Corporate Scandals

1
Corporate Scandals Lessons Learnt
Professor Gillian Yeo
Executive Vice Dean Dean (Degree
Programs) Nanyang Business School Nanyang
Technological University Singapore
2
Corporate Scandals Lessons Learnt

• Responsibility for detecting and preventing
  corporate scandals
• Expectation gap and auditors role
• Positive approach vs negative approach
• Professional Skepticism

3
Suppliers Facilities
Customers
Complements
Other Information Providers
Culture
Competitors
Suppliers Inventory
Core
Brand Image Delivery
Strategic Partners
Strategic
Suppliers Labor
Business Processes
Product - Service Delivery
Customer Service Delivery
Management
Resource Management Processes
Human Resources
Property Management
Regulatory Management
Regulators
Suppliers Capital
Information Management
Financial/Treasury Management
Process
Objectives Tactics
Structure Activities
Capital Markets
Financial Statements
Accounting Transactions
Generally Accepted Acctg. Principles
External Auditor
External Auditor
SSA Audit
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The Fraud Triangle

• Three conditions are present when fraud occurs

• Incentive/ Pressure
• Reduce earnings volatility
• Support or increase stock price
• Increase earnings-based incentive compensation
• Meet analysts forecasts

• Opportunity
• Absence of controls
• Ineffective controls
• Ability of management to override controls

• Rationalization/ Attitude
• Consistent with personal code of ethics to commit
  dishonest act

Adapted from SAS99
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Earnings Management to Avoid Losses
No. of Firms
Change in EPS (1974-1996) (cents)
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Fraudulent Financial Reporting

• Recognition of premature or fictitious revenue
• Aggressive capitalization and extended
  amortization policies
• Misreported assets and liabilities

7
Premature or Fictitious Revenue

• Goods ordered but not shipped
• P. Inc - ambitious sales targets, predating
  packing lists, shipping records, invoices
• Goods shipped but not ordered
• BS. Corp meet or exceed sales targets,
  commercial warehouses leased and unsold goods
  shipped there credits later issued and goods
  resold to different customers

8
Premature or Fictitious Revenue

• Cover-up activities CB Corp 1991

Bought 975k goods Paid 975k
CB Corp.
975k goods shipped back
Sold 975k goods
Paid 975k to Cambridge
Third Company
975k to Distributor to pay Cambridge
Distributor
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Detecting Premature or Fictitious Revenue

• Understand the policy for revenue recognition
• Is revenue really earned? Informatics and
  recognition of international student revenue
• Is there right of return or price protection?
• Sales agreement side letters

10
Detecting Premature or Fictitious Revenue

• Service revenue finance-related income
• Y Corp sales type lease accounting
• Gross Profit PV of lease payments cost to
  manufacture
• Used low interest rates to obtain high PV of
  lease payments
• But Latin American sales high inflation high
  interest rates should be used

11
Detecting Premature or Fictitious Revenue

• Watch accounts receivable or other accounts used
  to offset premature or fictitious revenue

CMD Corp., Selected Quarterly Account Balances Statistics, Years Ending June 30, 1993 and 1994 (000) CMD Corp., Selected Quarterly Account Balances Statistics, Years Ending June 30, 1993 and 1994 (000) CMD Corp., Selected Quarterly Account Balances Statistics, Years Ending June 30, 1993 and 1994 (000) CMD Corp., Selected Quarterly Account Balances Statistics, Years Ending June 30, 1993 and 1994 (000) CMD Corp., Selected Quarterly Account Balances Statistics, Years Ending June 30, 1993 and 1994 (000) CMD Corp., Selected Quarterly Account Balances Statistics, Years Ending June 30, 1993 and 1994 (000) CMD Corp., Selected Quarterly Account Balances Statistics, Years Ending June 30, 1993 and 1994 (000) CMD Corp., Selected Quarterly Account Balances Statistics, Years Ending June 30, 1993 and 1994 (000)
Fiscal Year 1993 Fiscal Year 1993 Fiscal Year 1993 Fiscal Year 1993 Fiscal Year 1994 Fiscal Year 1994 Fiscal Year 1994
Sept. Dec. Mar. Sept. Dec. Mar.
Revenue 7,564 8,173 8,237 9,315 10,212 11,341
Percent increase from prior quarter _ 8.1 0.8 3.1 9.6 11.1
Accounts receivable 8,449 9,916 10,531 12,647 16,997 19,386
Percent increase from prior quarter _ 17.4 6.2 2.5 34.4 14.1
A/R days 101.9 110.7 116.7 123.9 151.9 156.0
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Detecting Premature or Fictitious Revenue

• Watch for steps taken to thwart detection
• Transfer from accounts receivable to plant,
  property and equipment or other assets
• Evaluate relationships, rate of change in account
  relative to rate of change in revenue
• Compare with industry norms and competitors

13
Detecting Premature or Fictitious Revenue

• Consider physical capacity
• Fictitious warranty repair claims of mobile
  phones
• Sales increased significantly
• Volume of handphones serviced - significant
  increase - unrealistic compared to companys
  capacity

14
Detecting Aggressive Cost Capitalization Policies

• Software development costs

Software Development Costs Capitalized Expensed AS Inc., Years Ending April 30, 1998-2000 (000) Software Development Costs Capitalized Expensed AS Inc., Years Ending April 30, 1998-2000 (000) Software Development Costs Capitalized Expensed AS Inc., Years Ending April 30, 1998-2000 (000) Software Development Costs Capitalized Expensed AS Inc., Years Ending April 30, 1998-2000 (000)
1998 1999 2000
Total capitalized computer software development costs 8,827 10,902 11,066
Total research development expense 12,112 11,511 9,055
Total software development costs 20,939 22,413 20,121
Costs capitalized as percent of total costs incurred 42.2 48.6 54.9
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Detecting Aggressive Cost Capitalization Policies
and Extended Amortization Periods

• Z com manipulated E/R ratio (line cost expense
  to revenue) to maintain at previous reported rate
• Industry-wide declines in telecommunications
• Z com had notably better E/R ratio than its peers
• Competitors had taken impairment charges but Z
  com did not write down business goodwill

16
Detecting Misreported Assets and Liabilities

• Overvalued assets/Undervalued liabilities

Selected Income Statement Balance Sheet Amounts with Related Statistics G Inc. (000) Selected Income Statement Balance Sheet Amounts with Related Statistics G Inc. (000) Selected Income Statement Balance Sheet Amounts with Related Statistics G Inc. (000) Selected Income Statement Balance Sheet Amounts with Related Statistics G Inc. (000) Selected Income Statement Balance Sheet Amounts with Related Statistics G Inc. (000) Selected Income Statement Balance Sheet Amounts with Related Statistics G Inc. (000)
Dec. 96 Mar. 97 June 97 Sept. 97 Dec. 97
Cost of goods sold 173,014 178,097 187,248 174,784 173,066
Gross profit margin 17.9 18.7 21.4 22.8 18.9
Inventory (yr end bal) 144,736 148,251 144,052 141,898 159,095
Percent increase (decrease) _ 2.4 (2.8) (1.5) 12.1
Accounts payable 110,942 100,354 107,279 115,424 97,786
Percent increase (decrease) _ (9.5) 6.9 7.6 (15.3)
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Detecting Misreported Assets and Liabilities

• Undervalued liabilities off balance sheet and
  contingent liabilities
• Speculative trading in options in 3Q 03
• Put options that mature in 1Q 04
• High risk exposure of open positions
• Oil price moved in opposite direction in 4Q 03
  and 1Q 04 and MTM value of companys options
  trades deteriorated significantly
• Hugh liability for open positions at year end
  and subsequent to year end

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Detecting Misappropriation of Assets

• Using technology and data mining techniques to
  detect fraud
• Fictitious vendors matches between vendor and
  employee addresses/phone numbers, more than one
  vendor with same address/phone number, post
  office boxes in residential areas
• Vendor kickbacks exclusive dealing with a
  limited number of vendors, prices charged higher
  than market average, accelerated payment of
  invoices, purchasing agents lifestyle

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Concluding Remarks Fraud Deterrence

• Professional skepticism
• Think like the fraudster
• Understand the organization, motivation of people
  to commit fraud and conditions in which fraud
  occurs
• Ask direct/polite questions eg. Do you think
  this company has any problems with fraud? Why or
  Why not?
• Education
• Interview skills - Understand and interpret human
  behaviour
• Antifraud specialist on team if needed

20
Will the Future be like the past?
White collar crime of the older and
better-educated and our society is aging Warren
Buffet You dont know who is swimming without
any shorts on until the tide runs out!