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One in five survey respondents don’t use analytics or rare event modelling in anti-fraud programs: Deloitte


December 17, 2015   by Canadian Underwriter


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One-fifth (20.8%) of respondents to an online survey released earlier this week by Deloitte LLP don’t use analytics or rare event modelling in their anti-fraud programs.

The poll of more than 3,600 professionals – during a Sept. 22 webcast titled Managing fraud in the digital era: Channeling faint signals amid the noise – also found that 24.9% of respondents said that fraud is expected to increase during the next year and 31.4% said that fraud became tougher to detect during the past year. Respondents worked in a range of industries, including commercial and industrial products (32.5%), financial services (27.5%) and technology, media and telecommunications (9.6%), Deloitte noted in a press release. [click image below to enlarge]

Only 5.2% of respondents said that they were confident in their organization’s use of fraud analytics

Findings indicate that the biggest challenges to using fraud analytics effectively are lack of resources (29.6 percent); treatment of fraud analytics as an IT issue, not an organizational priority (15.1 percent); and inability for leadership to understand the value (10.5 percent).

When asked how confident they were in their organization’s use of fraud analytics, 35.8% of respondents didn’t know/NA. Only 5.2% said they were very confident (analytics tools scour dark data and rare event modelling is used; 15.1% were confident (analytics tools scour all but dark data and rare event modelling is used); 23.1% were somewhat confident (analytics tools scour some dark data (not dark data) and rare event modelling is not used)); and 20.8% were not confident (neither analytics tools nor rare event modelling are used).

“When done well, analytics and rare event modelling accelerate fraud prevention and detection efforts,” said Kirk Petrie, Deloitte Advisory principal in advanced analytics, Deloitte Transaction and Business Analytics LLP, in the release. “Good execution often involves executive leadership, legal, finance, risk, compliance – along with data scientists – so that faint signals of fraud can be identified and organizational improvements made. Unfortunately, few companies currently involve data science in their compliance directorates.”

Shuba Balasubramanian, another Deloitte Advisory principal in advanced analytics, added that “fraudsters are getting smarter, but tools to identify schemes earlier are advancing, too,” but the company sees increasingly more organizations using advanced analytics for rare event modelling. “Identifying anomalies – possibly fraud, waste, or abuse – earlier than ever before can help stem financial losses and negative brand impact.”


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