Fraud Detection + Data Analytics = “FraudAlytics™”: The New Dark Art


Fraud Detection + Data Analytics = “FraudAlytics™”: The New Dark Art

Problem, what problem! The Fraud Landscape


During the current recession there are many issues that senior management have to deal with, which demand urgent attention.  Paradoxically, fraud prevention, detection and investigation seems to be pushed into the background despite:the expected increase of fraud.  


  • The fraud industry states that in a recession the amount of fraud is expected to increase.  However, there are no reliable indicators or measures of how much fraud is taking place, hence the creation of the National Fraud Reporting Centre.  Some commentators suggest that the majority of fraud goes undetected, and that the reported cases of fraud could account for as little as 10%.  KPMG’s 2009 fraud barometer reported that £1.1 billion of fraud came to Courts in Britain alone;

  • The UK Fraud Advisory Panel believes that between 75% to 80% of “reported and investigated” frauds involve an employee;

  • The American Association of Certified Fraud Examiners (ACFE), which has been conducting a survey every two years for the last decade, has identified a consistent trend that over 60% of frauds are identified either by accident or by a whistle blower, not by any internal controls or any form of pro-active measure;

  • An erosion of personal morality, ethics and corporate governance.  We live and operate in an increasingly materialistic environment, where mixed messages; huge city bonuses awarded to senior managers of failing companies, Ponzi schemes which promote on “get rich quick” schemes coupled with uncertainty over the future has led to a “get it while you can” culture where right and wrong issues are so grey as to be ignored.


Control Delusion


Senior management is faced with difficult choices as to where to allocate budgets and resources.  The argument for not investing in counter-fraud measures fosters a dangerous self-deluding belief that existing controls are adequate. These arguments include:


We haven’t had a significant problem in the past because:


  • We only employed trustworthy and honest people (HR estimate that over 70% of CV’s contain material inaccuracies; lies);

  • Internal Audit would detect any cases of fraud (Internal Audit specifically DO NOT look for fraud);

  • External Audit keep an eye open for fraud and irregularities (no they don’t, and who employees the External Auditors, Bernard Madoff selected a family run firm of external auditors based in a council house in north London to audit a world-wide financial empire)


Since we haven’t had any problems in the past, it is unlikely, given our internal controls and procedures, that there are any significant problems on the horizon.




While Data mining and data analytic techniques have been around for many years; I have been involved in this field for over fifteen years, they unfortunately are not used to their full extent.  Many organisations are still surprised, that after the fraud has been investigated; nobody spotted the warning signs.  As mentioned this may be due to the unconscious culture of corporate control delusion.


In most organisations the implementation of simple, data mining techniques to detect employee fraud, such as the deliberate abuse of expense allowances and the corporate credit cards can have a dramatic effect in keeping employees “on the straight and narrow”, and reducing inappropriate personal expenditure.  A client recently implemented our software solution, the Corporate Procurement Card Profiler (CPCP™), to detect unusual credit card transactions, and publicised its use to all employees, suggesting that perhaps they should review their expense claims before Internal Audit did.  Within four months of the system going live, the company received personal cheques from its employees for over £250,000, a fourteen fold return on investment.  Would there have been such a huge problem in the House of Commons if the expenses committee used similar techniques?


According to internal IT specialists, the comparison of internal data from different systems is difficult and time consuming and would detract from the implementation of the next generation of “Blue Sky” concepts.  Not much use if the company fails due to a massive fraud!  The benefit of such data mining can be vastly increased if internal data is compare against specialist external databases, such as HM Treasury’s list of sanctioned organisations or employees, or Companies House list of disqualified directors or “front companies” operating from virtual offices and accommodation addresses. 


The City of London is a financial powerhouse where ripples in one area can have a dramatic effect on the entire economy; the “Butterfly Effect”.  Self regulation requires budgets and a will to address the problem.  Perhaps it is time for FraudAlytics™ to be taken seriously and counter-fraud data analysis solutions to be embraced; not just as an insurance policy, but as an active way to improve corporate governance and make a financial difference to the success of the company.




Written for Haymarket by Richard Kusnierz, Divisional Director.

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