Insurance in the digital era: use cases

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1 Insurance in the digital era: use cases Miami, August 28 th, 2018

2 HCS Capital approach to investing InsurTech Drivers: AI and digitalization FinTech & InsurTech Fund Corporate Venture Capital as-a-service Machine Learning 2

3 About HCS Capital HCS Team Alex Horvitz CEO Luis Felipe San Martín Managing Partner Ryan Smith Associate Raphael Geronimi Machine Learning Expert Over 30 years of experience managing businesses and defining and implementing growth and optimization strategies Former Director at McKinsey & Company where he served as the leader of the Insurance, Banking and Technology practices in Europe and Latin America. Senior executive with Allianz SE where he led the creation of Allianz Partners (largest B2B2C insurer in the world). Director of strategy and marketing at Allianz Partners. M.S. in Industrial and Operations Engineering from the University of Michigan. Over 10 years of professional experience in private and public sectors (finance, PGC and government management). Worked at P&G and Walmart, and held leadership positions in the Government of Chile during President Piñera s first administration. Led the due diligence and deal closings of HCS Tech Fund I investments in InsurTech and Fintech. M.B.A. from Harvard Business School and M.P.A.-ID from Harvard Kennedy School of Government. B.S. in Industrial Engineering from Universidad de Chile. Extensive experience within the public and private sectors. He has served as a special assistant and adviser to a U.S. presidential candidate and has worked in multiple administrations. Worked at Perella Weinberg Partners asset management division, where he analyzed global hedge fund credit and equity strategies. Worked as an associate at Chrysalis Ventures, where he spent time in portfolio operations and investment due diligence. M.B.A. from The Wharton Business School. B.S. in Political Science and Economics from The University of Kentucky. 10 years contributing to top corporate transformations, incl. 3 years with McKinsey. 7 years directing data-oriented programs for Société Générale investment bank: Structured finance deals migration to Basel II, Trader fraud detection, Global IT transformation program. Founder and Chief Scientific Officer of Portendo Analytics, HCS s sister company, specialized in designing and implementing large scale & high performance machine learning platforms for finance, insurance and e-commerce companies. M.S. in Mathematics and Computer Science from French Ecole Polytechnique. 3

4 HCS Capital approach to investing Target Sectors: FinTech and InsurTech Sectors Geographic Scope: North and South America InsurTech FinTech North America Distribution of specialty insurance Claims, fraud and risk management Retail property & casualty Industrial processes SME insurance Travel & expat health insurance Artificial Intelligence Money transfer and payments Personal loans Mortgages Savings and investments SMEs credit Underlying Technologies Machine Learning & Predictive Analytics Digital, big data driven platforms Budgeting and financial planning Risk & compliance Sectors: InsurTech & Underlying Technologies Focus: Series A and later stage firms that are prepared to scale globally South America Sectors: InsurTech, FinTech & Underlying Technologies Focus: Series A and later stage firms that are prepared to scale to North and South America Internet of Things 4

5 HCS Capital approach to investing InsurTech: Drivers and opportunities Drivers Insights Investment opportunities in the US & Latin America 1 Shifting behavior towards insurance Customers are looking for solutions rather than specific products or services, leading to the emergence of platform-based ecosystems Clients (individual or companies) expect high quality digital interaction Specialty insurance marketing and distribution Pet & equine insurance Car collectors insurance Renters & security deposit Travel and expat health insurance 2 From value-inservice to value-in-use Digital interaction is transforming distribution, product structure, and client interaction, leading to lower client and servicing costs Customer understanding and continuous engagement create the opportunity for micro products Claims processing platforms AI-based automated claims processing platforms Fraud detection 3 4 A.I. and Machine Learning Internet of Things (IoT) for risk management Machine learning is transforming client interaction, churn management, fraud detection, micro pricing/lower loss ratios Cognitive processing (natural language processing) and robotics will optimize all operational areas leading to greater productivity and quality The explosion of connected devices (from 23 billion today to 75 billion in 2025) generates tremendous amounts of new data and, when combined with analytics, can produce distinctive risk management insights IoT will impact all areas of insurance Insurance products for SMEs Internet of Things (IoT) enabled & telematics P2P insurance platforms Credit default insurance for P2P credit and factoring platforms Low complexity industrial processes Internet of Things monitoring and automation Optimized data based risk transfer mechanisms Connected car insurance 5

6 HCS Capital approach to investing Machine Learning: Core techniques Family Description Application examples 1 Supervised learning The algorithm learns with past data how context variables (e.g., user age, marital status, revenues) are linked to an outcome (e.g., did he purchase or not), and use it to predict future outcomes on new data Traditional insurance underwriting Fraud detection 2 Unsupervised learning The algorithm discovers the structure of data set (e.g., the various categories or topics ). From there it can also detect changes in real-time new data Customer segmentation Error detection 3 Reinforcement & bandit learning The algorithm determines optimal action plan toward an objective (e.g., maximize revenues), balancing exploration and exploitation of opportunities Merchandising optimization Pricing optimization

7 Insurers can create substantial value by using Machine Learning in 3 key areas: Churn and sales optimization, Micro Pricing and Fraud Detection Area Description Impact 1 Churn and sales optimization Optimize different sales channels (including remote) through automatic machine learning models Higher revenues Better call centers profitability Uncovering and resolution of pockets of anomalies 2 Micro Pricing Optimize on a personalized basis: Each contract price based on signup-time price elasticity and later churn behavior Expected losses from different types of insurance claims Each contract price based on behavior of client across channels (e.g., second call with agent) Better technical and commercial pricing Identification of pockets of good risk within bad risk segments 3 Fraud Detection Apply a broad range of machine learning techniques to identify different types of fraud, from identity fraud at application to false insurance claims Reduce costs from false claims Prevent application fraud

8 HCS Capital approach to investing InsurTech Drivers: AI and digitalization The transformation of the P&C value chain from Artificial Intelligence (AI) and Digitalization. P&C Insurance Industry value chain: Present and Future. Costs and margins disaggregation (%) The Present: Traditional P&C insurance value chain with an MGA in the front, an underwriter, and a reinsurer 100 Written Premiums Sales & Marketing 24 Distribution Admin & Claims 6 MGA Margin 60 Loss Ratio Margin for insurer and reinsurer 10 Margin for risk carriers 1 A Managing General Agent (MGA) assumes oversight of marketing, distribution, and claims processing. By optimizing the brand and user experience, an MGA lowers customer acquisition costs and boosts retention. MGA s margins are increased by leveraging AI in areas such as: Customer Service (cost reduction) Claims & Fraud (loss reduction) Sales Optimization (CAC reduction) Cross Selling (revenue increase) The Future: Technologyenabled modern insurance value chain with intensive AI adoption, an MGA, and a single risk taker 100 Written Premiums 1 Sales & Marketing 22 The MGA controls the end to end consumer journey in a more efficient way by leveraging digital distribution, automating claims processing and even pricing Distribution Admin & Claims 10 MGA Margin 56 Loss Ratio 90% of the revenue can be optimized using AI based and digital technologies to lower acquisition costs, reduce fraud, increase client satisfaction, and improve risk pricing 2 AI allows better pricing and reduces loss ratios 3 Single risk carrier 12 Re Insurer s Margin 2 Introducing advanced Machine Learning algorithms allows MGAs to support the risk carrier (value sharing model) by improving pricing, thus reducing the loss ratio. That extra margin is shared among both the MGA and the risk carrier. 3 As MGAs take control of distribution, claims processing, and customer journey, risk carriers can provide insurance capacity directly to the end customer, thus reducing overhead. 4 Economic surplus will increase by 30 to 40%. And 2/3 of this value will be captured by the MGAs and 1/3 by the risk carrier. 8

9 HCS Capital approach to investing InsurTech Drivers: Leveraging data collected from IoT The volume of data generated by the Internet of Things is staggering. Users are increasingly willing to share their data in exchange for greater value. IoT main benefits Car Insurance Accurate driver risk assessment Driver behavior modification and risk reduction Lower customer premiums IoT main benefits Health Insurance Higher drug adherence and behavior modification More accurate health risk assessment Higher patient engagement Lower treatment costs Home Insurance IoT main benefits Real time proactive alerts that prevent major damage Higher customer engagement Faster claim processing Personalized risk ratings Industrial Insurance IoT main benefits Real time monitoring Ability to remotely control and automate processes Predictive maintenance Operating cost savings Accurate risk assessment Benefits for InsurTech companies More accurate insurance pricing Identification of good risk in pockets of bad risk Enhanced customer satisfaction Higher loyalty and stickiness Higher revenues and margins Sources: IoT and the State of Insurance Industry Study LexisNexis, Insurers need to plug into the IoT (or risk falling behind) McKinsey and Co.,

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11 Value in use Figo Pet Insurance In-Force GWP (USD) per company (US) North American Pet Health Insurance Association (NAPHIA) Company GWP growth % growth Nationwide 314,400, ,600,000 60,200,000 19% Trupanion 160,200, ,600,000 31,400,000 20% Healthy Paws 81,300, ,200,000 41,900,000 52% Embrace 45,300,000 61,700,000 16,400,000 36% Crum & Forster 58,000,000 69,200,000 11,200,000 19% Pets Best 41,800,000 51,000,000 9,200,000 22% Figo 2,500,000 8,500,000 6,000, % Pet Plan 78,200,000 83,600,000 5,400,000 7% Pet First 19,500,000 24,900,000 5,400,000 28% Pet Partners 11,600,000 14,000,000 2,400,000 21% Pet Health Inc 26,200,000 27,700,000 1,500,000 6% Total 839,000,000 1,030,000, ,000,000 23% What s unique about Figo? Pure Digital player, born in a Google incubator MGA model, thus no balance sheet exposure, and a very high EBITDA margin on steady state Distictive tech platform: the Pet Cloud, allowing for the creation of a digital ecosystem Customer acquisition costs are 50% lower than industry leaders Young, millennial focused and distinctive brand with a superior digital experience Model (operations and IT) can be easily expanded to Europe, Asia and Latin America (2 to 3 month per country) Outstanding digitally oriented CEO and leadership team 11

12 Value in use Figo s Pet Cloud Figo s first-of-its-kind Pet Cloud is designed to give customers the tools they need to manage their pet s life

13 Value in use Figo s Pet Cloud

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15 Increase the frequency of contact points Improving the digital relationship and knowledge of the insured

16 Predict Consumer Behavior To Customize the Value Proposition and Generate New Services Connecting cars is only the first step, the real value comes from the use of data and applied intelligence to offer customized connected services and micro products

17 Smartcar Insurance & Services Changing the way we relate with our consumer Mechanical Support (B-Call) Contextual Discounts Geolocation Services Safe Driving J Maintenance Reminders Rewards Smart Pricing Jooycar Copywrite Mechanical Diagnostic Crash Detection (E-Call)

18 Insurance in the digital era: use cases

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