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Just over the past few weeks I saw three headlines in The New Zealand Herald that caught my eye:
In 2014 the Serious Fraud Office (SFO) estimated that total fraud loss in New Zealand was between a staggering $6.1 and $9.4 billion. 55% of fraud happened in the private sector with an estimated $1.2 billion in wholesale/retail trade & accommodation and $1.1 billion in manufacturing & construction. The public sector accounted for an estimated 38% of which tax fraud alone is c. $2.0 billion (followed by $567 million for health and ACC).
An expert, in that same article, said that in general economic crime is estimated to be between 3 and 6% of an organisations revenue. Research shows that since 1984 the average SFO case investigated had an economic crime value of $2.9 million. Now do the maths and ask yourself if you have done everything you can to prevent and detect economic crime within your own organisation...
Detecting fraud is not easy, but there are indicators. AccountingWeb has a list of 20 indicators that may help you to detect fraud. Although the feature is over a decade old, it still applies today and especially might help you detect fraud in smaller businesses. It ranges from identifying unusual behaviour and reconciliation issues to ghost employees and inventory shortages. Analysing monthly accounts in detail for example can help you to detect abnormalities. Have a chat with your accountant if you are unsure about certain transactions or increases/decreases in some line items.
For large enterprises there is a whole range of other solutions available. Just Google "fraud detection software" and you will find a range of solutions out there that may help you to prevent and identify suspicious events and mitigate associated risks. Some are industry specific and others add-ons of ERP systems.
If you are considering investing in analytics, I recommend you to have a look at IBM Watson. Content analytics (based on natural language processing and machine learning) will not only help you to improve your competitive positioning in terms of customer and business insights, but also applies to crime analytics (investigation analytics, incident management, and cyber crime investigation), healthcare (fraud detection and prevention), insurance (risk assessment, fraud detection, claims analysis, payment validation, and loss review), and finance (anti-money laundering, internet banking fraud, and risk management and compliance).
If you are not familiar with machine learning (which is a subset of artificial intelligence), have a look at Coursera. This course is from Stanford University.
And if you don't want to be the next headline in the news or become yet another statistic get in touch with CBA Strategic IT.
Title quote from Greek dramatist Sophocles (496-407 BC) and image from 123rf.com (royalty free stock photos).