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Data Analytics. Updated: 3/6/2013. Agenda. About Us Define Data Analytics Data Diagram Tools to Analyze Data ACL Demo AP Testing Case Study SQL Demo SAS Demo JE Analysis Questions. Updated: 11/10/2010. Introductions. Aaron Wilton Maria Hao. Education Colorado State University
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Data Analytics Updated: 3/6/2013
Agenda About Us Define Data Analytics Data Diagram Tools to Analyze Data ACL Demo AP Testing Case Study SQL Demo SAS Demo JE Analysis Questions Updated: 11/10/2010
Introductions • Aaron Wilton • Maria Hao
Education Colorado State University Bachelor Degree in: Accounting & Computer Information Systems Colorado State University Master of Accountancy Work Experience Deloitte (AERS Advisory) Certification CPA CISA Aaron Wilton
Education Jiangxi University of Finance and Economics, China Bachelor Degree in: Accounting University of Denver Master of Accountancy Work Experience Prior to Deloitte Deloitte (AERS Advisory) Certification CPA CISA Yuhua (Maria) Hao
Data Analytics • What is Data Analytics?
Data Diagram Database #2 Database #1 Process Application (front-end): PeopleSoft, SAP, and some reporting tools (e.g., Essbase, Business Object), etc. Database (back-end): SQL, Oracle, etc. Interface: BizTalk, webMethods, etc.
Tools to Analyze Data MS Excel MS Access SQL Server Management Studio Audit Command Language (ACL) SAS Others
ACL Demo How to import data How to use the basic functions to run queries Advantage of ACL: • Cannot change the raw data • Log all the procedures performed
Accounts Payable Testing Case Study Background: XYZ Corporation is a manufacturing client with offices at multiple locations. We have been engaged to provide services to the internal audit function of XYZ Corp. The client recently acquired a new business unit and is facing issues integrating the financial systems from the newly acquired business. The client is particularly concerned that these issues could be more significant around accounts payable processing and supplier master maintenance and could result in missing or invalid information or duplicate disbursements that might have been made due to lack of controls. The client is also unsure whether the user rights are properly set up to access/update various files. The internal audit function does not currently have the skill set to develop the data analytics that might help them better gauge the extent of the problem and the client has reached out to us for help. They would like us to test vendor master data and transactional information for the period starting 01/01/2009 to 12/31/2009.
AP Risk Brainstorm Disbursements Vendor Master File Maintenance Open AP Other Fraud Risks
AP Risk Brainstorm Disbursements • Duplicate payments • Inappropriate access • Active vendors only • Reconcile to authorized invoices • Timely (i.e. after invoice receipt) Vendor Master File Maintenance • SOD relative to disbursements Open AP • The Company’s Credit rating Other Fraud Risks • Sequential checks • Fictitious vendors
SQL Demo Join several tables in the same time Deal with complicated calculations
SAS Demo Benefits • Leaves Original data set untouched • Documented steps/procedures Disadvantages • Complicated, Steep Learning Curve
Journal Entry Testing Entries made to unusual accounts • Purpose: To identify entries made to unusual accounts. • Logic: Performs word search within the account description field for the keywords specified in the AIF Users with few postings • Purpose: To identify users who posted less than X nonstandard entries or X standard entries during the period under review. • Logic: Total number of entries posted by each user for each type of population are calculated. • Users with less than the specified number of entries in the AIF are flagged. • Output: User analysis tab
Journal Entry Analysis • Entries posted on holidays or weekends • Purpose: To identify entries posted on Saturdays, Sundays, or holidays. • Logic: Finds entries with a posted date that occurs on Saturdays, Sundays, or holidays. • The option to search for Saturdays, Sundays, or holidays is specified in the AIF • Output: Output contains entries flagged for each Saturday, Sunday, or holiday specified Large debits to revenue at the beginning of a quarter • Purpose: To identify journal lines that debit revenue for more than $X that were input and effective within the first Y days of a quarter. • Logic: • Finds all the journal lines that: • Were posted to accounts that are mapped to account subtype “Revenues”
Questions ???