How Artificial Intelligence is Transforming the Insurance Industry

The big picture

• The National Association of Insurance Commissioners reported in March 2020 that the use of AI by insurers has grown exponentially over the past few years and that “the acceleration in AI is being driven by exceptional technological advances along with a major shift in customer expectations.”
• More and more consumers want a completely digital buying experience
• AI companies like Zelros allow insurance providers to offer policyholders fully automated, advisor-free subscription options.
• An ecosystem of start-ups developed around the insurance industry, proposing AI-based fraud management, product distribution, customer onboarding, risk assessment, underwriting and pricing, claims, policy reviews, and other services

• McKinsey projected a potential annual value of up to $1.1 trillion in additional business revenue if AI is fully embraced in the insurance industry alone
• According to Mc Kinsey, 4 trends are driving the AI adoption in Insurance
• Experts estimate there will be up to one trillion connected devices by 2025. The resulting avalanche of new data created by these devices will allow carriers to understand their clients more deeply, resulting in new product categories, more personalized pricing, and increasingly real-time service delivery.
• Increased prevalence of physical robotics.3-D-printed buildings will be common, programmable, autonomous drones; autonomous farming equipment; and enhanced surgical robots will all be commercially viable, and carriers will need to assess how this development changes risk assessments. A much larger proportion of standard vehicles will soon have autonomous features, such as self-driving capabilities. Carriers will need to understand how the increasing presence of robotics in everyday life and across industries will shift risk pools, change customer expectations, and enable new products and channels.
• Open-source and data ecosystems. Open-source protocols will need to emerge and ensure data will be shared and used across industries. The best-case scenario will see various public and private entities come together to create ecosystems in order to share data for multiple use cases under a common regulatory and cybersecurity framework. For example, wearable data could be ported directly to insurance carriers, and connected-home and auto data could be made available through Amazon, Apple, Google, and a variety of consumer device manufacturers.
• Advances in cognitive technologies. Convolutional neural networks and other deep learning technologies will be applied in a wide variety of applications. These cognitive technologies will become the standard approach for processing the incredibly large and complex data streams that will be generated by “active” insurance products tied to an individual’s behavior and activities. Carriers will have access to models that are constantly learning and adapting to the world around them — enabling new product categories and engagement techniques while responding to shifts in underlying risks or behaviors in real-time.

Be smart

• Insurance companies are multiplying joint ventures and partnerships with AI shops
• Acquisitions will follow
• The focus is on using the most advanced data analytic techniques available to simplify and accelerate processes like development, underwriting, marketing, and distribution.
• As life insurance and investment companies are emerging from the pandemic, they’re looking for unique ways to position themselves ahead of the curve.
• More insurers will consider or deploy cognitive and related technologies to use data for product development.

Why it matters

• Consumers are increasingly demanding highly personalized offers in real-time
• Distribution of insurance products get faster with the use of AI algorithms that rank businesses and individuals risk profiles based on IoT and alternative data
• Underwriting is streamlined with the use of models that calculate the risks based on real-time changing factors
• Claims are processed with AI-Based Image Recognition and Processing
• Automation tools improve the first notice of loss (FNOL) and triage processes by speeding up the review of damaged photos, identification of total loss vehicles and supports the identification of the next best action for repairable vehicles. Decisions that affect claims outcomes for the insurer, repairer, and insured are made at the beginning of the claims process.
• AI-based natural language (NL) platform can automate the reading, understanding, and extraction of meaningful data from structured and unstructured text to augment and expand insights for every process that involves language

Yes but

What are the privacy and consumer protection rules in the future where your watch, your shoes, your car, your phone, and home sends data to your insurer?

• if deployed at scale, even a minimal bias in an AI system can affect large numbers of individuals.
• Providing meaningful explanations is a challenge, as some ‘black box’ algorithms are by nature complex — the price to pay for better accuracy — and therefore difficult to interpret and explain.
• Insurers and banks are huge, slow to adapt, extremely dependent on legacy systems conservative entities

What’s next

• There is a global convergence towards five core principles for responsible AI: (1) transparency and explainability, (2) fairness, (3) safety, (4) accountability, and (5) privacy. Considerable uncertainty remains, however, regarding how ethical principles and guidelines should be implemented in a specific context
• Usage-based insurance (UBI) products will proliferate and will be tailored to the behavior of individual consumers
• Usage-Based Insurance (UBI) is a type of auto insurance that tracks mileage and driving behaviors. UBI is often powered by in-vehicle telecommunication devices (telematics)-technology that is available in a vehicle that is self-installed using a plug in-device or already integrated into original equipment installed by car manufactures. It can also be available through mobile applications. The basic idea of UBI is that a driver’s behavior is monitored directly while the person drives, allowing insurers to more closely align driving behaviors with premium rates.
• Example of UBI: pay-by-stay insurance for home-sharing services, such as Airbnb. Slice Labs provides variable commercial insurance specifically tailored for home-sharing.

What people say

• “Digital transformation is fundamentally changing how businesses operate, and with insurtech funding reaching an all-time high of $7.1 billion in 2020, the insurance industry is no exception,” said Christophe Bourguignat, co-founder and CEO, Zelros.
• With expert.ai, Patra is unlocking the ability for clients to be alerted of policy inaccuracies, reduce E&O exposures, drive cost savings, create additional value for our services, and push the limits of today’s technology,” said John Simpson, CEO, and Founder of Patra. “Policy Checking has been one of the insurance industry’s biggest challenges for decades. Now, with expert.ai and the formation of the InsureConneXtions Alliance, Patra has brought to market a proven leader in artificial intelligence, in addition to partnering with innovators in the insurance industry to solve challenges that apply to every policy issued. Policy Checking is just the first of many services we are addressing.”

What I think

• AI technologies are deeply transformative for the insurance industry
• Everything, literally every aspect of their business is changing
• From customer onboarding to risk assessment, to permanent connection with their clients
• This is extremely impactful for corporations deploying IoT that can be leveraged to negotiate insurance premiums as factory and supply chain based connected devices funnel data to their insurer
• The challenges are immense for the society, as a whole, governments, regulators on how to craft the path toward sustainable and respectful use of human activity produced data
• The benefits are immense for health insurance and life insurance but the drawbacks can be catastrophic without the right guardrails
• The EU is building an AI regulatory framework, 10 years from now every major power will have one

Go deeper

Driving the news

• The Guardian Life Insurance Company of America (Guardian Life) announced it has entered into a joint venture with the AI and predictive analytics innovators at Atidot. The collaboration is focused on creating a platform that deploys artificial intelligence and machine learning to power data-driven decision-making that helps make insurance products and services easier for consumers to understand and buy.
• Zelros, an industry’s first AI-driven platform dedicated to advancing insurance distribution, announced the successful close of an $11 Million Series A financing round, bringing the company’s total funding to date to $16.5M. Silicon Valley-based BGV led the round with new participation from ISAI Cap Venture and Plug and Play. Historical investors HI INOV, 42CAP, and astorya.vc also participated in the round.
• Earnix, a global provider of advanced AI-driven rating, pricing, and product personalization solutions for Insurance and Banking, has announced $75M in growth funding with a pre-money valuation of $1B. The round was led by Insight Partners, with existing investors JVP, Vintage Partners, and Israel Growth Partners joining the round.
• Patra, a leading provider of technology-enabled services for the insurance industry, and expert.ai, an artificial intelligence solution for natural language understanding and natural language processing (NLU/NLP), announced a partnership that brings efficiencies to a variety of insurance processes. This partnership delivers AI-powered policy checking to the insurance market today.
• Zesty.ai, a leader in climate risk analytics powered by Artificial Intelligence (AI), announced that The Cincinnati Insurance Company has signed a long-term contract to fully integrate Z-FIRE across the Cincinnati Insurance portfolio. With Z-FIRE, Cincinnati insurance agents are able to assess wildfire risk using an AI model that’s been trained on more than 1200 wildfire events across several decades and account for the property-level factors that contribute to wildfire risk, compared to the regional perspective that legacy models rely on.
• Hi Marley, creators of a smart SMS platform purpose-built for the insurance industry closed a $25 million Series B financing round. The investment was led by Emergence Capital. Returning firms Underscore, True Ventures, Bain Capital Ventures , and Greenspring also participated in the round, along with additional investors including Brewer Lane Ventures.
• LARUS Business Automation announced the results of the application of the LARUS Galileo Graph Explainable Artificial Intelligence (GXAI) platform powered by Fujitsu Deep Tensor Technology at a large insurance company in Italy. Based on the preliminary results, the fraud detection rate improved from 18% to 81% while the number of false positives decreased from 82% to 19% over traditional rules-based approaches.
• Arturo, an AI-powered platform that derives property insights and predictive analytics from aerial and satellite imagery, announced the addition of machine learning expert Roman Bueglerto to the team as vice president of research and development. Based in Munich, Buegler will be focused on building out the team to develop new machine learning products and further expand Arturo’s property analytics capabilities on satellite and aerial imagery for the global insurance industry.
• TrustLayer, a collaborative risk management platform developing a digital proof of insurance solution, completed a $6.6 million seed round of financing. Abstract Ventures led the round with participation from Propel Venture Partners, NFP Ventures, BoxGroup, and Precursor Ventures. . Some Insurance agencies participated including Holmes Murphy, Heffernan, M3, NFP, and Graham Company.

What to read

• Insurance 2030 — The impact of AI on the future of insurance — McKinsey A must read
• National Association of Insurance Commissioners (NAIC) Principles on Artificial Intelligence (AI) Adopted by the NAIC Membership on Aug. 14, 2020
• Challenges for the Insurance Industry in the Future, Journal of Insurance Regulation

CIPR Event: Demystifying the Use of AI in Insurance

• Presentation: How AI Has Transformed the Insurance Industry(Satadru Sengupta, Halos)
• Presentation: AI in Commercial Insurance (Max Drucker, Carpe Data)
• OECD Principles on Artificial Intelligence
• Intelligent Machines and the Transformation of Insurance
• This post is part of Convergences by Melvine. A series exploring how software is changing every corner of human activities. Melvine Manchau