David Ingram CERA, FRM, PRM EnterpriseRisk ManagementFor Insurers and Financial Institutions From the International Actuarial Association
1. INTRODUCTION - Why ERM? 2. RISK MANAGEMENT FUNDAMENTALS – FIRST STAGE OF CREATING AN ERM PROGRAM 3. RISK ASSESSMENT AND RISK TREATMENT - ACTUARIAL ROLES 4. ADVANCED ERM TOPICS Course Outline
ERM FUNDAMENTALS • FIRST STAGE OF CREATING AN ERM PROGRAM • 2.1 Risk Identification: systematic identification principal risks • 2.2Risk Language:explicit firmwide words for risk and Risk Management • 2.3 Risk Measurement: What gets measured gets managed • 2.4 Risk Management Policies and Standards: Clear and comprehensive documentation • 2.5 Risk Organization: Roles & Responsibilities • 2.6 Risk Limits: Set, track, enforce • 2.7 Risk Management Culture: ERM & the staff • 2.8 Risk Learning: Commitment to constant improvement • 2.9 Developing a First Stage Implementation Plan
2.1 Risk Identification: • Systematic identification principal risks • Two Common Methods: • Top Down • Bottom Up
Top DownKey Risks & Controls Workshop • Risk Identification • Risk Assessment • Risk Control Assessment • Heat Map Development • Risk Plan
Insurance Risk Credit Risk Market Risk ERM Liquidity Risk Operational Risk Group Risk Risk Identification • Which are your Risks?
Risk Assessment • How Significant are your risks? • Subjective Assessment • Consensus view • Frequency • Severity
Risk Control Assessment • For Most Significant Risks • How effective are your existing control processes? • For the best controlled risks, how much risk is left after the control process? Are they still significant? • Subjective Assessment • Not as easy to reach consensus
Risk Control Plan • Choose High Priority Risks to address this year • Plan will be to: • Prepare detailed documentation of existing control processes • Research and identify best practice control processes • Compare existing to best practice • Choose improvements to make • Implement improvements
2.2 Risk Language: • Explicit firmwide words for risk and Risk Management • RISK WORDS • Start with LOSS • What are the words for the worst thing that has happened? • In the past quarter? • In the past year? • Ever?
Realistic Loss Terminology • Good – Company meets plans, bonuses paid • Adverse – Company fails to meet plans by significent margin, no bonuses paid. May be some layoffs. • Terrible – Company shows significant loss. Top management loses jobs • Horrible – Company suffers large loss. Downgraded (or other bad publicity) causes company to lose ability to sell new business • Disaster– Company loses almost all surplus. Taken over by regulators Substitute your own words
Risk Terminology • Frequency & Severity • Does “High Severity” mean the same thing in different departments? • Do different departments have similar time frames in mind?
Risk Management Terminology • What is it called when someone doing risk management? • Risk Treatment • Risk Mitigation • Underwriting • Hedging • ALM • Quality Control
Make a List • Of Risk & Risk Management words that we use this week that are NOT part of company vocabulary • And another list of words that are used
2.3 Risk Measurement: • What gets measured gets managed Includes: Gathering data, risk models, multiple views of risk and standards for data and models.
Risk Measurement – Minimal Practice • Do not have needed data readily available • Models for some risks • Only one measure of risks where there are any • May be calculating something that is slightly or significantly • different from risk definition
Adequate Risk Measures • Information is not too late to drive any action • Gives broad indication of the amount of risk – mostly reflecting differences to volumes • Inexpensive • May be understood by primary users and misunderstood by occasional users
Good Risk Measure • Timely • Accurately distinguishes broad degrees of riskiness within the broad risk class • Not too expensive or time intensive to produce • Understood by all who must use • Actionable
Excellent Risk Measure • Good Risk Measure Plus • 6. Can help to identify changes to risk quality • 7. Provides information that is consistent across different Broad Classes of Risk • 8. For most sensitive risks will pinpoint variations in risk levels
Best Practices Risk Measurement • Gathering data for risk measurement is regular output of operational processes • Risk Models exist and are used for every risk • Multiple views of risk are developed • Risk Measurements are consistent with Risk definitions & Risk Language • Clear standards for Data, Models and measures of risk
Improving Risk Measurement • Identify existing risk measures • Classify as Adequate, Good, Excellent • Look to create additional risk measures where needed • Look to improve quality of measures where needed
Risk Assessment • Risk Metrics • Gross Exposure • Expected Losses • Volatility of Losses • Ruin / Tail Losse
Gross Exposure • Credit – Amount invested in single group of companies (Name) • Equity Market Risk – Direct Holdings + Separate Account Holdings + Maximum value of guarantees • Interest Market Risk – Direct Holdings • Insurance – Face Amount + Max Probable Loss • Operational – Largest losses known adjusted by size of operation
Expected Losses • Credit – Average per period Expected Loss over cycle – Maximum Loss per period over cycle • Market – may not apply • Insurance – Net Premium • Operational – Average losses per period
Volatility of Losses • Market, Credit, Insurance • Standard Deviation of losses based on: • Historical experience • Expected future of next cycle • Implied Volatility from market price of derivatives
Ruin / Tail Losses • Stress Tests • VaR • CTE
Market Risk Measures Cash Flow Testing Duration Convexity Value at Risk Option Adjusted Spread Sharpe Ratio Key Rate Durations Tracking Error General & Insurance Measures A/E Experience Monitoring Liquidity Analysis Scenario Analysis Stress Testing Embedded Value Earnings at Risk Probable Maximum Loss Performance Attribution Earnings by Source RBC Ratios Risk Measurement Tools
A/E Experience Monitoring • Actual experience is regularly compared to pricing and\or budget\plan expectations to show the degree to which liability assumptions are being met. Trend analysis is often performed on A/E ratios to see whether to expect continuation of favorable or unfavorable experience.
Stress Testing • Process to identify and manage situations that could cause extraordinary losses. Stress Testing uses scenario analysis, stress models, correlations and volatilities, and policy responses.
Probable Maximum Loss • The maximum loss that is incurred for the entire company in a pre-defined disaster scenario situation. PML is usually the ultimate stress test selected subjectively by the company management to reflect the worst situation that they think has any significant likelihood. PML is also the term sometimes used to describe the exposure to loss from a single event such as a natural disaster or the default of a bond issuer.
Scenario Analysis • Evaluation of the asset and liability portfolios under various economic assumptions. Typically involves large movements in key variables and full cash flow projections.
Liquidity Analysis • Analysis of a company’s ability to withstand a stress liquidity situation over a short term horizon. The analysis takes into account the company’s capital position, the liquidity of the asset portfolio, the surrender potential of the liability portfolio, the degree of cash matching employed, the number of contract-holders, distribution channels, target markets and size of the company.
Embedded Value • The present value of future profits that are “embeded” in the existing inforce business. • May be best estimates discounted at a risk adjusted interest rate. • Some use accounting system profits (with margins for adverse deviation) and discount at an after-tax return on underlying assets • Used as a proxy for market value of liabilities.
Earnings at Risk • The expected decrease in earnings over a specified time period within a given confidence level. Using GAAP values avoids some of the difficult problems of marking insurance company liabilities to market. However, the full GAAP impact from a shock to certain risk factors does not necessarily emerge in the short time frame generally captured in these types of calculations.
Performance Attribution/ Earnings by Source • Process of disaggregating actual return into pre-defined components. This is a retrospective measure that can be designed to show which risk factors are causing losses.
RBC Ratios • The ratio of RBC to adjusted statutory surplus is used as the standard for surplus adequacy related to company risks. Some companies use Rating Agency surplus formulas while others use internally developed Required Surplus formulas.
VaR • Value at Risk • Quick Measure of Risk – originally for derivatives trading book of bank • Has become primary measure for Banks
= 232 90th Percentile Expected Value = 498 VaR – Monte Carlo VaR = 498 – 232 = 266
VaR • Advantages • Quick & Easy to calculate • Easy to explain and understand • Disadvantages • Shortcuts commonly used may render result meaningless • Ignores much of tail • Can be “gamed”
VaR • Definition: • Value at Risk is expected loss at a particular level of probability (usually 95% or 98%)
VaR • Calculation Methods • Historical • Mean Variance • Simulation • Usually calculated for 1 day and extrapolated to 10 days
VaR – Historical Calculation • Collect historical values for past 250 trading days • Rank Values • 95% VaR is 238th worst value
VaR Mean Variance Calculation • Determine Mean and Variance of loss function: • Historical • Expectations for Future • Risk neutral – Implied by Current Market Prices • Assuming Normal Distribution of loss, determine 95%/98% loss • 95% loss = mean – 1.645 x Std Dev • 98% loss = mean – 2.052 x Std Dev
VaR Stochastic Calculation • Usually used where • market values are not available and • distribution of losses is know to be non-normal • Develop stochastic scenarios of fundamental market elements • interest rates, equity
CTE • Contingent Tail Expectation • aka Tail VaR • Average of values worse than VaR • CTE90 means average of worst 10% of values
= 232 90th Percentile Expected Value = 498 CTE – Monte Carlo 90 CTE