1. Drake DRAKE UNIVERSITY Fin 129 Operational Risk Fin 129

2. Drake Drake University Fin 129 Operational Risk Risks related to the design and efficiency of internal procedures, systems, and human resources The risk of loss resulting from inadequate or failed internal processes people and systems or from external events. (Basel Committee 2001). Generally this includes legal risk, but not reputational or strategic risk. However, some institutions also consider reputational and strategic risks as operational risks.

3. Drake Drake University Fin 129 This and the next few Slide from Operational Risk, Carol Alexander BCBS Definitions of Operational Risk 1. Internal Fraud 2. External Fraud 3. Employment Practices and Workplace Safety 4. Clients, Products and Business Practices 5. Damage to Physical assets 6. Business Disruption and system failures 7. Execution Delivery and Process Management

4. Drake Drake University Fin 129 Internal Fraud Losses due to acts of a type intended to defraud, misappropriate property or circumvent regulations, the law or company policy Unauthorized activity – Theft and fraud – Fraud / worthless deposits, Bribes/ kickbacks

5. Drake Drake University Fin 129 External Fraud Losses due to acts of a type intended to defraud, misappropriate property or circumvent the law, by a third party Theft and Fraud – Forgery, Robbery, check kiting Systems Security –

6. Drake Drake University Fin 129 Employment Practices and Workplace Safety Losses arising from acts inconsistent with employment, health or safety laws or agreements, from payment of personal injury claim or from diversity/discrimination event. Employee Relations – Safe Environment- general liability (slip and fall), workers comp. Diversity and Discrimination

7. Drake Drake University Fin 129 Clients, Products and Business Practices Losses arising from an unintentional or negligent failure to meet a professional obligation to specific clients (including fiduciary and suitability requirements) or from the nature or design of a product. Suitability, Disclosure, and Fiduciary –

8. Drake Drake University Fin 129 Clients, Products and Business Practices Improper Business Practices – Antitrust market manipulation unlicensed activity, money laundering Product Flaws – model errors Selection, sponsorship, and exposure – failure to investigate per client guidelines exceeding client exposure limits Advisory activities

9. Drake Drake University Fin 129 Damage to Physical assets Losses arising from loss or damage to physical assets from natural disaster or other events

10. Drake Drake University Fin 129 Business Disruption and system failures Losses arising from disruption of business or system failures Hardware failures Software failures Telecommunications problems Utility Outage / disruptions

11. Drake Drake University Fin 129 Execution Delivery and Process Management Losses from failed transaction processing or process management, from relations with trade counterparties and vendors Transaction capture – Miscommunication, data entry error, missed deadlines Monitoring and reporting – failed mandatory report Customer intake and documentation – client disclaimers/ permissions missing

12. Drake Drake University Fin 129 Execution Delivery and Process Management Customer client account management – unapproved access given to accounts negligent loss or damage of assets Trade counterparties – nonclient counterparty misperformance Vendors and Suppliers

13. Drake Drake University Fin 129 Total Loss by Risk Type

14. Drake Drake University Fin 129 Basle Requires measurement of the operational risk capital requirement resulting from each source in each of 8 business lines 1. Corporate Finance 2. Trading and Sales 3. Retail Banking 4. Commercial Banking 5. Payment and Settlement 6. Agency and Custody 7. Asset Management 8. Retail Brokerage

15. Drake Drake University Fin 129 Frequency and Risk (F/R) Internal Fraud External Fraud Employ Practices ClientsDamage to Phys Bus Disruption Execution delivery Corp FinL/HL/ML/LL/HL/L TradingL/HL/L M/ML/L H/L Retail BankL/MH/LL/LM/MM/LL/LH/L Com BankL/HM/ML/LM/ML/L M/L Pay & SettL/ML/L H/L Agency & Cust L/ML/L L/ML/L M/L Asset Mgmt L/HL/L L/HL/L M/L Retail BrokL/M L/LL/ML/LM/L

16. Drake Drake University Fin 129 Importance of Technology Efficient technological base can result in: Lower costs Increased revenues Earnings before taxes = (Interest income - Interest expense) + (Other income - Noninterest expense) - Provision for loan losses

17. Drake Drake University Fin 129 Technology and NIM Well chosen Technology can increase net interest margin, by decreasing interest expense and increasing interest income. It also impacts non interest income and non interest expense

18. Drake Drake University Fin 129 Impact of Technology Interest income can be increased Interest expense can be decreased

19. Drake Drake University Fin 129 Impact of Technology Other income can be increased Noninterest expenses can be reduced

20. Drake Drake University Fin 129 Impact on Wholesale Banking Wholesale Banking – corporate customer services Improvements to cash management Controlled disbursement accounts – establishes in morning all payments that need to be made by the customer that day. The Fi then receive a wire transfer in that amount form the client. Account reconciliation

21. Drake Drake University Fin 129 Impact on Wholesale Banking Improvements to cash management continued Wholesale lockbox – centralized collection service designed to reduce float. FI serves receives payments directly instead of through the client Electronic lockbox – same as above except on line Funds concentration –

22. Drake Drake University Fin 129 Impact on Wholesale Banking (continued) Electronic funds transfer – CHIPS, Fedwire, automated payrolls etc.. Check deposit services Electronic initiation of letters of credit – allows customers to initiate letters of credit Treasury management software Electronic data interchange –

23. Drake Drake University Fin 129 Impact on Wholesale Banking (continued) Facilitating B2B e-commerce Electronic billing Verifying identities Issue of law enforcement access to encrypted data since September 11, 2001 Assisting small business entry into e- commerce assistance for small business to establish electronic capabilities that work in conjunction with the FI.

24. Drake Drake University Fin 129 Impact on Retail Banking Automated teller machines Point-of-sale debit cards Home banking Preauthorized debits/credits Pay-by-phone E-mail billing Online banking Smart cards

25. Drake Drake University Fin 129 Effects of Technology on Revenues and Costs Investments in technology are risky Potentially negative NPV projects due to uncertainty and potential competitive responses Potential agency conflicts:

26. Drake Drake University Fin 129 Effects of Technology on Revenues and Costs Evidence shows the impact of regulation on value of technological innovations. Branching restrictions in U.S. affect the value of cash management services, for example. Less valuable in Europe where comparable restrictions are absent

27. Drake Drake University Fin 129 Effects of Technology on Revenues and Costs Revenue effects: Facilitates cross-marketing Increases innovation Service quality effects Survival of small banks and value of “human touch” Cost effects: Technological improvements Shift in cost curve.

28. Drake Drake University Fin 129 Economies of Scale On impact is the ability to take advantage of economies of scale. Economies of scale exist when the FI can lower its average cost per unit by increasing its size.

29. Drake Drake University Fin 129 Effects on Costs (continued) Economies of scale Optimal size depends on shape of average cost curve. AC Size AC Size

30. Drake Drake University Fin 129 Effects on Costs (continued) Economies of scope Multiple outputs may provide synergies in production. Diseconomies of scope Specialization may have cost benefits in production and delivery of some FI services

31. Drake Drake University Fin 129 Testing for Economies of Scale and Scope Production approach: Views FI as producing output of services using inputs of labor and capital. C = f(y,w,r) Intermediation Approach: Includes funds used to produce intermediated services among the inputs (k). C = f(y,w,r, k)

32. Drake Drake University Fin 129 Empirical Findings Evidence economies of scale for banks up to the $10 billion to $25 billion range. X-inefficiencies may be more important. Inconclusive evidence on scope. Recent studies using a profit-based approach find that large FIs tend to be more efficient in revenue generation.

33. Drake Drake University Fin 129 Technology and Evolution of the Payments System Use of electronic transactions higher in other countries. (E.g., TARGET). U.S. Payments system: FedWire Clearing House Interbank Payments System (CHIPS) Combined value of transactions often more than $2.7 trillion per day.

34. Drake Drake University Fin 129 Wire Transfer System Risks Daylight overdraft risk FedWire settlement at 6:30 EST Example of magnitude of daylight overdraft risk: Bank of New York (BONY)

35. Drake Drake University Fin 129 Risks (continued) International Technology Transfer Risk Crime and Fraud Risk Regulatory Risk Technology facilitates avoidance of regulation by locating in least regulated state or country. Tax Avoidance Competition Risk

36. Drake Drake University Fin 129 Controlling Operational Risk Loss prevention : Training, development, review of employees Loss control: Planning, organization, back-up Loss financing: External insurance Loss insulation: FI capital

37. Drake Drake University Fin 129 Regulatory Issues 1999 Basel Committee on Banking Supervision noted the importance of operational risks Required capital: Basic Indicator Approach Standardized Approach Internal Measurement Approach Consumer protection issues

38. Drake Drake University Fin 129 Basic Indicator Approach The default option under Basle K BIA =  GI K BIA = capital charge  predetermined scaling factor  GI = gross income = the sum of net interest income, net non-interest income, net trading income, and other income gross of provisions exclusive of irregular items.

39. Drake Drake University Fin 129 Why Net Income? Consist and comparable across jurisdictions Easily confirmed by independent auditors Measure of size of activity (but not operational risk) Readily available

40. Drake Drake University Fin 129 Problems Associated with the Basic Indicator Approach Should be related to an indicator of operational risk. Would operating expense be a better benchmark than gross income? Better relationship to operational risk Currently there is a incentive to decrease gross income to lessen capital requirement Why should there be a linear relationship with a volume (size) indicator? May impose different burden based upon business lines – advisory services, agency services and asset management – high operational risk – trading low operational risk given standard.

41. Drake Drake University Fin 129 The Standardized Approach There is a capital charge for each of the 8 business lines. All activity must be mapped into one of the business lines The total capital charge is the sum of the individual capital charges in each of the business lines K STA  i GI i

42. Drake Drake University Fin 129 Beta Factors Business LineBeta Factor Corporate Finance18% Trading and Sales18% Retail Banking12% Commercial Banking15% Payment and Settlement18% Agency Services15% Asset Management12% Retail Brokerage12%

43. Drake Drake University Fin 129 Benefits of Standardized Approach Better reflection of the size, scope and culture of the organization Ability to assess risk from different activities and identify which business units contribute to the operational risk picture.

44. Drake Drake University Fin 129 Issues with the Standardized Approach Still tied to gross income. No clear empirical evidence hat different business lines should have different sensitivities. May create a moral hazard problem if banks decide to self insure through the capital requirement instead of though the insurance industry.

45. Drake Drake University Fin 129 Advanced Methods Based upon past loss experience Monitor loss experience based on the frequency and risk matrix. The risk measure (99.9% confidence) must be based upon loss data Combinations of expected loss and unexpected loss Regular validation of the model.

46. Drake Drake University Fin 129 Some possible methods Loss modeling Simulation Bayesian Estimation Scorecard Approach