Carriers Will Pay When Insurtech Doesn’t Deliver on Big Promises

Carriers Will Pay When Insurtech Doesn’t Deliver on Big Promises

Carriers Will Pay When Insurtech Doesn’t Deliver on Big Promises

A startup claiming to predict disaster damage and optimize response has attracted insurers’ interest, but flaws in the methodology could put carrier partners at risk.

The promise of new technology historically tends to be rooted more in hype than reality. Insurtech is not immune.

While Insurtech has proven useful in streamlining claims management, garnering more granular data and improving customer experience, it hasn’t revolutionized the industry as dramatically as some predicted.

In addition to its advantages, any new tool or solution inevitably introduces its own risks — one of which is the chance that it will underdeliver on its promises or fail altogether.

A recent New York Times article detailed one such example in a Silicon Valley-based startup claiming to use artificial intelligence and machine learning to optimize disaster response.

The Product

One Concern is a tech firm founded by Stanford grads seeking to help cities prioritize first response efforts after a disaster.

Often, as in the earthquake that struck Napa Valley in 2014, emergency responders are inundated with 911 calls from all over the region and struggle to determine who is in the greatest danger and should be rescued first. A disorganized response could result in many preventable deaths.

Using a city’s property, topographic, seismographic and demographic data, One Concern claims to be able to predict an earthquake’s damage with up to 85% accuracy within 15 minutes.

Using artificial intelligence, the models are meant to continually update as real-time information is fed into the system during a disaster. These prediction models can theoretically help city emergency departments pre-plan their disaster response efforts, prioritize hardest-hit areas first and save more lives.

So far, One Concern has attracted $55 million in venture capital funding and has worked with the U.S. cities of San Francisco and Seattle, as well as the Japanese city of Kumamoto and the states of Pennsylvania and Arizona.

The Controversy

A few cities have decided not to renew their contracts with One Concern after discovering errors in its prediction models.

These errors, the cities claim, are so significant that disaster response decisions based on the startup’s models could actually lead to greater loss of life.

An official with Seattle’s emergency department, for example, noted some major structures in the metropolitan area, including a big box store and parts of a university campus, were left out of the analysis completely due to lack of data.

Many have also complained about the lack of transparency in how One Concern generates its models and applies artificial intelligence, and how it arrives at its touted figure of 85% accuracy within 15 minutes. The company has not disclosed how it tests the accuracy of its models, and has not submitted its results for independent, third-party review.

Of the data sources and methodology that One Concern has disclosed, the Times article points out that much of it is already publicly available, free of charge. This includes building codes, liquefaction maps, census data and FEMA resources including their own damage-prediction tools.

One Concern’s business model has also drawn ire.

The company has partnered with insurance companies that will pay for a city’s use of the service in exchange for the data that One Concern compiles and the models it builds.

This is currently the case in Seattle, where American Family Insurance is subsidizing the cost of the service, and in Japan, where the nation’s second-largest property insurer, Sompo, is covering the cost for Kumamoto.

Critics claim the partnerships demonstrate a prioritization of profit over the stated purpose of saving lives.

This article originally appeared on riskandinsurance.com To read the full article, click here.

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