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Enterprise Risk Management Not just insurance, auditing, risk analysis

ERM David L. Olson, University of Nebraska-Lincoln Desheng Wu, University of Reykjavik, University of Toronto. Enterprise Risk Management Not just insurance, auditing, risk analysis A philosophy – A way of business. Definition. Systematic, integrated approach

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Enterprise Risk Management Not just insurance, auditing, risk analysis

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  1. ERMDavid L. Olson, University of Nebraska-LincolnDesheng Wu, University of Reykjavik, University of Toronto Enterprise Risk Management Not just insurance, auditing, risk analysis A philosophy – A way of business

  2. Definition • Systematic, integrated approach • Manage all risks facing organization • External • Economic (market - price, demand change) • Financial (insurance, currency exchange) • Political/Legal • Technological • Demographic • Internal • Human error • Fraud • Systems failure • Disrupted production • Means to anticipate, measure, control risk Finland May 2010

  3. Finland May 2010

  4. Finland May 2010

  5. DIFFERENCES Finland May 2010

  6. Risk & Business • Taking risk is fundamental to doing business • Insurance • Lloyd’s of London • Hedging • Risk exchange swaps • Derivatives/options • Catastrophe equity puts (cat-e-puts) • ERM seeks to rationally manage these risks • Be a Risk Shaper Finland May 2010

  7. Types of RiskStroh [2005] • External environment • Competitors; Legal; Medical; Markets • Business strategies & policies • Capital allocation; Product portfolio; Policies • Business process execution • Planning; Technology; Resources • People • Leadership; Skills; Accountability; Fraud • Analysis & reporting • Performance; Budgeting; Accounting; Disclosure • Technology & data • Architecture; Integrity; Security; Recovery Finland May 2010

  8. Another viewSlywotzky & Drzik, HBR [2005] • Financial • Currency fluctuation • DEFENSE: Hedging • Hazard • Chemical spill • DEFENSE: Insurance • Operational • Computer system failure • DEFENSE: Backup (dispersion, firewalls) • New technology overtaking your product • ACE inhibitors, calcium channel blockers ate into hypertension drug market of beta-blockers & diuretics • Demand shifts • Gradual – Oldsmobile; Rapid - Station wagons to Minivans Finland May 2010

  9. Technology Shift • Loss of patent protection • Outdated manufacturing process • DEFENSE: Double bet • Invest in multiple versions of technology • Microsoft: OS/2 & Windows • Intel: RISC & CISC • Motorola didn’t – Nokia, Samsung entered Finland May 2010

  10. Brand Erosion • Perrier – contamination • Firestone – Ford Explorer • GM Saturn – not enough new models • DEFENSE: Redefine scope • Emphasize service, quality • DEFENSE: Reallocate brand investment • AMEX – responded to VISA campaign, reduced transaction fees, sped up payments, more ads Finland May 2010

  11. One-of-a-kind Competitor • Competitor redefines market • Wal-Mart • DEFENSE: Create new, non-overlapping business design • Target – unique product selection Finland May 2010

  12. Customer Priority Shift • DEFENSE: Analyze proprietary information • Identify next customer shift • Coach leather goods – competes with Gucci • Went trendy, aggressive in-market testing • Customer interviews, in-store product tests • DEFENSE: Market experiments • Capital One – 65,000 experiments annually • Identify ever-smaller customer segments for credit cards Finland May 2010

  13. New Project Failure • Edsel • DEFENSE: Initial analysis • Best defense • DEFENSE: Smart sequencing • Do better-controllable projects first • Applied Materials – chip-making • DEFENSE: Develop excess options • Improve odds of eventual success • Toyota – hybrid: proliferation of Prius options • DEFENSE: Stepping-stone method • Create series of projects • Toyota – rolling out Prius Finland May 2010

  14. COSOCommittee of Sponsoring OrganizationsTreadway Committee – 1990sSmiechewicz [2001] • Assign responsibility • Board of directors • Establish organization’s risk appetite • establish audit & risk management policies • Executives assume ownership • Policies express position on integrity, ethics • Responsibilities for insurance, auditing, loan review, credit, legal compliance, quality, security • Common language • Risk definitions specific to organization • Value-adding framework Finland May 2010

  15. COSO Integrated Framework 2004Levinsohn [2004]; Bowling & Rieger [2005] • Internal environment – describe domain • Objective setting – objectives consistent with mission, risk appetite • Event identification – risks/opportunities • Risk assessment - analysis • Risk response – based on risk tolerance & appetite • Control activities • Information & communication – to responsible people • Monitoring Finland May 2010

  16. Risk Management Tools • Simulation (Beneda [2005]) • Monte Carlo – Crystal Ball • Multiple criteria analysis • Tradeoffs between risk & return • Balanced Scorecard • Organizational performance measurement Finland May 2010

  17. ERM SoftwareRhoden [2006] Penny [2002] • Algorithmics Incorporated – ERM software, global financial institutions Jane’s Defence Industry [2005] • Strategic Thought – Active Risk Manager – defence industry Rhoden [2006] • Q5AIMS • From Q5 Systems Ltd • Safety audit & corrective action tracking • Mobile devices, Web-link • Preceptor • Learning management system • Regulatory compliance, technical training • PicketdynaQ • Workplace audit & assessment management • Regulatory references built in Finland May 2010

  18. SIMULATION • Crystal Ball • Spreadsheet add-in • Value at Risk (VaR) • Distribution of expected value at specified probability level • >3.42 @ 0.95 Finland May 2010

  19. Spreadsheet Finland May 2010

  20. Stochastic Elements these PRO FORMA models include a number of inherently STOCHASTIC elements • costs are really guesses • can base variance on subjective estimates • for repetitive operations, collect data • revenues are even more uncertain • discount rates in NPV uncertain Finland May 2010

  21. Net Present Value where n = number of time periods in analysis ini= revenues in period i outi= cash outflow in period i r = discount rate i = END of time period Finland May 2010

  22. EXCEL RN generation • Options • Analysis Tools • Random Number Generation • Output Range • Number of Variables • Number of Random Numbers • Distribution • Parameters • Random Seed Finland May 2010

  23. Sharpe Ratio • Consider variance of stock as measure of risk • Tradeoff between mean and variance • Efficient investment opportunities Finland May 2010

  24. Simulation studies involving the Sharpe ratio • Opdyke – Journal of Asset Management [2008] 8:5, 308-336 • Simulated to reflect autocorrelation of distributions • Yu et al. – Journal of Asset Management [2007] 8:2, 133-145 • Value-at-risk = max expected loss over a given time period at a given confidence level • Simulation showed simply using Sharpe ratio insufficient – need to reflect covariance • Chen & Estes – Journal of Financial Planning [2007] 20:2, 56-59 • Dollar-cost averaging for 401k contributions • Simulated different strategies for contributions, allocation ratios, growth targets as decision variables • Boscaljon & Sun – Journal of Financial Service Professionals [2006] 60:5, 60-65 • Value-at-risk & return-at-risk more conservative than variance • Simulated all 3 Finland May 2010

  25. Simulation studies involving Black-Scholes model • Alam – Journal of Economics & Finance [1992] 16:3, 1-20 • Figlewski et al. – Financial Analysts Journal [1993] 49:4, 46-56 • Barraquand & Martineau – Journal of Financial & Quantitative Analysis [1995] 30:3, 383-405 • Frey – Finance & Stochastics [2000] 4:2, 161-187 • Gopal et al. – Decision Sciences [2005] 36:3, 397-425 • Fink & Fink – Journal of Applied Finance [2006] 16:2, 92-105 Finland May 2010

  26. Black-Scholes Option Pricing • Model to value options Price of call = Prob{x<d1}*S – Prob{x<d2}*E*e-rT where S = price of stock E = exercise price r = risk-free interest rate T = time to maturity (years) Finland May 2010

  27. Estimation of specification error biases – Black-Scholes & Cox-Ross models Alam, Journal of Economics & Finance, Fall 1992, 16:3, 1-20 • Black-Scholes • assumes constant variance of returns • Tends to underprice options at-the-money, overprices at extremes (“u-shaped”) • Cox-Ross • Variance changes with stock price • Analytically intractable Finland May 2010

  28. Evaluating Performance of Protective Put Strategy Figlewski et al., Financial Analysts Journal, Jul/Aug 1993, 49:4, 46-56 • Having put in place protects portfolio from loss below strike price • Simulated 3 put strategies: • Fixed strike price • Strike price a fixed % below asset price • Upward ratcheting policy • Ignores buying, selling, settlement costs (taxes) • Cost of put strategy is path dependent, thus only cost effective if expect high volatility in market Finland May 2010

  29. Numerical Valuation Barraquand & Martineau, Journal of Financial & Quantitative Analysis, Sep 1995, 30:3, 383-405 • Cox-Ross does well for one asset, but computational demands increase exponentially • Closed form solution unfound • Monte-Carlo only tractable method Finland May 2010

  30. Advanced Option Pricing Fink & Fink, Journal of Applied Finance, Fall/Winter 2006, 16:2, 92-105 • Foreign currency options have volatility smiles (“u-shaped”) • Equity options have volatility skews (higher volatility for lower strike prices) • Bates model uses mean reversion for volatility estimates • Simulated Black-Scholes, Merton & Heston, Bates • Bates won easily • Black Scholes inflexible (Merton & Heston better here) Finland May 2010

  31. More efficient super-hedging Frey, Finance & Stochastics, 2000, 4:2, 161-187 • Add descriptive, predictive power by allowing variation of volatility estimate • Hedge what you intend to hedge • Minimize transactions costs • Probabilistic argument Finland May 2010

  32. Online Auction Risk Gopal et al., Decision Sciences, Aug 2005, 36:3, 397-425 • Buyer’s risk – loser’s lament (bid too low & lose; bid too high & pay too much) • Seller’s risk – accept too low • Simulation used to estimate volatility • Searches through combinations of strike price & option price Finland May 2010

  33. Financial Simulations • a very rich field for simulation • high degrees of uncertainty in cash flows • SPREADSHEETS for the most-part Finland May 2010

  34. Iceland heating pipesMean Lognormal (30.76,38.61) – offset 30 Finland May 2010

  35. Supply Chain SimulationProduce to Forecast Finland May 2010

  36. Supply Chain SimulationProduce to ROP/Q Finland May 2010

  37. Monte Carlo Simulation Finland May 2010

  38. China vendor price distribution Finland May 2010

  39. Taiwan vendor price distribution Finland May 2010

  40. Simulation Output Finland May 2010

  41. MCDMj alternatives, I criteriaweights, scores Finland May 2010

  42. MCDM Weights Finland May 2010

  43. Scores Finland May 2010

  44. Values Finland May 2010

  45. Balanced Scorecard Finland May 2010

  46. Conclusions • Outsourcing provides competitive access • Broader opportunities • Demonstrate 3 tools • Monte Carlo simulation • Evaluate probabilistic elements • MCDM • Consider multiple criteria • Select vendor by decision maker preference • Balanced Scorecard • Measure effectiveness of selected vendor Finland May 2010

  47. ERM Research • Mostly descriptive, frameworks • SURVEY • Lynch-Bell [2002] surveyed 52 companies • Examined practices of governance, strategy, processes, technology, functions, culture • Milladge [2005]; Gates [2006] surveyed 271 members of the Conference Board • Skelton & Thamhain [2003]; Thamhain [2004] • 3 year field study R&D product development • Suggest look-ahead simulation, rapid prototyping to anticipate problems • Beasley et al. [2005] • Gathered data on 123 organizations, found ERM implementation positively related to: • Chief risk officer presence • Board independence • Top management support • Big Four auditor presence • Entity size • Banking, Education, Insurance Finland May 2010

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