1. Corporate Collapse “Virtually nothing is to be learned from studying individuals involved in corporate failures, no matter how exciting their lives may be.” Frank Clarke and Graeme Deane

2. Classic Symptoms Preceding Collapse or “I reallly should have known”. Overstatement of the value of assets, and understatement of liabilities in financial reports. Use of related party transactions to disguise the reality, e.g. to create a false impression about earnings.

3. continuing financial losses and cash flow deficiencies weak management inadequate management succession planning looming debt payments & concealment of bad debts inadequate capital expenditure programs lack of adequate information systems shareholder disputes

4. See also Clarke and Deane p 149-151 declining sales or margins & attempts to increase market share at expense of profits delays in financial reporting over-leveraged capital structure high-cost debt negative publicity in the financial and business communities deterioration in asset quality and values leading to reduced liquidity

5. Vulnerability of accounting standards to manipulation Capitalising expenses, e.g. interest charges and taxes (Rolls Royce in 1970s) Use of accounting fictions such as Future Income Tax Benefits (able to be written off by Bond Corp in the 1980s and HIH recently) that are in accord with Accounting Standards.

6. The remedies do not treat the disease Corporate governance theory has concentrated on producing transparency and accuracy through greater compliance with existing rules. Clarke and Deane argue that the rules are the problem - at least in accounting.

7. An example: the audit committee The audit committee, composed of non-executive directors, should ensure compliance with Accounting Standards. But a purely technical compliance with the Standards ensures that accounts are regarded by auditors as true and fair, even if in the professional judgment of the auditors they are not. So compliance does not guarantee transparency. There is no true and fair override on data quality.