Risk & Analytics. Trends within Insurance Companies Risk Management. Marc Paasch June Willis Towers Watson. All rights reserved.
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1 Risk & Analytics Trends within Insurance Companies Risk Management Marc Paasch June Willis Towers Watson. All rights reserved.
2 Key drivers & benefits Outcomes from an analytical approach to own insurance for insurance companies Demonstrate value of risk management framework Quantify value of risk transfer Fully align risk financing with risk profile and risk appetite Benefits Integrate insurance decisionmaking in the risk framework Incorporate risk transfer into capital models Auditable rationale for insurance purchase 2
3 Illustrative Tools and Inputs An analytical approach Incorporating operational risk, actuarial, modelling & insurance disciplines 1 Establish Risk Profile 2 Establish Insurable 3 Establish Optimal 4 Risk Profile Risk Finance Execution Operational Risk Uninsurable Risk Insurable Risk Risk Modelling Risk Finance Programme Internal/ External Loss Data Terrorism & nat cat modelling Insurance Mapping Risk Tolerance Marketing Placement D&O Quantified Global Peril Diagnostic Insurability Assessment Loss Distributions Risk Optimiser Premium Allocation Broking WTW Loss Data-WORLD Cyber Quantified IRIS Captive Analysis ART Global Service Risk scenarios: operational risks with frequency and severity Understanding where and how insurance responds to operational risk scenarios Optimal program recommendations (retention vs transfer at lowest premium) Risk finance program quantified value of risk transfer Limits Coverage Retention Transfer 3
4 Operational risk scenarios Insight and benchmarking for operational risk 1. Establish risk profile Typical major operational risks Operational Risk Loss data Terrorism and Nat Cat modelling D&O Quantified Cyber tools WTW loss data - WORLD Global Peril Diagnostic Outline of risk scenarios. Overview of operational risks with frequency and severity outlined LIMITS 4
5 Insurability of risk profile Structured approach to establishing insurance response 2. Establish insurable risk profile Illustrative summary scenario Uninsurable Risk Insurable Risk Insurance mapping Insurability assessment IRIS Understanding where and how insurance responds to operational risk scenarios COVERAGE 5
6 Modelling and risk finance recommendations Forecast loss profiles and determine optimal financing 3. Establish optimal risk finance Risk modelling Risk tolerance Operational risk scenario 1 frequency severity insurability Forecast loss profiles By scenario By risk category Aggregated Loss distributions Captive analysis Risk Optimizer Operational risk scenario 2 Operational risk scenario n frequency severity insurability frequency severity insurability Forecast loss profiles demonstrating impact of insurance (current and potential) Optimal program recommendations (retention vs transfer at lowest premium) RETENTION 6
7 Probability Modelling to establish value of risk transfer (1/2) Illustrative modelling output 3. Establish optimal risk finance Risk modelling 100% 80% Risk tolerance 60% Aggregated annual loss profile Loss distributions Captive analysis Risk Optimizer 40% 20% Aggregated annual loss profile after insurance Optimal program recommendations (retention vs transfer at lowest premium) 0% ,000 10, ,000 1,000,000 Annual aggregated losses ( 000) RETENTION 7
8 Modelling to establish value of risk transfer (2/2) Illustrative modelling output 3. Establish optimal risk finance Analysis of data to assess current and potential insurability by risk Risk modelling Risk tolerance Loss distributions Risk Optimizer Captive analysis Optimal program recommendations (retention vs transfer at lowest premium) RETENTION 8
9 Optimal risk finance Utilising the analysis to propose tailored insurance 3. Establish optimal risk finance Risk modelling Risk Optimizer output used to inform broking; dynamics of insurance market also taken into account Risk tolerance Each point represents a strategy The State Of Our Art The Willis Towers Watson Risk Optimizer Loss distributions Risk Optimizer Current strategy Captive analysis Efficient frontier: white line Optimal strategy Optimal program recommendations (retention vs transfer at lowest premium) RETENTION 9
10 Operational Risk Correlation Analysis Providing estimates on correlation parameters between operational risks 3. Establish optimal risk finance Risk modelling Driver Setting correlations is an important component in every Solvency II model in order to calculate a realistic measure of a company s risk exposure Risks may be linked both directly and /or indirectly Risk tolerance Does the stressed scenario for risk A impact risk B or vice versa? Are there events that could affect risk A and risk B? Loss distributions Risk Optimizer Risk A Risk B Risk A Risk B Captive analysis Optimal program recommendations (retention vs transfer at lowest premium) RETENTION Risk A Risk B Common Factor Analysis assumes plausible worst case scenarios equivalent to a 1 in 50 year event 10
11 Approach relies on modelling empirical data and expert judgement 3. Establish optimal risk finance Risk modelling Utilise multi-disciplinary team to estimate correlation parameters: actuarial expertise for modelling empirical data industry expertise Risk tolerance Structured approach relies on quantitative and qualitative analysis Loss distributions Captive analysis Risk Optimizer Optimal program recommendations (retention vs transfer at lowest premium) Risk quantificatio n Quantify risk scenarios by frequency / severity Risk categorisati on Organise risks into discrete categories and sub-categories (Basel II categorisation typically used) Risk modelling Modelling of empirical data to determine any direct correlation Risk drivers Determination of driving risk factors internal (company specific) and external Indirect correlation Indirect correlation analysis using risk drivers Correlation parameters Correlation parameters assuming plausible worst case RETENTION 11
12 Correlation matrix example ET1-4 matrix 3. Establish optimal risk finance Risk modelling Risk tolerance Loss distributions Risk Optimizer Captive analysis Optimal program recommendations (retention vs transfer at lowest premium) RETENTION 12
13 Program Design & Placement Evidence based insurance design 4. Execution Risk Finance program Marketing Placement Premium allocation ART Broking Service Risk finance program quantified value of risk transfer TRANSFER 13
14 Utilization of outputs for risk transfer Two parallel options; i) expanding cover with traditional insurers and ii) alternative risk transfer solutions 4. Execution Risk Finance program Marketing Premium allocation ART Risk finance program quantified value of risk transfer TRANSFER 14
15 Summary Utilise analytics to your advantage Quantify and understand risk and the impact it has on your financial objectives Save money by optimising insurance purchasing and strengthening negotiating position with insurers Provide an audit trail of objective decision making Leverage your approach to risk management and exploit the risk framework 2017 Willis Towers Watson. All rights reserved. Proprietary and Confidential. For Willis Towers Watson and Willis Towers Watson client use only. 15
16 2017 Willis Towers Watson. All rights reserved.
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