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 Data Mining and Analytics - Rich Lanza full day 7 CPE

1/24/2013 8:00 AM
1/24/2013 4:00 PM
UCONN Stamford |
Using Data Analytics for Maximizing, Errors, Fraud, and Cash Savings
This course gives you an understanding of the power of data analysis by providing a holistic approach using simple tools (like Excel).  Learn about useful tests in the areas of accounts payable, contract auditing, and the general ledger.  Also discussed are the different data analysis tools that are available as well as continuous monitoring applications.
Further, given Excel has permeated all of our business processes, Excel can also be an effective data analysis tool for auditing.  However, the mini-systems built in Excel can be rife with errors given the lack of software methodology, poor security, and ease-of-change that comes with the Excel territory. Learn some tricks to properly use Excel in auditing and also assess the risk of spreadsheet failure.
Lastly, finding errors, inefficiencies, and fraud is largely about understanding patterns, and making exceptions to those patterns stand out. Statistical analysis and transactional scoring are essential tools in that process of finding the needles in the haystacks. Another essential tool is graphing. In this course, you’ll learn how to translate unwieldy files of financial data, with tens of thousands of transactions ranging from $1 to $10 million, into a single compact scattergraph, pie chart, or overlay—and then to pick out the key items that merit sampling and follow-up. 
It is expected that after this seminar, each participant will understand:
·        How data analysis can work like magic to uncover fraud, errors, and cost recovery opportunities.
·        The various types of technology used to detect fraud with a focus on Microsoft Excel to facilitate explaining data analysis concepts.
·        Audit techniques to apply to Excel spreadsheets to ensure their validity.
·        How data analysis is used to query and mine data for gold in the areas of accounts payable and the general ledger.  Specific case studies will be reviewed and discussed.
·        The use of fraud scoring to flag suspicious transactions and minimize audit time.
·        The power of graphing and geo-mapping that can highlight key items for sampling and follow up.