Lemonade’s founders started the company believing AI could provide insurance services more efficiently and accurately than humans. In June 2023, the company’s chatbot, AI Jim, settled a claim within two seconds.
McKinsey describes AI’s impact on the insurance industry as “seismic,” predicting it will not only change insurance distribution, underwriting, and settlement significantly but will change insurers’ entire model from “detect and repair” to “predict and prevent.”
Let’s take a look at AI’s potential for the insurance industry before learning how Lemonade is using AI right now to settle almost half its claims.
AI for Insurance – What Could the Future of Insurance Entail?
McKinsey’s AI in insurance predictions for 2030 tells the tale of a customer that self-drives his autonomous vehicle with AI adjusting his premium in real-time based on risks and suggesting the safest route. The customer’s life insurance policy also auto-adjusts because it’s priced on a “pay-as-you-live” basis. The additional amounts are debited from his account immediately. When the driver bumps a parking sign, the vehicle assesses the damage, and his personal assistant instructs him what pictures to take. By the time he gets in the vehicle, the claim is approved.
The consultancy firm published the example in 2021, and it’s fair to say AI developments in 2022 and 2023 have likely taken us closer to this reality despite McKinsey describing it then as “beyond the horizon” but that:
“Such integrated user stories will emerge across all lines of insurance with increasing frequency over the next decade. In fact, all the technologies required above already exist, and many are available to consumers.”
AI’s Use Case in Insurance
McKinsey cited AI developments and says the pace of change will accelerate as brokers and insurers become more adept at using advanced technologies for better decision-making, increased productivity, lower costs, and optimized customer experience.
Insurers take advantage of generative AI chatbots to improve customer service and use AI tools internally to assist with scheduling, dealing with emails, marketing outputs, and much more. There are also some very specific use cases.
Risk assessment and customer understanding in underwriting
AI can provide insurers with more data, instantly, and provide access to new data assets from digital partners. Insurers can use telematics, remote sensors, satellite images, and even digital wellness records, and AI can analyze all these instantly to help provide very specific coverage and pricing.
Insurers can also use AI to identify high-risk and potentially fraudulent claims and route them effectively, prioritizing genuine customers to provide better service.
Swiss Re is already using AI in its Life & Health automated underwriting solution platform.
Improving processes, products, and coverage on the claims side
So there’s vast potential for efficiencies and insights into insurance risk and claims incidents, but AI can also facilitate new solutions and help to develop coverage for risks that have in the past been uninsurable. Swiss Re has also developed a flight delay compensation tool that uses 200 million historical data points and pays out instantly without customers needing to file a claim.
Reducing car accident fraud and detecting driving style
McKinsey already gave an example of super-enhanced auto insurance. Swiss Re says an Italian startup has already been granted a patent to record footage from the front of a moving vehicle, identify the driver’s driving style, and certify accidents. Footage is taken to the cloud in real time, and algorithms anonymize other people’s data in compliance with privacy regulations such as GDPR.
Swiss Re is also investigating AI in its core processes and for decision-making. It, too, believes that with responsible implementation, AI can impact the entire insurance value chain and give substantial benefits to customers.
How Lemonade Uses AI for Revolutionary Insurance Services
Lemonade broke a world record in 2023 with its two-second settlement of an insurance claim using AI and machine learning. The chatbot, AI Jim, was able to assess the claim, check policy conditions, and use dozens of anti-fraud algorithms before sending the payment instructions directly to the customer’s bank.
This innovative InsureTech firm has combined AI chatbots, the cloud, and made the customer the “human-in-the-loop” (HITL), per HBR, to eliminate distrust between insurance companies and customers.
To file claims, Lemonade customers tell a chatbot what happened. They don’t have to wait in a telephone queue for a customer service center agent, get transferred between departments, or fill in forms. Around 30% of Lemonade’s claims are paid out instantly once its AI has run the anti-fraud algorithms. Other claims are escalated to a human agent.
In an earnings call with investors, after exceeding revenue expectations, Lemonade’s CEO Daniel Schreiber says Lemonade was “built for AI since day one.” Lemonade is full-stack AI-driven and its processes are highly automated. It uses in-house AI technology and natural language processing (NLP) to handle its data. Schreiber says:
“If you haven’t architected your company so that AI has access to deep information, it will be hard to glean the type of deep insights we’ve built our business upon.”
Lemonade expects its AI-powered underwriting and risk management policies will be increasingly accurate over time as well as more profitable. 98% of all its claims already start with AI Jim in its app and 40% of claims require no “human intervention at all” says Schreiber.
The innovative company’s AI specializes in using contextual data to analyze risks, damage, repair costs and anything else relevant to a claim.
In a blog penned by Schreiber on Lemonade’s website the CEO explains how “AI Can Vanquish Bias.” He concludes:
“Insurance is the business of assessing risks, and pricing policies to match. As no two people are entirely alike, that means treating different people differently. For the first time in history, we’re on the cusp of being able to do precisely that.”
Though the CEO discusses bias, achieving modern-day customer’s expectations of personalization, and hyper-personalization is another way AI will transform the way we do business.
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