"Smarter counter fraud." That's the name of a new IBM initiative to tackle fraud by using big data analysis in tandem with hundreds of experts.
Fraud and financial crimes cost an estimated $3.5 trillion annually, according to a report from the Association of Certified Fraud Examiners. In its announcement Thursday, IBM said its new "holistic approach" includes Counter Fraud Management Software, which it described as an that uses the company's big data analytics to "prevent, identify and investigate suspicious activity."
This approach is intended to scour external and internal data sources for hidden relationships between entities, provide visualization of larger fraud patterns and employ machine learning to help prevent similar attacks.
IBM Red Cell
Another component of the initiative is a new counter-fraud intelligence task force, call IBM Red Cell. It will work with the company's X-Force unit, a research and development team that analyzes trends across industries for attack patterns.
New service offerings include Outcome-based Accelerators, where an organization's ability to counter fraud is evaluated and a rapid prototype of measures is provided. A Target Operating Model can be generated, which proposes the organizational and technology structure best able to detect, respond to and investigate fraud. A Scale and Manage phase, the company said, can provide fast implementations.
Analytics are conducted in the , and the initial focus will be on medical fraud, insurance claim fraud, public tax fraud and occupational fraud. The IBM Fraud Asset Management System is used to discover medical fraud, the Loss Analysis and Warning System detects insurance claim fraud, and the Tax and Audit Compliance System addresses public tax fraud for governments.
This counter-fraud-as-a-service includes hosting, application management, behavior modeling and scoring, and analytics and referral generation, using a subscription model.
'A Large Opportunity'
Chris Christiansen, an analyst with industry research firm IDC, told us that "the level of fraud and waste in a lot of industries represents a large opportunity" for IBM. He noted that "anti-fraud was featured in a lot of services engagements [from the company,] but now it's a key focus."
There wasn't "any mention of Watson" in the announcement, Christiansen pointed out, referring to the IBM supercomputer whose greater-than-human intelligence is now being applied as a service to various fields, including medical diagnosis. He described Watson as "very interesting in terms of big data and predictive analysis," and said he expected Watson to be a component of these anti-fraud offerings in some fashion.
In a post last month on its corporate blog, industry research firm predicted that a quarter of large global companies would adopt big data analytics for at least one security or fraud detection incident by 2016. That compares with only 8 percent of global companies doing so today, and Gartner said such big data analytics would show a positive return on investment within the first six months of implementation.
Gartner Vice President Avivah Litan noted on the blog that companies can "cut down on the noise and false alerts in existing monitoring systems by enriching them with contextual data and applying smarter analytics." Big data analysis, she said, also enables the detection of patterns, the pooling of internal and external data in one place, and the ability to find "anomalous transactions" when compared against user profiles.