THE SMART WAY TO ANALYSE YOUR RISKS. DAVID STEBBING Partner, Willis Risk & Analytics

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2 THE SMART WAY TO ANALYSE YOUR RISKS DAVID STEBBING Partner, Willis Risk & Analytics

3 Increasing risks and challenges Commodity market volatility Short-term cashflow planning Profitability of longterm investments exposed to price change Increasing project scale and complexity Cost escalation Project execution and operational risks Competition New technologies New competitors Regulatory and Compliance Health and safety incidents Political risks Sources of raw materials Environment Tailings

4 Our experience with mining clients We want to analyse the value for money we are receiving from our reinsurers for our coverage We need to understand our exposures to earthquakes and other natural catastrophes We are worried about the potential for us to retain significant amounts of losses We are considering establishing a captive and need to demonstrate the financial impact of doing so

5 Why do we model? Enhance understanding of your risk profile Quantify uncertainty and exposure to large losses Optimise your insurance buying / risk financing strategy Maximise value for money from insurers ( bang for your buck ) Provide a robust audit trail to support corporate governance requirements

6 Our approach to risk financing Understand your business, its current risks and future plans (potential changes in risk profile) Risk tolerance and stakeholder expectations Actuarial risk modelling, risk allocation, and risk pricing Willis Optimiser portfolio analysis To maximise financial efficiency Implementation: Risk retention vehicles / risk transfer

7 Understanding your data Analysis of historical data reveals vital information Loss amount in 'm Rebased Attritional Losses Rebased Largest Loss15 Number of Losses Loss amount in 'm Company X Retained Reinsurance Number of Losses Numbe of Losses Numbe of Losses

8 Modelling: Claim frequency and severity We start with building models to estimate: how many claims (loss frequency) and; The size of a given claim (loss severity) 25% Loss frequency distribution (Poisson) Average of 3 losses per year with a volatility range of 1.7 (standard deviation) 100% Loss severity distribution (Lognormal) Average loss size of 9.9m with a volatility range of 145.2m (standard deviation) Probability 20% 15% 10% 5% 0% Number of losses per year Probability 80% 60% 40% 20% 0% 1, ,000 10,000,000 1,000,000,000 Loss size

9 Willis Mining Industry Database We utilise Willis s experience with mining clients to supplement our understanding of potential large losses In the example below, we used steel losses above $10m to build a more robust model Loss severity forecast 1,000,000,000 Modelled losses Industry model Loss amount (USD) 100,000,000 10,000,000 1,000, ,000 10,000 1, % 10.0% 1.0% 0.1% Probability that a given loss exceeds a given amount

10 Modelling: Understanding results Distribution Curve for the Ground-up Losses Simulation Results ('000) Percentile (Cumulative Probability ) 99% 75% 50% 25% of the time, claims will exceed 7.98m 50% of the time, claims will exceed 4.5m 1% of the time, claims will exceed 34.12m Total Losses (m) Return Period (Years) Percentile Ground-up Losses Total Loss ('000) 1 in % 4,539 1 in % 7,979 1 in % 9,200 1 in % 13,221 1 in % 18,227 1 in % 26,384 1 in % 34,124 1 in % 44,562 1 in % 57,687 1 in % 72,153 Mean 6,487 Std Dev 7,380

11 Drawing meaningful conclusions 1% chance of large uninsured losses: Purchase higher limits? Dollar swapping with insurers: Increase retentions? High profitability for insurers: Opportunity to reduce premium? Current Insurance Programme Amount in $m Return Period (Years) Percentile Total Loss Total Number Business Units Captive Market Uninsured 1 in 2 50% in 4 75% in 5 80% in 10 90% in 20 95% in 50 98% in % in % in % 1, Mean Std Dev $200m Combined Single Limit for all perils Captive EEL $500k PD/BI Combined PD $500k BI: 60 days Current premium ($m): 10.0

12 Reducing your Total Cost of Risk Methodology used to optimize risk allocation between retentions, and reinsurers In this case, compare the impact of increasing self-insured retentions Reduces Total Cost of Risk, depending on premium reductions offered by reinsurers Total Cost of Risk (in $m) $12 $10 $8 $6 $4 $10.2m $9.2m Market Premium Client Cost of Capital Client retention $2 $0 Current Programme Alternative Programme 1 Captive retention of $5m

13 Portfolio analysis: The Risk Optimiser

14 Integrated Implementation Willis Peru Willis Captive Practice Client Willis Risk & Analytics Willis Natural Resources

15 Client inputs Usual underwriting submission information: Claims: Historical ground-up losses and claims details Exposures: Historic and projected exposures Programme structure: Retentions/limits, Premiums Opportunity for discussion around risk tolerance and potential for large losses Minimal time commitment from you

16 Take-aways Real insights and actionable conclusions Analysis presented in financial language Increasingly common practice Minimal time commitment Initial process steps: Contact your Willis Client Advocate Send loss and exposure data Introductory call to understand your requirements