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Usage-Based Auto Insurance

What Is Usage-Based Auto Insurance?

Usage-based insurance refers to the collection of driver behavior and environmental data to underwrite car insurance plans. It is also called Pay-As-You-Drive or Pay-How-You-Drive insurance.

Why Is It Important to Have a Good Usage-Based Insurance Model?

Real-time data forms a more accurate basis for calculating insurance premiums than demographics. Of course, this helps insurance companies create better policies, but it also attracts customers who want policies that reflect their personal driving behavior rather than their demographic statuses.

Moreover, usage-based insurance can help locate stolen vehicles and determine fault in accidents, thereby reducing rates of insurance fraud. Companies can also help drivers improve their driving with analysis and real-time safer driving prompts.

What Internal Data Should I Have for a Good Usage-Based Insurance Model?

There are two main types of internal data for usage-based insurance models. The first is your company’s insurance policies, discount or loyalty programs, and the cars driven by your clients.

The second and most numerous type is driver behavior data. This refers to the driver’s steering, signaling, and braking patterns as well as distance travelled, amount of time spent driving, and the times of day the car was in use.

What External Data Is Essential for a Good Program?

Industry standards and news inform any usage-based insurance program. Other essential data includes the car’s location (some areas have poorer infrastructure) and environmental conditions at the time of use.

What External Data May Prove Useful for a Good Program?

Additional external data may include scheduled maintenance, remote diagnostics, traffic patterns, and infrastructure updates.

What Are the Main Challenges of this Use Case?

The challenges to employing a user-based insurance program are sourcing and cleansing the data. In the first case, different states have different data collection regulations, making generalize policies difficult in large enough enterprises. Additionally, some drivers don’t consent to data collection of their behavior.

Secondly, collecting and cleansing data in real-time from multiple sources is extremely difficult.

Interesting Case Studies and Blogs to Look Into

Otonomo: Automotive Data for the Insurance Industry
IMS: The Future Trends of Usage Based Insurance and Telematics

Tangible Examples of Impact

“Volvo has a subscription service that includes insurance,” Kerr observed. “Tesla is offering, in California, built-in insurance connected with their cars. There is a lot of common sense for the carmakers themselves to offer convenience services — whether it be financing, insurance services and so on — that would make it a more attractive, holistic offer for one-stop shopping for their clients.”

Canadian Underwriter: The next revolution in telematics: An insurer partners with an automaker to collect data

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