With somewhere around 2,000 artificial intelligence (AI) startups out there, applications have been identified across every single sector you can think of. While few industries are as mundane as Insurance, it starts to become interesting in the context of using AI in Insurance. On one hand, the predictive powers of AI threaten to all but replace human actuaries resulting in reduced labor costs and more accurate predictions. On the other hand, autonomous cars threaten to decimate traditional auto insurance premiums.
The insurance industry is roughly divided into Life, Health, and Property & Casualty (P&C). We’ve thinly touched on technology innovation in P&C with an article aboutMetromilewith its “pay-as-you-go auto insurance coverage”. Metromile’s technology automates the collection of statistics like distance traveled or driver behavior to rationalize auto insurance coverage. Why is this so meaningful? Take the below excerpt from a recent report by McKinsey titled “Time for insurance companies to face digital reality“:
So essentially, auto insurance companies are not operating in a sustainable fashion and the only way we can resolve that is through technology. Maybe that’s why venture capitalists are pouring money into Insurance Technology or “InsurTech”. Startups like Metromile are part of the growing trend of investments into“InsurTech” as seen below:
Let’s have a look at some examples of startups that are leveraging artificial intelligence across all areas of the insurance industry.
Founded in 2015, New York-based startup Lemonade has taken in $60 million in funding so far from the likes of Google, Allianz, and Sequoia Capital. Lemonade is a licensed insurance carrier offering insurance to renters and homeowners exclusively through a chatbot app for smartphones. It takes about 90 seconds to get insured and about 3 minutes for claims to be paid. The economical subscriptions of just $5 monthly for renters and just $25 monthly for homeowners are attracting clients from other insurance carriers like these:
Lemonade uses premiums pooled from each peer group to pay for the group’s claim and gives the leftover money to the customers’ common cause. Reinsurance is used to cover cases of claims exceeding whatever is left in the pool. Big Data and machine learning algorithms help combat fraud.
Founded in 2011, it’s a miracle that Oakland California startup Captricity hasn’t had the $52 million they raised jacked yet based on where they decided to setup camp in. We first talked about this amazing startup in a past article about “What Jobs will Robots and AI Do in The Future?” in which we remarked that Captricity has developed machine learning algorithms that can extract and transforms data from handwritten and typed forms at a +99.9%accuracy. Here are a few comments about Captricity’s value proposition from Forrester analyst Ellen Carney:
Capturing and analyzing historical policy data improves underwriting accuracy which is why 50% of the top U.S. insurers now use Captricity.
Founded in 2014, Silicon Valley startup Cyence has taken in $40 million in funding so far to develop an analytics platform that can quantify the financial impact of cyber risks. Insurance is all about managing risk, and one of the biggest operational risks companies face is that of cyber security. A single hacker can steal information that might be worth billions of dollars to a company. As an insurance company, how can you offer a policy that covers such a problem if you have no way of assessing the risk that you’re taking? Cyence offers the industry’s first platform that quantifies cyber risk using probabilities and dollars. The volume of Big Data that would need to be analyzed in order to come up with such information is where the machine learning algorithms come in to play.
