The Aberdeen Group has a new research report out on Fighting Fraud with Big Data Visibility and Intelligence.
The report includes a useful review of the risk and cost of fraud. (Note that it errs when it refers to ‘tips’ as being external: these are typically calls to the internal compliance hotline or whistleblower line.)
What is new in the report is the discussion of the ability to mine the mass of Big Data, perhaps with predictive analytics, to understand and assess fraud risk, and also to monitor for red flags that indicate an investigation is warranted. As the report says:
“Rapid changes in information technology infrastructure are increasing the difficulty of maintaining high levels of preparedness simultaneously against all threats. In response, organizations are adopting enhanced strategies for fighting fraud: from 100% success at prevention, to greater visibility, faster detection and incident response; from “figure out what already happened” using post-incident forensics, to proactively “figuring out what’s happening” using Big Data and predictive analytics.”
Unfortunately, Aberdeen’s research showed that only about 16% are using predictive analytics for the detection and prevention of fraud.
Why is this? I suggest it’s from one or more of these factors:
- Those responsible for fraud prevention/detection are not aware of the capabilities of the new technology
- Those responsible for fraud prevention/detection are (justifiably or not) content with the ‘older’ technology
- Priority and/or resources are not given to fraud prevention/detection
I welcome your views.
