Dear Walter Hugo Arboleda Mazo,

I am sorry that I have not any datasets you need since I am specialty in the field of finance.

Best regards,

Jung-Bin Su, PhD

Associate Professor, Department of Finance, China University of Science and Technology, No.245, Academia Road, Sec3, Nangang 115, Taipei City, Taiwan, ROC.

Phone: 886-2- 2786-4501 ext. 16. ; Fax: 886-2-27864534.

E-mail: [email protected]; [email protected]

If your question encompasses financial crime, then there are various techniques for detecting financial fraud using data mining.  Typically I use payment transactions data going through an organisation's accounts payable process (to suppliers) and payment transactions going through the payroll process (to employees).  I then set up various hypotheses about how fraud may have happened, usually in consultation with management using an action research approach (Kurt Lewin).  Mostly that requires adding further data sets such as GPS tracking data, cell phone data, building entry/exit data, CCTV etc.  Testing the data with those hypotheses often leads me to actual fraudulent transactions - sometimes different to what was expected under the initial hypotheses, but nearly always useful to management.  In the case of zero findings, that at least provides a degree of assurance that the fraud (probably) has not occurred during the period covered by the data.  The attached articles explain a little more fully.  Hope this helps.  

Article Sniffing out errors: increasing internal audit effectiveness...

Article Improving the bottom line: Achieving material cost recoverie...

Even though the hypothesis construction and testing approach I have described here relates to financial crime, I am sure it would be adaptable to non-financial crime.  There are multiple data sources available now which should assist early detection of crime.