Is Loop's Equitable Model the Usage-Based Insurance's Lifeline?

Loop is an American insurance startup looking to reshape the industry by offering fairer and more transparent automobile insurance prices through telematics and artificial intelligence (AI). Instead of using traditional underwriting models based on demographics (e.g., educational attainment, credit score, homeownership) that disproportionally overcharge indebted and low-income individuals, Loop developed risk assessment algorithms that only consider how and where their customers drive.

The company uses TomTom's maps, speed profiles, and traffic stats to determine road risk and add context to its telematics data collected via Loop's smartphone app. Context is crucial in telematics-based driver performance because it can establish whether an event indicative of poor driving is intentional or based on the condition of the road—for instance, a harsh braking event due to kids on the street instead of speeding—preventing bias. Also, by combining AI algorithms with the maps and traffic data, Loop can suggest safer driving decisions and rerouting that avoid roads at high risk of car accidents in real-time.

Telematics and usage-based insurance (UBI) have been available for over a decade, and presently the market is stagnating or even declining in countries like the U.S. Still, Loop—which is not currently live—has a waiting list of over 30,000 people and raised US$3.25 million in funding. Which raises the question: is Loop's all digital equitable model Usage-Based Insurance’s (UBI's) lifeline?

The ultimate goal of UBI for insurers is assessing driver behavior to be more assertive in determining their risk, calculating the policy price, and, most importantly, improving driver behavior to reduce their risk profile and probability of accidents. Improving driver behavior is key to delivering value as customers can see a direct relationship between driving and policy price, which will build customer loyalty. Yet, most insurers offering UBI fail to achieve it due to low customer interaction and little effort for customer retention, struggling to deliver a value proposition. Even though insurers are migrating to smartphone-based policies like Loop, eliminating hardware (e.g., on-board diagnostics (OBD) dongle, black box) costs, most programs do not advance from the proof-of-concept stage because they cannot justify return on investment (ROI).

Loop has a clear value proposition to offer a fair price to its customers, targeting its products to minorities, low-income, and indebted individuals that are often penalized with high insurance prices regardless of their driving habits. Also, it is a certified B-Corp—businesses with the legal obligation of balancing profit and positively impacting their employees, communities, and the environment—which reinforces its commitment to an equitable insurance model.

The strategies to encouraging 'positive' behavior are well determined. The company will send weekly reports with analytics and a percentage of driving on safe roads, making drivers aware of how their data is used and allowing them to make better decisions based on the relevant indicators. Drivers will also receive real-time push notifications with alternative routes that avoid unsafe roads and better behavior suggestions.

Loop's UBI offering is similar to other solutions available today. Its main differentiators are the underwriting algorithms which are purely based on telematics and location data, clear commitment to improving driver behavior, and its B-Corp designation. While they address the key challenges mentioned above and ROI is easier to justify due to its all-digital approach, are they enough to succeed in a declining market?

The insurance industry is notorious for a profit-centered approach and lack of innovation; the UBI market has been remarkably slow in responding to the changes caused by the COVID-19 pandemic. Thus, it is not surprising that a new competitor with a slightly different product and strong social mission attracts attention. However, tinkering with the algorithms to incorporate context to make risk analysis a little more accurate is unlikely to lead to a vast consumer uptake suddenly.

Loop targets a niche market of customers that do not conform with the indicators used by more conventional companies and are open to an all-digital, with no physical offices, app-based approach, limiting its growth potential. The product could be used for fleet management because there is always value in better understanding context—for instance, knowing that a truck is doing 50mph in a 50mph zone while everyone else on the same stretch of road slows down to 30mph—for driving behavior analysis and training purposes. Still, the fleet market is considerably smaller than passenger vehicles.

Another worrying aspect is the high reliance on user data. The company believes its customer base, mainly composed of millennials and generation Z, is more willing to share data, and its transparency concerning data being collected and how it is used will create higher confidence. Nevertheless, according to a UBI survey conducted by Nationwide in the US, 62% of respondents have privacy concerns about the information telematics is capturing. Also, this could be a barrier if the company expands to regions with high data protection laws, such as Europe. Lastly, but most importantly, as the product is not available yet, it is hard to tell how much fairer their UBI prices will be compared to incumbent UBI players.