I have to say it’s refreshing and exciting to see data analytics garnering more attention this year at the National ACFE conference!
In multiple breakouts I was hearing the same terms over and over: “Hadoop” , “Big Data”, “Unstructured Data”, “Video Analytics”. This is the cutting edge of fraud detection and I’m happy to see the ACFE embracing these topics.
Fraud analytics are not going away anytime soon. For as much as was mentioned at the June 2014 conference there are many other topics to be covered. From other analytic tools like R and Python, the use of Application Programming Interfaces (API’s) to analyze social media outlets like Twitter, Facebook and YouTube and diving even deeper into the mathematical theories used to detect fraud (beyond Benfords Law and into other mathematical models such as Levenshtein Distance, machine learning, etc).
For those interested in learning more in these areas I’ve put together some resources you can check out:
Websites:
Free Analytic Tools:
In multiple breakouts I was hearing the same terms over and over: “Hadoop” , “Big Data”, “Unstructured Data”, “Video Analytics”. This is the cutting edge of fraud detection and I’m happy to see the ACFE embracing these topics.
Fraud analytics are not going away anytime soon. For as much as was mentioned at the June 2014 conference there are many other topics to be covered. From other analytic tools like R and Python, the use of Application Programming Interfaces (API’s) to analyze social media outlets like Twitter, Facebook and YouTube and diving even deeper into the mathematical theories used to detect fraud (beyond Benfords Law and into other mathematical models such as Levenshtein Distance, machine learning, etc).
For those interested in learning more in these areas I’ve put together some resources you can check out:
Websites:
Free Analytic Tools:
- R http://www.r-project.org
- SQL Server Express http://www.microsoft.com/web/platform/database.aspx
- Python https://www.python.org
- Cynthia Hetherington @HetheringtonGrp
- Informs @Informs
- Big Data Science @analyticbridge
- Data.Gov @usdatagov
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