Many people know black box insurance as a way for insurers to offer more accurately priced premiums, based on your actual driving behaviours rather than statistics, but telematics technology can do more than that.
These systems can be used for tracking, safety and accident alert, and the data collected from these systems can help with investigations into accidents, make settling insurance claims more efficient and improve driver’s skills.
This article discusses how a black box’s accident alert system could help you.
What is a black box accident alert system?
A black box records various bits of data and information related to the vehicle and its operation. Some are fitted with accident alert systems that can notify your insurer of an accident and provide crucial information about the collision. The system captures critical data during and immediately before and after a collision, which can be valuable for accident reconstruction and settling claims.
What Does A Black Box Accident Alert System Record?
- Collision date and time
- Speed of the vehicle
- If the engine was on
- If brakes were applied
- Force of impact
- Whether seatbelts were used
- If airbags were deployed
Your insurer can then use this data to help determine the events that led up to the accident.
How Could Your Black Box Accident Alert System Help You?
Accident Alerts
A black box is programmed to detect sudden deceleration, harsh braking, or rapid speed changes that could indicate a collision. When the system detects an accident, it can automatically send an alert to your insurer outlining information about the location of the vehicle, the severity of the impact, and other relevant details.
Cause Of Accident
A car's black box can provide crucial information about an accident and the events that led up to it. This data can be used to corroborate or contradict statements made by other drivers involved, helping your insurer determine liability.
Claims Settlement
Data can be used as evidence in insurance claims settlements. It provides an objective and data-driven perspective on the accident's circumstances and a non-biased account of what happened