In this interview, Hari Balakrishnan, Founder & Chief Technology Officer of Cambridge Mobile Telematics, shares his insights on how the smartphone is one of the key components in distracted driving and how the same tool can actually be used to improve driving quality. Cambridge Mobile Telematics is a global company working with 35 organizations from over 20 different countries to accurately measure driving quality, deploy behavioral incentives to improve driving, and use AI to automate the claims process.
Keep reading to learn how Hari and CMT are investing in the future of better driving by expanding their global platform, developing new video analytics software, and improving driving safety in a world where self-driving cars are a soon-to-be reality.
What problem did you set out to solve when founding CMT?
In 2010, the concept of using a smartphone to collect fine-grained data to draw accurate inferences about vehicle dynamics or give direct feedback to drivers was unknown. Any attempts at that time to use smartphones to better understand user behavior were seen as inaccurate and generally unreliable, especially in the field of telematics.
When we started Cambridge Mobile Telematics (CMT), however, we were betting that the smartphone would be a critical, central component to the field in the future; more so, that although the smartphone would be the very device responsible for distracting drivers on the road, it could also help make them less distracted and become better drivers.
We also realized that many people do not recognize the dangers of driving while distracted. We were seeking approaches for what we viewed as preventable incidents. Our goal was to accurately measure driving quality and to create better drivers, making the roads safer for all.
Over the last nine years, CMT’s DriveWell platform has helped make roads safer by making drivers better in a world where crashes are rising because of factors like distracted driving. CMT’s rapid growth is fueled by a company culture that is deeply customer-committed, values collaboration, and values creativity via investment in research to improve current solutions and develop new ones.
CMT’s DriveWell platform provides insights on drivers and vehicle dynamics to insurers. What type of insights do you provide?
Many of the largest insurers in the world have adopted CMT’s DriveWell platform – a complete telematics and behavioral analytics solution for the connected car world that (1) accurately measures driving quality using mobile sensor data, (2) deploys a range of behavioral incentives to improve driving by reducing risk factors such as phone distraction and risky speeding, and (3) uses artificial intelligence on telematics data to automatically automate several aspects of claims management.
Using machine learning and signal processing, DriveWell accurately infers key metrics about mileage, speed, acceleration, driving style, distraction, and collisions. DriveWell understands a driver’s behavior over time, providing positive reinforcement for safe driving behavior: incentives such as gift cards and reduced insurance rates based on good driving influence behaviors. Meanwhile, our AI methods operating on sensor data can step in to save lives in the event of a crash.
Following a crash, it takes a lot of time and money for insurers and drivers to process a claim. CMT’s crash reconstruction technology applies AI techniques to telematics and contextual data, providing insights and decision-support capabilities to reduce the effort and cost. As a first step, crash reconstruction provides a comprehensive picture of the event, using processed telematics data, calculated crash indicators, and contextual information. Insurers can receive this information visually in the DriveWell portal or via an API. With this service, insurers can see machine-generated crash descriptions and details like severity rating, number of impacts, duration of impact, probability of vehicle hit location, weather and more.
As a result, insurers and agents are able to begin the claims process earlier and reduce manual efforts to document and analyze crash details.