. See if one of these will remove your roadblock.
With many insurers pursuing an analytical fraud detection solution, a common question arises: Buy a solution or build one internally?
Some organizations have leveraged statistical software and internal experts to build their own fraud detection models. But building models is only half the battle. This post will review the factors to consider when implementing a fraud detection model.
In today’s world of cybersecurity threats, fraudsters use social media to gather personal information and target vulnerable places within your organization. The criminals have no boundaries when securing illicit funds and then funneling them through financial institutions disguised as legitimate financial transactions and eventually sending wires to offshore accounts.