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How AI Is Changing The Game In Insurance

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The insurance industry is one of the largest in the world and has been around for hundreds of years, making it ripe for transformation by newcomers in the space. Over the past five to ten years, technology has pushed the frontier of what’s possible, making way for a new breed of digital-first insurance companies to come to life. The use of technology, data, artificial intelligence (AI), and modern design has created a powerful combination, changing what was once a very policy-centric industry to one that’s customer-centric.

I recently had the chance to speak to Daniel Schreiber, co-founder CEO of Lemonade, the digital insurance company powered by social impact with a mission dedicated to building the “most loveable insurance” available. During our conversation, he spoke about the company’s use of AI and big data, how it impacts the customer experience, and the opportunities (and, at times, challenges) it brings to the industry.

Gary Drenik: Can you share more on how Lemonade is using AI?

Daniel Schreiber: We describe Lemonade as being built on behavioral economics and artificial intelligence, which has been true since Lemonade was founded. As a new company looking to disrupt what’s been the go-to model for a centuries-old industry, we wanted to harness the power of AI and big data to not only power our own product but encourage the industry to do the same. In an ideal world, this would lead to insurance becoming fairer, cheaper, and faster. No two people are entirely alike; different people should be treated differently—this should be reflected in how insurance assesses risk and prices policies in a world of individuals.

At Lemonade, AI is deeply integrated into our product and also internal processes. Interactions with our customers across our platform generate a trove of data, which in turn improves future interactions. This includes interactions with our chatbots AI Maya, a playful onboarding and customer experience bot, and AI Jim, our claims bot that handles the “first notice of loss” (and many times can manage a claim start to finish). Internally, AI deeply impacts our approach to our book of business through advanced machine learning models, like our recent LTV6 model, and Lemonade’s forensic graph, which utilizes AI combined with the power of behavioral economics and big data to predict, deter, detect, and block fraud throughout the customer engagement.

Drenik: Can you dive into more about how this impacts the customer experience?

Schreiber: When Lemonade was founded six years ago, part of our mission was to digitize insurance end-to-end, leveraging technology, data, and artificial intelligence to create a more delightful, affordable, and precise approach. We wanted to build a product that would appeal to the next generation of consumers, which meant easy-to-use, personalized, and efficient service when and where they needed it.

A two-minute chat with our bot, AI Maya, is all it takes to get a personalized quote, sign up for a policy, and facilitate payments. AI Jim is our claims bot that handles the “first notice of loss” for almost all Lemonade claims and can manage an entire claim through resolution without any human involvement for almost half of all claims. This breezy experience from start to finish is a core part of what makes Lemonade unique—giving customers a seamless, delightful experience.

Today, a majority of our customers are under the age of 35—according to a recent Prosper Insights & Analytics Survey, more than 30% of this general age range (Gen-Z and Millennials) are looking to move in the next six months. Whether that’s renting their first apartment or buying a home, this opens up Lemonade to two separate opportunities with both Renters and Homeowners insurance, and our use of AI makes it possible for either audience to get a quote and obtain a policy in a matter of minutes.

Drenik: Beyond Lemonade specifically, how do you see AI and big data impacting the broader industry?

Schreiber: When we’re assessing risk and pricing policies, the factors that come into play (e.g., credit scores) have been used for decades. Thankfully, no insurer will ever use membership in a ‘protected class’ (race, religion) as a pricing factor. But there remain systematic issues at the root of factors like credit scores. This is where I believe big data and AI can make a huge difference—when properly implemented, AI can help solve some of the fairness issues we see in the industry today.

As an industry that relies heavily on proxies like gender and credit score, there’s a lot of opportunity at hand. Some feel that more data will only exacerbate a problem; however, in insurance I believe the opposite is true. We’ve been generating and advocating for frameworks to test this theory, one being the idea of Uniform Loss Ratio (ULR). Simply put, by using big data and AI individuals would be charged a rate directly proportional to the risk they pose, creating a constant ratio across an insurer’s customer base. We have a way to go, but we’re hopeful it’s a future we can prepare to embrace.

Drenik: AI ethics has been a big conversation over the past few years. What do you think about this, especially with regards to insurance, and how has Lemonade approached the topic?

Schreiber: The insurance industry has had a long history of red-lining, and concerns of discriminatory treatment in both pricing and the way claims are investigated and paid out. And, if not leveraged carefully, AI has the potential to continue & intensify these concerns.

Last year we brought on Tulsee Doshi as our AI Ethics and Fairness Advisor to help ensure both Lemonade and the future of insurance is one where opportunity is available, equitably, to everyone—a passion we both share. We also wanted to broaden the conversation beyond our own four walls and this year launched a limited-series podcast, Benevolent Bots. With experts across the industry, Doshi and I dive into varying topics related to the nuances, complexities, and opportunities that AI brings to the table.

We’re always working to ensure fairness, safety, and accountability is a key part of our design process, and we hope these conversations also inspire important discussions - and ultimately change - across the industry.

Drenik: You mentioned the podcast Benevolent Bots you started. After talking with so many experts in the space, any key takeaways, or favorite moments?

Schreiber: In both bringing on Doshi as our AI Ethics and Fairness Advisor and in the various episodes of Benevolent Bots, many important and interesting questions have been raised about the use of AI.

Each episode brings a unique perspective given the guest’s expertise. In our first episode we spoke with Meg Mitchell, a research scientist focused on algorithmic bias and fairness in machine learning. Our conversation was eye-opening and touched on a critical point around when to use AI and how to ensure human values and perspectives are incorporated, which can be applied to industries far beyond insurance. In another episode we talk with Ivana Bartoletti, Global Chief Privacy Officer at Wipro, about the privacy and the responsibility that comes with collecting the vast amount of data that’s available to companies these days. While more data gives us better precision and personalization in pricing, Bartoletti was firm that more data means a responsibility to the consumer, increasing efforts to protect privacy—a stance we absolutely agree with at Lemonade and hope to see implemented throughout our industry and more.

Drenik: Thanks, Daniel, for the insights into Lemonade’s approach to AI and what it means for your customers. It was great to chat, and I look forward to seeing what’s next for you and the Lemonade team!

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