AI for proactive risk management in fleet insurance
Data is already recognized as the most valuable asset in auto insurance. For an industry based on risk prediction, it’s essential for auto insurance companies to have both volume and quantity. But data is typically gathered during the course of a policy, and therefore takes time to prove its value. Now, the potential of AI for proactive risk management is shaking the industry, revolutionizing the way that commercial fleet insurers measure, manage and mitigate risk with greater control than ever before.
Recognizing the capabilities of AI for proactive risk management
Artificial intelligence (AI) is such a powerful tool in commercial fleet motor insurance because it provides insurers with previously unseen intelligence. Instead of estimating driver risk levels based on a careful analysis of past events, AI analyzes risk in real-time to predict future outcomes.
Some of the key benefits include:
- Proactive risk selection
- Policy validation
- Risk mitigation
- Transparent risk communication
- Loss control
Utilizing AI for smarter customer acquisition decisions
For insurers, one of the major advantages of AI analysis is seeing a concrete overview of what their future claims costs will look like, before their customer has actually made a claim. This provides a 12- to 18-month lead compared with other risk calculation models.
In other words, using AI eliminates the need for guesswork. Or the analysis of lagging indicators or other historical data. Because AI analyzes data in real-time, it can provide crash probability instantly, streamlining and optimizing the current process of risk identification and facilitating fast, informed, decision-making.
Realizing the competitive advantage of understanding risk
Traditionally, understanding risk can be a slow, time-consuming exercise. And risk can change. Assuming a fleet’s risk level based on its past performance can be a risky approach. Drivers can change – as can their personal circumstances. Schedules can change. Management can change. Any change can have a significant impact on risk level.
Analyzing risk in real-time brings a new dimension to understanding risk. AI algorithms can assess risk in ways that humans can’t and according to criteria that humans aren’t even aware of. By predicting crash probability for a group of drivers, AI provides insurers with a glimpse into the future that provides a huge competitive advantage.
Leveraging AI for proactive risk management with customers
For insurers, AI takes driver risk analysis to a whole new level. It examines all the circumstances surrounding a given situation, gleaning a complete view of driver risk in real time.
This insight is instrumental in helping insurance companies to reap the benefits of AI for proactive risk management. It empowers them to hold valuable open conversations with customers about how to manage and mitigate risk. Because it’s based on current driving performance it can identify changes to risk level promptly, ensuring fleet customers can take action to predict and prevent crashes from happening.
AI to facilitate accurate insurance pricing
Data-driven insights delivered via AI can be used to optimize current pricing models or create entirely new usage-based models. At the commercial fleet level this means that premiums can be priced according to the actual risk that the fleet poses, as a result of crash probability.
AI enables motor insurers to offer data-driven insurance solutions that are attractive to the modern fleet. Usage-based models are particularly relevant for customers who are transitioning towards an EV fleet or mobility-as-a-service.
Sustainability and ESG benefits of using AI for proactive risk management
Environmental, Social and Governance (ESG) is a hot topic, and it’s something all insurance companies will need to pay more attention to as additional legislation is introduced. See our eGuide for more information on ESG legislation. Not only will insurance companies need to think about their environmental impact, but how they contribute to global sustainability goals – including the support they provide to customers.
By utilizing AI, insurance companies can offer solutions to customers that help them measure and reduce emissions, and adhere to ESG reporting requirements.
How AI for proactive risk management works
Greater Than uses AI to convert existing GPS data (easily shared via an API – dashcam, connected vehicle, telematics device etc.) into crash probability and climate impact insights. The data is harmonized regardless of vehicle type, size, location, and fuel type. This means that, even if fleet customers use different telematics solutions, the crash probability and climate impact is comparable.
Getting started is simple – and all we require is 1km of GPS driving data to get started. To learn more about using AI for proactive risk management, contact Greater Than or book a meeting.
