Improve motor insurance loss ratio with predictive risk insights
With the industry struggling against persistently high loss ratios, insurance companies are seeking new innovative digital solutions that will drive profitability and competitiveness. As one of the top industry tech trends, artificial intelligence (AI) is fast becoming the technology of choice for motor insurers, thanks to its capabilities of uncovering new predictive risk insights that can dramatically improve loss ratio.
Why are motor insurance loss ratios so high?
The motor insurance industry has been under intense pressure for some time. After a short pause during COVID, results continue to deteriorate due to a number of factors.
A report published in October 2022 by the American Property and Casualty Insurance Association highlighted that motor insurers were struggling to keep up with the highest inflation in 40 years. The report also pointed to other reasons for high insurance loss ratios, including an increase in:
- Private passenger vehicle losses
- Average cost per collision claim for private passenger vehicles – a record high in the first quarter of 2022
- Cost of medical care
- Lawsuits and high jury awards or settlements, due to a combination of adversarial legal procedures and a litigious culture
- Riskier driving behavior
The impact of driving behavior on loss ratio
Driving behavior plays an important role in motor insurance loss ratio. Why? Because risky behaviors, including vehicle control, distraction, and impaired driving, are linked directly to crash probability – and severity. Insurance carriers that have been successful at containing runaway loss ratios have harnessed the power of understanding real-time driver behavior data and layered it into their product offerings.
Today, many insurance experts talk about “predict and prevent”. While predicting can help with more accurate pricing, prevention is not necessarily built into insurers’ DNA. However, it should go without saying that influencing safer driving behavior helps to reduce crashes and, ultimately, loss ratio. It also makes sense that rewarding drivers with the lowest crash risk has a measurable impact on retention rates.
Utilizing AI to identify and segmentize driving risk
AI is a powerful new tool in accurate pricing and risk segmentation for motor insurers. Not only that, but it can help with risk mitigation efforts. It can also have a powerful effect on loss ratio without sacrificing the expense line. At Greater Than, our AI gives motor insurers a whole new perspective on driving risk. Here’s how it’s different:
- It is not a “proxy”, meaning we don’t try to make assumptions based on limited data
- It isn’t based on driver “events” alone
- It doesn’t allow for variable risk thresholds and doesn’t vary between vehicle types or fuel types
Instead, our AI:
- Analyzes GPS data to establish a unique DriverDNA for each trip, and compares this against a database of over 7 billon driving patterns, trained with data from over 106 countries and 1,600 cities since 2004
- Calculates crash risk using per-second driving data, including longitude, latitude, altitude, speed, heading and time
- Is similar to facial recognition. But instead of comparing data to a database of known faces, it compares billions of data sets during each trip to a database of known vehicle trips, and their outcomes
- Measures crash probability AND climate impact
Why innovation matters in risk understanding and segmentation
Traditional event-based telematics roughly analyzes 5% of every hour, maybe 150 data sets. The AI we are using measures approximately 3.6 billion data sets per hour. While telematics can provide useful snapshots of a trip, AI provides an accurate analysis of the whole trip. AI provides such a granular analysis that it can identify micro-movements that point to risky behaviors and which normally might not be detected. These include lack of focus, distraction, poor vehicle control, and poor planning ahead.
The result is a much deeper understanding of driving attitude and an accurate prediction of crash risk and climate impact. And, crucially, it can be layered onto existing telematics solutions for companies that want the best of both worlds.
What this means for motor insurance loss ratio
With Greater Than’s AI, motor insurers can see into the future. That is, they can quickly identify the 15% of drivers who will cause 50% of crashes, and the 85% lowest-risk drivers, giving them much greater control over loss ratio. The result is a better understanding of risk for renewal, quotation, and ongoing pricing.
With these new insights, motor insurers can finetune their existing pricing models, or create entirely new risk sensitive products. In the case of the latter, they can also help to incentivize safer, eco-friendly driving. Not only does this help to improve loss ratios, but it positively contributes to important road safety and sustainability goals.
Accessing new AI-driven risk insights for loss ratio is easy
At Greater Than, all we need to uncover new predictive driving risk insights is GPS data. In most cases we access this via an API (dashcam, connected vehicle, telematics device etc), enabling us to convert driving data into a real-time crash probability and climate impact score for every driver.
And, because the data is harmonized by us, we can convert data from multiple telematics providers into comparable scores, making it easy to compare risk level and identify drivers for risk mitigation. We can even integrate our AI into existing insurance solutions so that motor insurance providers can improve loss ratio whilst adding extra value for their fleet customers.
To find out more about using Greater Than’s AI to access predictive risk insights and reduce loss ratio, please contact us or book a meeting.
