10:30-10:40 Introduction of panelists and purpose of panel 10:40-11:15 Day 2: External Introductory remarks by panelists Expert Panel 11:15-11:45 Moderated discussion between panelists 11:45-12:00 Audience Q&A 1
John McWilliams Enterprise risk management Kenneth Wee Learnings from risk management in financial services Ned Morse Safety and operational risk management in oil and gas industry 2
John McWilliams Enterprise risk management 3
Understanding the Distribution of Risk 4
Enterprise risk management maturity model Maturity Level 6.Risk Decisions 5. Risk Enabled 4. Risk Managed 3.Risk Defined Risk-based Risk decision making 2.Risk Aware management including Enterprise wide Strategies and and internal prioritized approach to risk 1.Risk Naive policies in place controls fully allocation of management and embedded in Scattered silo resources developed and No formal based approach communicated. the operations. communicated. framework for to risk Risk appetite risk management defined. management Key Characteristics 5
Kenneth Wee Learnings from risk management in financial services 6
Leading institutions manage risk through a governance process linking risk management to business planning Business Planning Risk Identification Bringing risk awareness into the Identify risks and comprehensively next round of strategic planning describe them, especially emerging risks Risk Learning & Stress testing Risk Assessment and Inventory Management Ensure they can withstand To assess and track how a risk might certain extreme events Lifecyle manifest in your footprint Risk Policy and Controls Risk Appetite Set roles, control the risk to How much of each Risk are you willing within your desired Appetite to take as part of your business model 7
A comprehensive risk management strategy needs to target both everyday losses and infrequent events that can lead to large losses Losses Losses Sources of everyday data • Loss database: banks maintain Long tail records of operational risk losses needs • Manager self-assessments: managers external Unexpected data and are required to create Risk Control loss scenario Self-Assessments analysis Average Tail risk events and data loss Plentiful • Investment needs to be made in internal data Expected for expected understanding how big events loss loss happen and increasing resiliency to Time Probability those • With climate change tail risk can Examples of risks with long tails: internal fraud, cyber risk, only go up, either in frequency or market illiquidity, concentration risk, unexpected correlations, severity of tail events wrong-way risk 8
Tail Risk can be hard to identify! “ Right now everything on my screen is flashing red. That doesn't make me nervous… The machine works.” Former CRO of Bear Stearns, June 2006 9
Model risk: How confident are you in the model and the data behind it? Disciplined model risk management is now in place at most large banks Year Liability modeling and assumptions were flawed and remained unresolved over years in 2018 the long-term care insurance which resulted in $15B additional reserves Charged $98M by the SEC - "for their failure to take reasonable steps to ensure the 2018 models worked as intend and for contributing to the company's compliance failings" Flawed risk management models allowed a trader to accumulate huge short positions on 2012 CDX products distorting market prices. $6.2B loss incurred by the company and congressional hearings and investigations by the Federal Reserve, SEC, FBI followed When you use a model, do you know what its key assumptions are? Do you know its limitations? How much data was it built on? What manual adjustments does it contain (to data, coefficients, etc.?) Do you know when it needs re-calibrating? 10
An ideal scenario analysis process links risk factors to the value of business and mitigation strategies, to aid in capital allocation Risk Environmental Macroeconomic Modeled P&L & 1 3 4 5 Identification Scenarios… and Market Balance Sheet Responses outcomes • E.g. Wildfires, • E.g. Land use, climate change, temperatures, • E.g. Impact on • E.g. Changes in fraud, cyber, rainfall EBITDA 2020-40 in Housing Prices by counterparty risk three scenarios county … and Socioeconomic Scenarios • E.g. Changes in Mega Trends 2 Employment by Value of • E.g. Growth path of sector • E.g. Urbanization different MSAs and industry 6 rate, migration adaptation patterns, and mitigation demographics strategies 11
What can we do to improve risk management throughout an industry? Encourage data Publish best practices, Invest in technology, Tone-from-the-top: risk collection and pooling conduct horizontals front-to-back reporting governance is important Embed risk management Create KRIs and a link to Creating consistency in Taking a risk-based into operational culture compensation stress scenarios selective approach 12
Ned Morse Safety and operational risk management in oil and gas industry 13
Dramatically improved safety at major West Coast refinery Achieving 2 years without a recordable employee injury 1 Injury rate of employees Behavior based culture Recordable injury rate 2 change launched 2.0 1.6 1.5 1.0 0.9 0.8 0.5 considered 0.5 world class 0.5 performance 3 0.2 0.0 0.0 0.0 Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 YTD 1 Oil refinery 1 1. YTD at time analysis conducted 2. Injuries per 200,000 hours worked 3. Per Solomon benchmark report for EDC group 5 & 6 14
Reduction in number of injuries to contractors at major West Coast refinery Injury levels of contractors Behavior based culture change launched 12 Injuries 11 10 Moving average 8 8 8 6 6 4 3 2 1 1 1 0 Year 3 Year 3 Year 4 Year 4 Year 5 Year 5 Year 6 Year 6 1st half 2nd half 1st half 2nd half 1st half 2nd half 1st half 2nd half Oil refinery 1 15
Sustained decline in recordable injury rate in very large Gulf Coast refinery Recordable injury rate at a refinery Behavior based culture change launched 5.7 5.1 4.9 4.8 5 4.5 Employees Employees 4.4 only + Contractors 3.9 4 3.7 3.5 3.4 3.3 Recordable 2.8 3 injury rate 2.3 1.8 2 1.6 1.5 1.3 0.9 0.9 0.9 1 0.7 0.5 0.5 0.4 0.3 0.3 0.2 0.3 0 Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr Yr 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Oil refinery 2 16
Oil major able to drive down LOC events and spills (I) Tier 1 and Tier 2 Loss of Containment (LOC) Count 250 200 150 100 50 0 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Tier 1 LOC Tier 2 LOC Oil Major 17
Oil major able to drive down LOC events and spills (II) Petroleum Spill Volume to Land and Water 50 45 40 35 30 25 20 15 10 5 0 Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Yr 11 Yr 12 Yr 13 Yr 14 Yr 15 Oil Major 18
Discussion and Q&A 19
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