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The Future Of Underwriting Transformation by Talent & Technology - Sanda Cagalj EY Advisory (2015)

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The Future Of Underwriting Transformation by Talent & Technology - Sanda Cagalj EY Advisory (2015)

  1. 1. The Future of Underwriting Transformation by Talent & Technology Sanda Cagalj EYAdvisory Sanda.Cagalj@tr.ey.com
  2. 2. Contents Key drivers of the future Transformative role of Underwriter Development of Technology Influencing Role of Underwriter • Data Collection Tools • Business Solution Tools 1 2 3
  3. 3. Key drivers of the future Overview Integrated systemsand processes Key Trends Automationin Underwriting Innovative products and services 3 The Future of Underwriting Pricing optimization Digital Future –focus on analytics and BI Personalized customer experience
  4. 4. Financial Services lags other industries in analytics Lack of historical investment, poor data quality and limited commercial imperative have meant Financial services lags other industries Analytics maturity modelValue Most companies are here Analytics maturity Leading ► Data: Relentless pursuit for new data and metrics ► Data viewed as strategic asset ► People/Talent: Strong leaders behaving analytically and showing passion for analytical competition ► Initiatives: Analytics integral to company strategy ► Enterprise approach: Analytics tools and infrastructure extended broadly and deeply across enterprise Nascent Developing ► Data: BU-level data, data management not a key priority ► People/Talent: Pockets of analytics excellence but not pervasive ► Initiatives: Multiple targets,not all of strategic importance ► Lack of global processes ► Limited standardized reporting ► Enterprise approach: Localized analytics, local value Established ► Data: Data virtualization – Identifying key data domains/central data repositories, 360 customer views ► People/Talent: Senior leaders recognize importance of analytics and developing analytic capabilities ► Initiatives: Global processes against small set of strategic targets ► Enterprise approach: Analytics embedded in all levels of decision making ► COE/operating model to enable Advanced 4 The Future of Underwriting
  5. 5. Supply and demand of deep analytical talent by 2018 150 180 30 300 140-190 440-490 2008 employement 5 The Future of Underwriting Graduares with deep analytical talent Others* 2008 supply Talent gap 2018 projected demand * Other supply drivers include attrition(-), immigration (+) and reemploying previously unemployed deep analytical talent (+). Source: US Bureau of Labor Statistics; US Census; Dun & Bradstreet, company interviews; McKinsey Global Institiude analysis Thousand people Demand for deep analytical talent in the United States could be 50 to 60 percent greater than its projected supply by 2018
  6. 6. What are your biggest barriers to using analytics more frequently to inform decision making? 0% 6 The Future of Underwriting 5% 30% 35% 40% 45% Other Math skills to do analysis None. We're a data-driven organization Expense What time. My Organization doesn't have analytics tools I can use without going through IT/business analytics Access to an analytics tool that is simple for me to use Access to the data to do analysis 10% 15% 20% 25% % Respondents
  7. 7. What do you want to accomplish in your organization with analytics? 00% 7 The Future of Underwriting 05% 10% 15% 20% 40% 45% 50% Improve quality control Improve IT processes and procurement Improve sales processes Improve customer targeting and personlization Assess financial risk Evaluate employee performance Anticipate product demand Improve logistics Gain insight into marketing campaigns Reduce customer churn Improve employee recruitment and retention Anticipate equipment maintenance Other 25% 30% 35% % Respondents
  8. 8. WHO LOSES What do Best Practices suggest What do the best ones do WHO WINS 8 The Future of Underwriting ► Investing in new underwriting analytical capabilities to use new data sources and interfaces to identify important trends, opportunities and risks ► Investing in powerful emerging technologies including sensors, telematics, web and mobile, new pricing techniques ► Integrating sales and underwriting portals ► Underwriter as: ► Sales executive ► Decision maker using data aggregator services and predictive analytics ► Customer advocate by increasing customer loyalty through better solutions which ultimately means higher account retention ► Innovator seeking for innovation in product development, customer engaged ► Convectional role of underwriter focused on calculating hit and retention ratios, annualized growth and calendar year and accident year loss ratio ► No investment in right technology tool sets
  9. 9. 9 Are you leveraging data and analytics fully to transform every aspect of your business? Are you READY?
  10. 10. 10 Key Questions Insurers Are Asking? What more can our own data tell us? 02 What else could we learn if we added external data to our models? 01 03 How can we build the power of analytics into day to day decision making? From data comes information, from information comes knowledge, and from knowledge, power” – Gail Jones, RGA
  11. 11. Innovate business models for insurers Price Optimization Real Time Pricing Underwriting Automation and Optimization Sensor Technology Telematics Straight – through Processing U.S. Commercial Insurer How can I apply additional data sources to improve the underwriting process? Mastered risk location and merged additional data sources to assess probable maximum losses (PMLs)? Improved combined ratio and reduced cost of reinsurance 11 The Future of Underwriting
  12. 12. Core capabilities of the Telematics Insurer Capabilities of the telematics insurance model 12 The Future of Underwriting Predictive modeling Data Managament Telematics technology expertise Customer İnsight and Relationship management Customer Oriented product Development and marketing Partnerships with telematics ecosystem constituencies Staff selection and training Business process management Web 2.0 capabilities Data and analytics Process and technology People and partnerships Customer centricity Underwriting Optimization Underwiting Automation
  13. 13. Telematics - expense cost for an average motor insurance policy Underwriting Optimization Underwiting Automation Telematics increases costs by 57% onaverage 40 40 13,5 13,5 36 50 0 20 60 40 100 80 36 160 140 120 Traditional Telematics Acquisition Levies Admin Box Data Expensesperpolocy GBP Source: S&P SynThesys, Deutsche Bank estimates Expense difference is a lesser issue for high value policies 18% 16% 14% 12% 10% 8% 6% 4% 2% 0% AdditionalExpense(%ptsofpolicy premium) Policy Premium Source: Deutsche Bank 57% 13 The Future of Underwriting
  14. 14. Reason why insurers shouldn’t underestimate insurance telematics Smartphones accounted for 57.6 percent of total sales in Q4 / 2013 Apple partnered wiht 15+ OEMs to bring the iphone experience and functionality to the car In 2014 Google introduced the Open Automotive Alliance. On board: Audi GM, Honda, Hyundai 69% of Americans use quantified – self applications. 2 of 3 Europeans are interested in such applications 0 20 60 40 80 100 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 Europe US China Based on known OEM plans 14 The Future of Underwriting Based on assumptions Annual fitment rate of embedded telematics devices (%) across Europe, US and China by 2020 Underwriting Optimization Underwiting Automation
  15. 15. Straight – through Processing Functionalities provided under automation underwriting End - to - end transparency Automated risk analysis Integration with existing platforms Modernization Straight – through processing Source: Analysis, 2012; Celent Model Insurer Asia 2011 15 The Future of Underwriting Functionalities embedded in automated underwriting systems Underwriting Optimization Underwiting Automation
  16. 16. Pricing sophistication project is expected to move your analytical maturity state from ‘nascent’ to ‘established’ Nascent Descriptive analytics ► Leverage historic data analysis to report and visualize WHAT has happened ► Typically have a data cube to enable data mining and production ofreports Predictive analytics ► Leverage past data to understand the underlying relationship between data inputs and outputs to understand WHY something happened and predict WHAT will happen in the future given various scenarios. ► Use of multi-variate statistical models to identify optimal price structure to maximiseprofits ► Embedded price optimisation process to determine a set of pricing actions to produce the most effectiveresults Established Prescriptive analytics - proving enterprise insight ► To determine WHICH decision or action across the enterprise that will produce the most effective results against a specific set of strategic objectives ► Commercial planning targets by product to drive a pricing and operationalstrategy ► Regular monitoring of conversion, elasticity and market movements at a customer segment level ► Dashboard to identify portfolio performance Leading 16 The Future of Underwriting
  17. 17. Pricing – Demand-Based vs. Risk-Based Aligning Insand Customer Views Competitio n Brand Reliability Convenienc e Loyalty Enable insurers to offer the optimal price for each customer Operational Cost Margin Lost Cost 2 Optimize the pricesto achieve corporate goals 3 Input the costs 1 Model customer behavior I n s u r e r C u s t o m e r Underwriting Optimization 17 The Future of Underwriting Underwiting Automation
  18. 18. Increase Profit and Grow R e t e n t i o n 22 22.8 23.6 24,4 25.2 26 26,8 27,6 28,4 29,2 30 30,8 31,6 32,4 88.40 88.90 88.65 89.15 89.90 89.65 89.40 90.15 90.40 90.65 88.15 87.90 We are here 0.85% AddedRetention, $3.1M Added Earnings $6.1M AddedEarnings, Same Retention 1.5% AddedRetention, Same Earnings 18 The Future of Underwriting Underwriting Optimization Underwiting Automation E a r n i n g s
  19. 19. The Pricing Optimization Cycle G O AL : optimize prices in order to maximize profit while achieving defined corporate performance objectives - business growth, volume targets,retention > Demand models > Cost/risk models > Profitability model (function to optimize) > Additional variables (for KPIs, constraints, other) > Run what-if scenarios > Analyze compare and choose Data Management Demand Estimation Price & Strategy Optimization Monitoring & Recalibration Data Feed Chosen Pricing Strategy Price Execution 19 The Future of Underwriting
  20. 20. Pricing Management: End-to-end Pricing Process, Multiple Products G e o An a l y t i c s E x e c u t i v e D a s h b o a r d Fully integrated workflow All Insurance LoBs in one instance: • Auto • Home • SME Commercial • Other ˃ Risk Premium Risk (Loss Cost) ˃ What if ˃ Individual PO ˃ Factor PO Price Optimisation ˃ Execution Manager ˃ Real Time PO Price Execution 20 The Future of Underwriting
  21. 21. Key Benefits P r o f i t s > Improves profits by 1-3% of GWP For $100M GWP,profit improves in $1-3M, or Combined Raito decreases by 1-3%. > Typical ROI greater than X10 achieved within first year > Balance profitability and retention to deliver corporategoals > Better management decisions through improved understandingof pricing strategies and their implication on businessKPIs > Improved understanding of customer behavior D e c i s i o n s > Faster time to market of prices & products through real time online integration > Improved pricing processes and more efficient work of pricing analysts > Increased collaboration across departments P r o c e s s e s 21 The Future of Underwriting
  22. 22. Price Optimization Source: Earnix 2012 North America Pricing Survey 22 The Future of Underwriting Earnix 2012 North America Pricing Survey 50 respondents, Home & Auto Earnix 2012 EMEA Pricing Survey 110 respondents, Home, Auto and SMB Source: Earnix 2012 EMEA Pricing Survey Underwriting Optimization Underwiting Automation
  23. 23. THANK YOU! Sanda Cagalj EYAdvisory Sanda.Cagalj@tr.ey.com
  24. 24. EY | Assurance | Tax | Transactions |Advisory About EY EY is a global leader in assurance, tax, transaction and advisory services. The insights and quality services we deliver help build trust and confidence in the capital markets and in economies the world over. We develop outstanding leaders who team to deliver on our promises to all of our stakeholders. In so doing, we play a critical role in building a better working world for our people, for our clients and for ourcommunities. EY refers to the global organization and may refer to one or more of the member firms of Ernst &Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients. For more information about our organization, please visit ey.com. . © 2013 EYGM Limited. All Rights Reserved.

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