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ISMG: 2016 Faces of Fraud: The Analytics Approach to Fraud Prevention

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Published on : Jul 19, 2019

2016 Faces of Fraud – 
Some alarming statistics about current fraud trends:
• 74 percent of respondents say the number of fraud incidents has remained steady or increased in the past year
• 70 percent say total fraud losses have also remained steady or increased
• 52 percent say it can take days or weeks before a fraud incident is detected

The forms of fraud are consistent from year to year, with payment card, skimming attacks and account  takeover taking the top spots. With a nod to participation from government agency respondents, information theft and insider fraud also rate highly among the most common schemes.

Oddly, 21 percent of respondents say they did not detect any incidents of fraud in the past year. The operative word there may be “detect.” It isn’t necessarily that fraud did not occur, but rather the respondent organizations’ people or systems failed to spot the scams.

But, of course, fraud is about far more than financial losses. Asked about non-financial impact, 45 percent of respondents say they have seen a loss of productivity due to incident response, while 44 percent report a reputation impact. Thirty-one percent say they have seen customers close their accounts and take their business elsewhere.

Those stats form the foundation of these conclusions:

1. It’s About Detection

2. New Tools Needed

3. Help Wanted: Educated Users to Deploy the Tools

    My organisation’s data access is through:
    ERPExcel files / AccessEmailsLog Books/ Hard CopiesCustom application (Please specify)

    My organisation is looking for a Data Quality & Integration solution that will help us:
    Address Data Quality issue and turn information in to mission critical intelligence for strategic business decisionsFetch departmental data from various 'source' systems to create a single version of truth

    Which of the challenges are you facing in your organization? (Tick ALL applicable points)
    Unable to tap into big data to surface unexpected insights for effective decision making`Lacking the ability to interact with data in a graphically driven, intuitive manner to identify new relationshipsUnable to interact with information on mobile devices for offline decision making


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