Risk management is critical for anyone involved in the operation, management, or insurance of fleet vehicles. Primarily, it helps to reduce crashes, injuries, and damage. It also brings additional benefits to organizations, including increased efficiency, competitiveness, and profitability. Now, artificial intelligence (AI) is proving a game-changer in the management of driving risk by predicting crashes before they happen. But, for some, two key questions remain. AI in risk management: how and why?
You don’t have to look far to find an article about AI. Whether it’s about AI being used to write articles, to match medicines to patients or to develop new music, news about AI are everywhere. Now, AI is transforming the face of risk management within fleets and motor insurance.
AI in risk management is capable of doing something that humans haven’t yet been able to do. And that’s to predict crashes before they happen. It can even predict climate impact, helping fleets, motor insurers, and anyone involved in mobility make sustainability an integral part of their risk management solution.
Think about facial recognition and how it compares faces to a database of known faces. AI in risk management works a little like this. At Greater Than, our AI pattern profiling analyzes GPS data to identify patterns in driving because of driver attitude and decisions made. By measuring and analyzing every second of driving, we can create a unique DriverDNA for every trip.
We compare this DriverDNA against our database of over 7 billion driving patterns, trained with damage data, saved CO2 emissions and fuel consumption from real trips. We’ve been training the AI since 2004, using data from over 106 countries and 1,600 cities. This extensive knowledge enables us to rapidly predict crash probability and climate impact and makes AI in risk management extremely powerful.
By simply analyzing GPS data, AI can predict the likelihood of future crashes. To put this into perspective, our AI can identify the 15% of drivers responsible for 50% of crashes before they happen. It can also identify the reason those drivers are likely to be involved in crashes. Using AI in risk management therefore gives risk managers a privileged view into the future. And it can be used for good at a driver, company, and society level.
Armed with new intelligence about crash probability, risk managers can prioritize high-risk drivers for training to prevent the predicted crashes from happening. They can also recognize the achievements of low-risk drivers. The associated benefits are huge, including fewer crashes and injuries, less damage, reduced costs. And optimized driver well-being, engagement, and efficiency.
As well as predicting crashes before they happen, AI can predict climate impact. At Greater Than, our AI enables organizations to quantify, mitigate, and report on their drivers’ climate impact. It also makes it easy for mobility companies to develop products that encourage drivers to be more aware of, and to reduce, their own environmental impact. Our partnership with Stellantis Japan is a recent example.
Some of our clients incorporate the AI into their own driver risk management solutions, to elevate sustainability and ESG. eDriving is a great example of this. And, because the average CO2 saving for a committed driver using a product with our AI is 20%, it’s easy to see how quickly sustainability efforts can be realized.
GPS data is all that’s needed to get started with Greater Than’s AI – and this can be obtained via a simple API connection. No in-vehicle hardware is required, nor is any additional technology. The data can be transferred via dashcam, connected car, telematics device, or any other system. We can even collect data from multiple telematics providers and convert it into one comparable, harmonized score.
Our driver scores – Crash Probability Score or Climate Impact Score – can be pushed to a company’s existing fleet management system, a driver app, SDK or visualized via one of Greater Than’s add-on solutions.