| 9:00 |
THE DEDUCTIBILITY TEST: THINK LIKE AN IRB AUDITOR
- Section 33(1); Wholly & Exclusively; Business Vs Private/Dual Purpose; Revenue Vs Capital; Burden Of Proof; The Four-Part Defence: Purpose, Eligibility, Documents and Payment Trail
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| 9:45 |
STAFF COSTS, WELFARE & EMPLOYEE BENEFITS
- Staff Meals, Overtime Refreshments, Annual Dinners, Festive Celebrations, Farewell Events, Family Day, Wedding/Baby Gifts, Condolence Support, Angpows; HR Policy, Reasonableness, Payroll/Form EA Implications And Evidence | |
| 10.45 |
ENTERTAINMENT, CUSTOMERS, SUPPLIERS & PROMOTIONAL SPENDING
- Entertainment Definition; 50% Vs 100% Treatment; Client Meals, Gifts and Hampers; Cash Angpows; Supplier/ Vendor Spending; Separating Staff and Outsider Costs; E-Invoice and Attendance vidence | |
| 11.45 |
BAD DEBTS: WHEN A WRITE-OFF IS NOT ENOUGH
- Trade vs Non-Trade Debts; Irrecoverability; Recovery Efforts; Contemporaneous Evidence; Ageing, Reminders, Negotiations, Legal Steps and Approvals; Lessons From The Nam Leong Department Store Case. | |
| 12.35 |
PAYROLL, CASH WAGES & FOREIGN-WORKER RISK
- Genuine Employment Evidence; Payroll Trail; Cash Wage Red Flags; Permits and Manpower Agencies; PCB/MTD, Form E, EA and Employee Notifications; Reconciling HR, Finance, Tax and Immigration Records. | |
| 2:00 |
cont. PAYROLL, CASH WAGES & FOREIGN- WORKER RISK | |
| 3:45 |
REPAIRS, MAINTENANCE, RENOVATION & CAPITAL EXPENDITURE
- Repair vs Improvement; Initial Repairs; Replacement of Parts vs Entire Asset; Buildings, Vehicles and Equipment; Invoice Wording; Before/After Photos; Splitting Repair and Upgrade Costs | |
| 3:45 |
NON-DEDUCTIBLE & HIGH-RISK PAYMENTS
- Personal/Domestic Costs; Fines and Penalties; Bribes, Kickbacks and Unofficial Payments; Withholding-Tax Restrictions; Capital Outlay; Accounting Treatment vs Tax Treatment | |
| 3:45 |
AUDIT DEFENCE WORKSHOP: MAKE THE FILE SPEAK FOR IT SELF
- IRB Challenge Checklist; GL Coding; Approvals and Board Resolutions; E-Invoice Support; Seven-Year Record Discipline; Handling Arbitrary Add-Backs; Using Facts, Evidence and Professional Judgement When AI Answers are too General | |
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