{"id":35770,"date":"2018-11-13T19:28:02","date_gmt":"2018-11-14T00:28:02","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/lemonade-re-invents-the-insurance-industry-with-machine-learning\/"},"modified":"2018-11-13T19:28:02","modified_gmt":"2018-11-14T00:28:02","slug":"lemonade-reinvents-the-insurance-industry-with-machine-learning","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/lemonade-reinvents-the-insurance-industry-with-machine-learning\/","title":{"rendered":"Lemonade reinvents the insurance industry with machine learning"},"content":{"rendered":"<p><strong>Introduction <\/strong><\/p>\n<p>Lemonade, a company offering home insurance policies, is a pioneer in the InsurTech world where its use of machine learning (ML) goes beyond satisfying customers and driving efficiencies to underwriting risks and managing claims. Viewing Lemonade as a revolution to the insurance industry, investors like SoftBank and Google Ventures backed the company with a $120 million funding [1]. The investors\u2019 trust was strengthened as the company managed to attract more than 14,000 subscribers in eight months only [2].<\/p>\n<p><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/growth-trajectorhy.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-large wp-image-35667\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/growth-trajectorhy-1024x629.png\" alt=\"\" width=\"640\" height=\"393\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/growth-trajectorhy-1024x629.png 1024w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/growth-trajectorhy-300x184.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/growth-trajectorhy-768x471.png 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/growth-trajectorhy-600x368.png 600w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/growth-trajectorhy.png 1300w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><\/p>\n<p style=\"text-align: center\">Figure 1: Lemonade&#8217;s growth trajectory [3]<\/p>\n<p>Despite its exponential growth, Lemonade\u2019s scalability is questioned considering increasing customer demand and limitations around availability and precision of data.<\/p>\n<p><strong>Lemonade\u2019s unique business model<\/strong><\/p>\n<p>Lemonade\u2019s business model is based on a transparent fee model, fast claim settlement, and social good.<\/p>\n<p>The InsurTech company communicates its fee structure with its customers to achieve trustworthiness and transparency; two key attributes missing in the insurance industry.<\/p>\n<p>Collected customer premium is utilized by Lemonade in the following manner:<\/p>\n<ul>\n<li>20% flat fee for Lemonade<\/li>\n<li>40% for reinsurance to cover major claims<\/li>\n<li>40% for claims; any surplus goes to charity<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Science-behind-lemonade.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-35686\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Science-behind-lemonade.png\" alt=\"\" width=\"800\" height=\"458\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Science-behind-lemonade.png 800w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Science-behind-lemonade-300x172.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Science-behind-lemonade-768x440.png 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Science-behind-lemonade-600x344.png 600w\" sizes=\"auto, (max-width: 800px) 100vw, 800px\" \/><\/a><\/p>\n<p style=\"text-align: center\">Figure 2: Lemonade&#8217;s business model [4]<\/p>\n<p>Apart from its transparent fee model, Lemonade differentiates itself by replacing agents with bots that run insurance processes from end-to-end. However, more than half of Lemonade\u2019s claims are still being handled by humans given their complexity which means that Lemonade still has a long way to go [5].<\/p>\n<p><strong>Use of machine learning to transform the DNA of insurance\u00a0<\/strong><\/p>\n<p>Lemonade uses ML to underwrite customer risk and handle claims transforming insurance from \u201cgrudge purchase\u201d to a \u201cconvenience purchase\u201d. The usage of AI significantly improves processes in insurance as it increases underwriting precision improving premium pricing accuracy, enhances customer experience through fast paper-free processes, and lowers claims costs by reducing fraud.<\/p>\n<p>When issuing insurance policies, Lemonade uses big data to predict risks and quantify losses by placing the customer in a risk group and thereby quoting a relevant premium. These groups of \u201cuniform insurers\u201d share similar risk behaviors and are compiled by AI algorithms that gather extensive customer data and monitor loss ratios (\u201cratio of claims paid by an insurer to premiums earned\u201d [6]). The more data accumulates, the more recursive risk patterns emerge enabling more precise assessments.<\/p>\n<p><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/recursion-2.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-large wp-image-35685\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/recursion-2-1024x310.png\" alt=\"\" width=\"640\" height=\"194\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/recursion-2-1024x310.png 1024w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/recursion-2-300x91.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/recursion-2-768x233.png 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/recursion-2-600x182.png 600w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/recursion-2.png 1030w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><\/p>\n<p style=\"text-align: center\">Figure 3: recursion patters forming with data accumulation [7]<\/p>\n<p>&nbsp;<\/p>\n<p><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/group.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-large wp-image-35683\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/group-1024x719.png\" alt=\"\" width=\"640\" height=\"449\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/group-1024x719.png 1024w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/group-300x211.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/group-768x539.png 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/group-600x421.png 600w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/group.png 1030w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><\/p>\n<p style=\"text-align: center\">Figure 4: improvement of underwriting precision with more data points [8]<\/p>\n<p>&nbsp;<\/p>\n<p>In claims settlement, Lemonade\u2019s \u201cAI Jim\u201d assesses the claim by cross-referencing home information, compares it to the customer\u2019s policy, runs fraud algorithms, and finally approves or rejects a claim. The whole process takes up to three minutes and is approved within seconds [8].<\/p>\n<p>&nbsp;<\/p>\n<p><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Example-of-claim.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-35682\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Example-of-claim.png\" alt=\"\" width=\"800\" height=\"420\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Example-of-claim.png 800w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Example-of-claim-300x158.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Example-of-claim-768x403.png 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Example-of-claim-600x315.png 600w\" sizes=\"auto, (max-width: 800px) 100vw, 800px\" \/><\/a><\/p>\n<p style=\"text-align: center\">Figure 5: claim handled by Lemonade&#8217;s AI Jim [9]<\/p>\n<p>&nbsp;<\/p>\n<p><strong>Lemonade\u2019s scalability questioned <\/strong><\/p>\n<p>Lemonade acknowledges that its AI models and infrastructure are not yet equipped to achieve its innovation targets [10]. Improving current models is important, but the company should also have a vision for its expansion plan to new products and geographies.<\/p>\n<p>The following challenges should be addressed for Lemonade to achieve scale:<\/p>\n<ul>\n<li><strong>Increase in customer demand<\/strong>: increase in claims especially after natural disasters should still be handled in a cost-efficient manner. Will lemonade\u2019s bots and \u201cno-employee\u201d model be able to process all the data as these transactions become more complex? [11]<\/li>\n<li><strong>Data shortage<\/strong>: Lemonade\u2019s databases are still limited. How will it compete with traditional insurance companies that own extensive data and are already digitizing processes? Will Lemonade\u2019s AI-based underwriting still be relevant? [12]<\/li>\n<li><strong>Low quality of data<\/strong>: gathered data is based on customer information which could potentially cover factors important in decision making. How can Lemonade ensure its data is accurate, representative, and unbiased? [13]<\/li>\n<\/ul>\n<p>While the company mentions a medium-term plan to scale, it still does not have a concrete strategy to address the aforementioned issues. Lemonade should consider practical solutions such as acquiring representative external data to train its models, partnering with large insurance companies to handle complex claims, and outsourcing customer service when capacity is exceeded.<\/p>\n<p><strong>Future of machine learning in insurance going forward <\/strong><\/p>\n<p>As the company thinks about improving its current AI models and prepares to scale, it could explore a wider use of AI across the insurance value chain. Will it be possible to use AI in product development i.e. in customizing policies? Can it use ML and IoT to prevent risks from happening? (800)<\/p>\n<p>&nbsp;<\/p>\n<p>[1] Ralph, Oliver. \u201cFinancial Times Softbank Takes Stake in US Insurtech Start-up Lemonade\u201d, Financial Times, December 19, 2017, <a href=\"http:\/\/www.ft.com\/content\/62d7d133-0b69-346d-8c29-6e87848fecbd\">www.ft.com\/content\/62d7d133-0b69-346d-8c29-6e87848fecbd<\/a>, accessed November 2018<\/p>\n<p>&nbsp;<\/p>\n<p>[2] Alois, JD. \u201cLemonade Updates on Platform Growth. Adds 14,300 Customers in 8 Months\u201d Crowdfund Insider.com, June 1, 2017, <a href=\"http:\/\/www.crowdfundinsider.com\/2017\/06\/101283-lemonade-updates-platform-growth-adds-14300-customers-8-months\/\">www.crowdfundinsider.com\/2017\/06\/101283-lemonade-updates-platform-growth-adds-14300-customers-8-months\/<\/a>, accessed November 2018<\/p>\n<p>&nbsp;<\/p>\n<p>[3] Wininger, Shai. \u201cLemonade Exposed. Eight Months In. Lemonade Renters &amp; Home Insurance | Protect The Stuff You Love\u201d May 6, 2018, <a href=\"http:\/\/www.lemonade.com\/blog\/lemonade-exposed-eight-months\/\">www.lemonade.com\/blog\/lemonade-exposed-eight-months\/<\/a>, accessed November 2018<\/p>\n<p>&nbsp;<\/p>\n<p>[4] Ariely, Dan. \u201cLemonade&#8217;s Social Impact in 100 Days. Lemonade Renters &amp; Home Insurance | Protect The Stuff You Love, Lemonade\u201d, May 3, 2018, <a href=\"http:\/\/www.lemonade.com\/blog\/lemonade-social-impact-100-days\/\">www.lemonade.com\/blog\/lemonade-social-impact-100-days\/<\/a> , accessed November 2018<\/p>\n<p>&nbsp;<\/p>\n<p>[5] Flack, Tom. \u201cAnalysis: Lemonade by Numbers.\u201d Insurance Times, August 1, 2017, <a href=\"http:\/\/www.insurancetimes.co.uk\/analysis-lemonade-by-numbers\/1422155.article\">www.insurancetimes.co.uk\/analysis-lemonade-by-numbers\/1422155.article<\/a><\/p>\n<p>&nbsp;<\/p>\n<p>[6] Investopedia. \u201cLoss Ratio.\u201d, June 29, 2018, <a href=\"http:\/\/www.investopedia.com\/terms\/l\/loss-ratio.asp\">www.investopedia.com\/terms\/l\/loss-ratio.asp<\/a> , accessed November 2018<\/p>\n<p>&nbsp;<\/p>\n<p>[7] Schreiber, Daniel. \u201cPrecision Underwriting. Lemonade Renters &amp; Home Insurance | Protect The Stuff You Love, Lemonade\u201d, August 7, 2018, <a href=\"http:\/\/www.lemonade.com\/blog\/precision-underwriting\">www.lemonade.com\/blog\/precision-underwriting<\/a> , accessed November 2018<\/p>\n<p>&nbsp;<\/p>\n<p>[8] Schreiber, Daniel. \u201cLemonade Sets a New World Record. Lemonade Renters &amp; Home Insurance | Protect The Stuff You Love\u201d, May 2, 2018, <a href=\"http:\/\/www.lemonade.com\/blog\/lemonade-sets-new-world-record\/\">www.lemonade.com\/blog\/lemonade-sets-new-world-record\/<\/a> , accessed November 2018<\/p>\n<p>&nbsp;<\/p>\n<p>[9] Wininger, Shai Wininger.\u201cThe Secret Behind Lemonade&#8217;s Instant Insurance \u2013 Lemonade Stories. Lemonade Stories, Lemonade Stories\u201d, November 23, 2016, <a href=\"https:\/\/stories.lemonade.com\/the-secret-behind-lemonades-instant-insurance-3129537d661\">https:\/\/stories.lemonade.com\/the-secret-behind-lemonades-instant-insurance-3129537d661<\/a> , accessed November 2018<\/p>\n<p>&nbsp;<\/p>\n<p>[10] Gogel, David. \u201cInterview with Daniel Schreiber, CEO and Co-Founder of Lemonade. Medium.com, Medium\u201d, December 20, 2016,\u00a0 <a href=\"https:\/\/medium.com\/wharton-fintech\/interview-with-daniel-schreiber-ceo-and-co-founder-of-lemonade-1a6aef384e2f\">https:\/\/medium.com\/wharton-fintech\/interview-with-daniel-schreiber-ceo-and-co-founder-of-lemonade-1a6aef384e2f<\/a> , accessed November 2018<\/p>\n<p>&nbsp;<\/p>\n<p>[11] Accenture. \u201cMachine Learning in Insurance.\u201d, <a href=\"https:\/\/www.accenture.com\/t20180822T093440Z__w__\/us-en\/_acnmedia\/PDF-84\/Accenture-Machine-Leaning-Insurance.pdf\">https:\/\/www.accenture.com\/t20180822T093440Z__w__\/us-en\/_acnmedia\/PDF-84\/Accenture-Machine-Leaning-Insurance.pdf<\/a> , accessed November 2018<\/p>\n<p>[12] Deloitte Digital. \u201cFrom mystery to mastery: Unlocking the business value of Artificial Intelligence in the insurance industry.\u201d, November 2017, <a href=\"https:\/\/www2.deloitte.com\/content\/dam\/Deloitte\/de\/Documents\/Innovation\/Artificial-Intelligence-in-Insurance-Whitepaper-deloitte-digital.pd\">https:\/\/www2.deloitte.com\/content\/dam\/Deloitte\/de\/Documents\/Innovation\/Artificial-Intelligence-in-Insurance-Whitepaper-deloitte-digital.pd<\/a> f, accessed November 2018<\/p>\n<p>&nbsp;<\/p>\n<p>[13] Balasubramanian, Ramnath. \u201cInsurance 2030&#8211;The Impact of AI on the Future of Insurance.\u201d McKinsey &amp; Company, April 2018, <a href=\"http:\/\/www.mckinsey.com\/industries\/financial-services\/our-insights\/insurance-2030-the-impact-of-ai-on-the-future-of-insurance\">www.mckinsey.com\/industries\/financial-services\/our-insights\/insurance-2030-the-impact-of-ai-on-the-future-of-insurance<\/a> , accessed November 2018<\/p>\n<p><strong>\u00a0<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Lemonade, a company offering home insurance policies, is a pioneer in the InsurTech world where its use of machine learning (ML) goes beyond satisfying customers and driving efficiencies to underwriting risks and managing claims<br \/>\nDespite its exponential growth, Lemonade\u2019s scalability is questioned considering increasing customer demand and limitations around availability and precision of data. <\/p>\n","protected":false},"author":11311,"featured_media":35842,"comment_status":"open","ping_status":"closed","template":"","categories":[1869,5059,298,259,5060,730,3953,346,664],"class_list":["post-35770","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-ai","category-artfiical-intelligence","category-big-data","category-fintech","category-home-insurnace","category-insurance","category-insurtech","category-machine-learning","category-scalability","hck-taxonomy-industry-insurance","hck-taxonomy-country-united-states"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/rc-tom-challenge-2018\/","yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - 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