Until recently, the automotive insurance industry used archaic methods to assess driver risk. Driver premiums were based on factors such as geography, age of the driver, whether or not the driver had been in an accident before and the type of car they drive. However, these factors are not good indicators of risk and heavily depend on an event taking place such as an accident. Any accident, leads to a huge cost and payout for an insurance company. The question the industry started to ask was, is there a way to predict risk before the fact and prevent accidents from happening at all?
This led to the advent of Usage Based Insurance. The premise is simple, using sensors to detect driving patterns which indicate risky behavior before a costly event takes place. This helped insurance providers identify risky drivers and charge more accurately based on driver’s risk profiles. The same technology can be used to provide feedback to driver, helping them improve their driving habits, in effect reducing the risk of an accident.
Arity recently spun out of Allstate, bringing machine learning and predictive analytics to better predict risk and help drivers understand their driving behavior. The solution initially started with the use of a OBDII based dongle, which once inserted into a car’s diagnostic port, would capture driving information from the vehicle (speed, diagnostics, accelerometer, GPS). Using proprietary models and machine learning, the data from the OBDII device is used to give each driver a risk score. This score determines the drivers likelihood to get into an accident and finally their viability as a customer. In most cases, the insurance company elect to not insure a high risk driver and most good drivers would actually see their premiums decrease.
While the solution using a dongle worked well, it was not cost effective and neither could it be used to gather information about the driver’s behavior. The next stage of this technology has moved to using the driver’s mobile device as a sensor. A driver’s mobile device being used to collect information such as
- travel speed,
- cornering speeds,
- time of day,
- Usage of the phone (connected over a Bluetooth device, or was the phone physically in the drivers hand)
All of this information is processed through proprietary models and compared to risk data. Arity has access to 21 billion miles and over 85 years of Allstate’s insurance underwriting data which is the baseline to creating accurate risk models. This allows Arity to create a driver risk profile and also provide feedback to the driver directly through the app on their mobile device.
Effectiveness and Commercial Promise
According to the National Safety Council, cell phone use while driving leads to 1.6 million crashes each year. 1 out of every 4 car accidents in the United States is caused by texting and driving. The estimated economic cost and comprehensive cost caused by phone usage while driving are $61.5 and $209 billion. Arity’s solution monitors a driver’s interaction with a mobile device along with driving behavior, which would deter or notify the consumer when they are distracted.
Insurance companies can leverage this technology to identify risky drivers and help them improve their driving habits. For example, Allstate’s Drivewise application allows policyholders to save up to 3% of their insurance cost when using the app to manage their insurance. After the first 50 trips, the auto insurance holders may earn up to 15% cash back based on their driving behaviors and risk profile. Arity’s solution is particularly important to the highest risk group: teenage and student drivers and can help them be safer on the road.
Ride sharing and commercial fleet customers –Taxi, Bus, Uber and Lyft are also looking for was to better track the performance of their employees and drivers. These companies would be able to manage risk better through the platform. They can qualify drivers based on driving behaviors and retain the safe drivers. High risk drivers also negatively hurt the riding experience of customers and ultimately hurt their brands. By using Arity’s platform, the companies can weed out high risk drivers and thereby lowering their auto insurance cost.
Today the algorithms do not take into account external factors. Our recommendation is to include:
- weather information,
- Location – proximity of known bars or high risk areas
- Improve data from mobile phones as the data is not very clean
- Make use of wearables as additional sensors which can provide insights into driver health information
- Lastly, partner with OEMs to get access to connected car data which is much more reliable than the data from mobile devices for tracking vehicle movement
Given multiple potential applications there is a space in the industry for many companies to operate successfully. Arity is positioned to outperform its competitors today due to the amount of data they can collect through Allstate’s large and diverse customer base. Arity is also making its platform available to other smaller insurance companies and fleet operators which will enable Arity to collect larger amounts of data which in turn will help improve the risk models.
- Primarily partners with government
- A global firm without strong data and market penetration in US
- Primary works with StateFarm insurance
- The data used for modelling is not as diverse as Arity
- Primarily targets the B2C segment but monetizes through B2B
- No current partnership with insurance company
Team – March and the Machines
Ewelina Thompson, Akkaravuth Kopsombut, Andrew Kerosky, Ashwin Avasarala, Dhruv Chadha, Keenan Johnston