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DATA MINING DEPT OF EDUCATION & TRAINING PRESENTATION BY LEN STAFFORD MANAGER MANAGEMENT AUDIT.

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Presentation on theme: "DATA MINING DEPT OF EDUCATION & TRAINING PRESENTATION BY LEN STAFFORD MANAGER MANAGEMENT AUDIT."— Presentation transcript:

1 DATA MINING DEPT OF EDUCATION & TRAINING PRESENTATION BY LEN STAFFORD MANAGER MANAGEMENT AUDIT

2 DET CONSISTS OF SCHOOL EDUCATION TAFE NSW VETAB

3 BUDGET 2005/06 - $9.6 BILLION $6.6 BILLION – EMPLOYEE EXPENSES $1.5 BILLION – OTHER EXPENSES $1 BILLION – GRANTS & SUBSIDIES $293 MILLION – DEPRECIATION $237 MILLION – MAINTENANCE

4 PERMANENT PAYROLL 66,000 TEACHERS 3,000 STATE OFFICE EMPLOYEES CASUAL PAYROLL 26,000 CLAIMS WEEKLY NOW COMPUTER BASED

5 AUDIT APPROACH CONTINUOUS PAYROLL AUDITS HR LEAVE DATABASES ACCOUNTS PAYABLE REGULAR SCHOOL AUDITS PREVIOUSLY EVERY 2 YEARS NOW MORE FOCUSED

6 WHY GO TO DATA MINING?

7 WHICH PRODUCT DID WE CHOOSE?

8 WHY NETMAP ANALYTICS?

9 WHAT PROCESS DID WE FOLLOW WITH NETMAP? FRAUD RISK ASSESSMENT DEVELOPMENT OF SCENARIOS

10 SOME FRAUD RISKS IDENTIFIED? CLERK PAYS FICTITIOUS EMPLOYEE OR VENDOR (4.1, 4.2, 4.3, 4.4 & 4.11) PAYMENT TO NON-EXISTENT ADDRESS PAYING OVERTIME / HDA / TRAVEL EXPENSES WHILST ON LEAVE

11 RESURRECT FORMER EMPLOYEE (4.5.1 & 4.5.2) MISUSE SUPER USER OR CHANGE CONTROL ACCESS (4.16) CREATE PAYROLL GHOST (4.1, 4.2, 4.10, 4.12, 4.13, 4.14 & 4.15) RELATIONSHIP BETWEEN OFFICER & EXTERNAL PARTY (4.14)

12 SOME SCENARIOS: 4.5.2 PAYROLL USERS LINKED TO EX EMPLOYEES WITH BANK ACCOUNT CHANGES 4.6 EMPLOYEES RECEIVING LARGE PAYMENTS ($20K+) 4.10 STAFF NOT ON PAYROLL BUT RECEIVING PAYMENTS

13 4.11 MULTIPLE JDE VENDORS AT SAME ADDRESS (EACH $20K+) 4.14 ADDRESS LINKED TO EMPLOYEE & VENDOR 4.16 STAFF WITH HIGH CONNECTIVITY

14 FINDINGS TO DATE MAINLY COMPLIANCE ISSUES: ►CREDIT CARDS FOR FLIGHTS NOT UNDER GOVT CONTRACT ► POOR ALLOWANCES MGMT ► GST REQs NOT FOLLOWED ► ACCTS PAYABLE MGMT ► OVERPAYMENTS ► CONFLICTS OF INTEREST NETMAP HASN’T FOUND A FRAUD

15 IMPORTANT LESSONS MUST UNDERSTAND BUSINESS & SYSTEMS & RISK RISKS ENABLE DEVELOPMENT OF SCENARIOS & IDENTIFY DATA NEEDS NEED TO REVIEW FINDINGS

16 CONTINUE BRAINSTORMING ISSUES RAISED NOT TRADITIONAL. HOW DID WE COME ACROSS ISSUES? DATA MINING IS ONLY ONE TOOL

17 QUESTIONS?


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