Industry

Competitive Pricing and Big Data Underwriting: How Insurtech Has Changed Insurers’ “Core Competencies”

“More granular data, allied with advanced analytics, enables better risk selection and improved profitability,” the report says.
By Rob Boyce Posted on May 30, 2019

The report, released earlier this month, delves into how the widespread implementation of insurtech solutions has given rise to fierce competition over pricing among insurers as well as to the increased leveraging of untapped data sources—artificial intelligence (AI), machine learning and the Internet of Things (IoT)—to inform and further refine the underwriting process.

“More granular data, allied with advanced analytics, enables better risk selection and improved profitability,” the report says, and “promises benefits through customer self-monitoring and feedback, enabling customers to control their own levels of risk.”

A general example of this is “motor telematics policies,” which as the name suggests, involves the insurer monitoring a policyholder’s telematics data and adjusting their premium based on the robustness of their risk-control efforts. For some already low-risk insureds, the prospect of being continually monitored outweighs what little price benefit they would glean from that type of policy; for others, it represents an opportunity to mitigate rising premium costs by adopting practices that minimize risk. Whatever the case, having this option thanks to the leveraging of previously underutilized data sources represents a net benefit for the industry.

All of the companies highlighted in the body of the report—ConcirrusRoot and HazardHub—embody the desire to make better use of data or to assist insurers in realizing that goal. As a “case study,” let’s take a look at how Concirrus approaches using data to inform the underwriting process.

Concirrus, founded in 2012, manages an insurance data platform, Quest, which utilizes AI and machine learning to process vast quantities of risk-related data to provide (re)insurers with actionable insights. For example, Quest Marine “analyz[es] static demographic vessel statistics (including, but not limited to, class, flag, year of build, shipyard and tonnage) and combin[es] it with historic, real-time and predictive behavioral data (such as mileage, days at sea, areas of operation, average speed and more) to determine the correlations and risk indicators associated with a fleet.”

More concretely, “the platform can determine if a vessel enters a war or ice zone and, when it does, can trigger the appropriate policies that reflect the time spent in the zone,” thus giving (re)insurers the ability to provide flexible and comprehensive coverage. The company has partnered with several larger (re)insurers and brokers, including Willis Re, and has extended Quest to also work with commercial auto risk data.

Apart from the report’s timely theme regarding how insurtech is changing pricing and underwriting, here are a few key statistics from the report:

  • 85 insurtech investment deals with a total value of $1.42 billion were announced in Q1 2019, marking the highest ever number of deals for a quarter.
  • Of those 85 deals, 56 were P/C transactions, the highest number of P/C transactions since WTW/CB Insights began publishing this report. Additionally, since Q2 2017, P/C insurtechs have consistently received more early-stage funding (seed/Series A) than Life and Health.
  • Q1 2019 recorded a record high of 10 deals over $40 million, a 67% increase from Q4 2018.
Rob Boyce Director, Market Intelligence & Insights Read More

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