January 9, 2013
NICE Systems (NASDAQ: NICE)
today announced the launch of its Contact Center Fraud Prevention solution, which tracks fraud patterns and screens all phone interactions for fraud against a watch list of known fraudsters. The solution brings together NICE Actimize's extensive expertise in fraud with NICE's years of experience in the contact center. The solution can be deployed as a standalone contact center solution or as part of the NICE Actimize enterprise fraud offering.
Organizations can reduce fraud-related losses without creating service hurdles or compromising customer experience by adopting a multi-layered approach, which includes non-intrusive voice biometrics technology, speech and transactional analytics, and real-time capabilities.
Aite Group claims that fraud in the contact center is on the rise and, while many businesses have recognized the need to protect customer data and secure online transactions, the phone channel has become a target for fraud. Datamonitor estimates that 20 percent of people who are defrauded will leave the institution at which this occurred.
Fraudsters often use social engineering by leveraging information available on social networks, enabling them to manipulate and trick customer service agents who continue to verify caller identity through traditional means.
"Preventing fraud losses and protecting clients' personal information are essential goals for enterprises and contact centers. Unfortunately, most agents do not have tools to help them identify fraudsters, which puts the enterprise and customers at risk," said
, President, DMG Consulting LLC. "Social media represents a goldmine for fraudsters. Almost every person has a digital footprint, which can be mined for nefarious purposes. Every public and private organization needs to equip their agents and other employees with tools and best practices to prevent losses."
NICE's Contact Center Fraud Prevention solution enables businesses to pinpoint fraudulent callers according to their unique voice print by using voice biometrics to automatically cross-reference each call with a suspicious watch list of known fraudsters. The solution also implements NICE Interaction Analytics to identify fraud patterns and social engineering attempts based on speech analytics, emotion detection, talk patterns, and interactions. For example, shouting at the agent or trying to change an address or phone number could be part of a fraudulent behavior pattern, and certain keywords may raise a red flag. Telephony and other contextual data, such as IVR events, caller location and ANI matching, also known as caller ID, are also examined to determine potential fraud.