Technology Innovation Trends in Insurance by Navdeep Arora

1. Technology Innovation Trends in Insurance Navdeep Arora 8 April 2020

2. 7 themes are reshaping supply & demand of insurance globally Growing expectations & demands from customers (value, omni-channel) and regulators (solvency) Emerging risks & developing markets necessitating digital architecture and solutions Downward pressure on pricing from excess underwriting capacity (alternative capital) and decreasing demand for traditional reinsurance; shift in focus from ‘protection’ to ‘risk prevention, mitigation and diversification’ Improved transparency of data on the buyer & seller side, stressing current distribution & broking models, especially in mature markets External data, contextual intelligence & sensory feeds becoming more ‘predictive’ than historical loss data, and enabling personalisation of insurance Ability to manage high velocity transactions and delivering at customer moments of truth becoming source of competitive advantage as lines of business (life, health, P&C) disappear; cross-sector partnerships, non-native capabilities and flexible technology architecture emerging as ‘table-stakes’ Large scale migration of premium & profit pools across the value chain, customer segments, products & sectors

3. Premium & profit pools are migrating across the insurance value chain Aggregators / Price comparison • Commoditising in mature markets as incumbents are building their own price comparison and direct capabilities. • Growth opportunity for nascent and developing markets • Online brokers are carving out new ‘direct to consumer’ capabilities in personal as well as commercial lines, especially SME (Insureon, Simply Business, etc) Online Brokers Traditional Brokers/ Agents • Traditional brokers are losing business, commissions, and margins, especially in mature lines of business such as property and liability, as well as geographies • Technology and digital capabilities are enabling MGAs to carve our new underwriting classes, go direct, and take on more risk on their balance sheets; Growing numbers in mature markets; Not yet a large phenomenon in developing markets but expected to grow MGAs/ Digital MGAs • Continuing downward pressure on pricing and margins in standard lines of business, while unmet and under-met risk needs offer growth potential Insurers • Reinsurance rates have declined for 18 consecutive quarters, as alternative capital continues to grow, and premiums ceded fall Reinsurers

4. Value creation opportunities are different across mature & developing markets Premium share (aggregated % per $ of premium) Trends Trends Profitability Margins Mature markets Developingmarkets Mature markets Developingmarkets Aggregators / Price comparison 15 to 20 % 0.5 to 1 % Online Brokers 8 to 30% 30 to 50 % Traditional Brokers/ Agents MGAs/ Digital MGAs 0 to 20% 18 to 25 % Insurers 10 to 15 % 60 to 70% Reinsurers 8 to 12 %

5. Technology & digital capabilities that target value chain effectiveness (not just scale efficiencies) offer compelling investment opportunities Non Life Insurance (Medical, P&C) 1 Indemnity Lost ratio 2 LAE A UW results Profitability(1-COR) Net income Expense ratio 3 Distribution AUM (Invested/asset/NEP) B Volume(NPE) Investments results 4 Penetration Investment Yield P&C Valuation Cash flow to equity 5 UW and pricing C Capital required(Capital/NPE) 6 Reinsurance & Cap mgt Long term grow 7 Acquisition, retention & servicing Cost of equity

6. InsurTech levers and start-up examples in non-life Insurance (1/2) Potential impact Examples Driver InsurTech levers A 1 • Claims cost reduction by 50% • Claims indemnity (leakage) improvement by 20-50% • Empowering the customer to self manage their claims experience • Delivering on the claims promise, leading to fair and accurate claims payments, lower cost of claims & higher customer NPS scores • Satellite and UAV imagery for CAT and large loss claims • Automated claims settlement and payment through distributed networks Profitability Indemity 2 LAE B 3 • 20% improvement in quote to bind rates • 30% increase in direct sales • AI/ML to review submissions & recommend new business/cross sell prospects • Micro-insurance distribution and servicing • 360 degree sales funnel optimisation • Robo-broking Volume Distribution C • Customer acquisition and conversion optimisation through social media data AI • Customer journey analytics • Improving customer acquisition through digital asset catalogues 4 • Customer acquisition/conversion increase by 25% and retention up 50% Penetration Capital

7. InsurTech levers and start-up examples in non-life Insurance (2/2) Potential impact Examples Driver InsurTech levers A 5 • Automated risk data capture through IOT sensors • Usage based on demand risk transfer • AI/ML driven underwriting insights • Underwriting without claims history • UW cost per policy reduction by 50% • Pricing leakage reduction by 30% Profitability UW and pricing B 6 • Cedant premiums reduction by 20% and reinsurance costs by 10% • Real time risk mitigation and capital allocation • Replace actuarial services with AI • Liquid reinsurance platforms • Reinsurance data analytics and integration Volume Reinsurance and Cap mgt. C • Auto claims settling based on triggers • Machine Learning for policy language optimisation • Fraud management • CRM and policy automation • Blockchain and smart contracts 7 • Cost per inforce policy reduction by 50% Acquisition & Retention Capital

8. Technology & digital capabilities that target value chain effectiveness (not just scale efficiencies) offer compelling investment opportunities Life Insurance 1 Acquisition(cost, conversion) 2 Underwriting (STP,Cost, Policy) A New business Profitability Value of new business (VNB) 3 Pricing (UW margins) B New business volume Franchise Value Long term growth 4 Policy servicing (cost/PIF) C Life Valuation In-force profitability 5 Retention (lapse rate) Net Income Size of book Embedded Value (EV) 6 Penetration(cross sale) DurationCapitalization (EV/net income) 7 Claims(% conversion)

9. InsurTech levers and start-up examples in life Insurance (1/2) Potential impact Examples Driver InsurTech levers A 1 • Turning social media data into insurance insights to improve conversion • Customer journey analytics • Digital asset cataloguing • Online direct distribution • Life aggregator • Facebook based life insurance concierge • 4x increase in conversion rates • NPS scores up 20 points • Commission ratio improvement Value of new business Acquisition and distribution 2 Underwriting • Predictive analytics platform for actuarial and risk management • Predictive scoring and data analytics • Facial analytics and bio-demographic info for UW • Forward looking UW using context, sensory and genomics • Online direct UW for term life B New business volume • Increase in STP by up to a third • Instant underwriting 2 Pricing C 4 • Expense ratio improvement Policy servicing • CRM and policy automation • Blockchain and smart contracts • Automation and use of AI • Online platform to manage life and disability insurance In-force profitability

10. InsurTech levers and start-up examples in life Insurance (2/2) Potential impact Examples Driver InsurTech levers A 5 • Life in-force analytics and optimisation • Monitor and mine life in-force books • AI and data analytics based on cross selling for disability insurance • Lifetime platform for optimising retention and cross sell for in-force • Web based portfolio management and placement • Increased cross sell • 25-50% improvement in lapse rates Value of new business Retention (lapse rate) 6 Penetration (cross sell) B New business volume 7 • Reduction in claims fraud • Settlement period from weeks to days • Fraud management • Convert analogue process to digital • AI to drive smarter/quicker settlement Claims (% conversion) C In-force profitability

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