How AI and Autonomy Will Usher in a New Age for Car Insurance

Artificial intelligence (AI) is now being applied in many systems today and with it, we have seen the rise of autonomous vehicles. Even with that, many questions arise – when an accident happens with an autonomous vehicle, who takes liability? The passengers are never in control of the vehicle and that means that the person in charge of the controls is responsible for whatever happens to the car. Therefore, it makes sense for the designer of the autonomous system to take responsibility. With high-level autonomous vehicles, traditional insurance cannot be used as cover because control is not in the hands of a human being. Even if it was to be used, it would be inaccurate and too expensive for customers seeking to enjoy the full benefits of autonomous driving.

With AI now being used to drive cars, there is definitely going to be a new path for auto insurance. All the same, the passengers inside the moving vehicle still can influence whatever happens to the vehicle especially in the event that an accident would occur. Even with a perfect system of driving, parameters such as maintenance condition or the surrounding environment can increase the chance of an accident happening. Suppose the technology used can forecast increased risk conditions based on the geography of a place, does it mean that passengers will take liability for the increased risk?

Evolution of Auto Insurance through AI

Payment of insurance premiums is based on risk and currently, it is founded upon the perceived risk of the vehicle driver. Auto insurance has now moved on the change the premiums of a car owner based on risk tolerance. Progressive Auto Insurance makes use of a snapshot that tracks habits of driving and gives premium reduction offers based on the findings. Similarly, a person found with a history of risky driving tendencies gets charged higher insurance premium because of their likelihood to cause accidents.

These two situations are all based on statistical models. How about designing algorithms to establish when and the duration for which a person gets exposed to the enlarged risk? This would permit insurance companies to provide new products that adapt to existing situations instead of being entirely based on driving behavior in the past. Suppose you don’t have snow tires on your car, the risks may increase due to bad weather. Other situations that may increase risks for autonomous driving include poor maintenance, anomalous traffic events and so on.

Data Analysis for Insurance Cost Efficiency

With the right data being continuously analyzed, all these risky situations can be predicted. Through the use of these technology advancements, it is possible to gather all this information and make predictions concerning future driving experiences. This could work to the advantage of the insurance industry in their efforts to make an insurance product that makes use of these risk predictions to establish whether passengers are ready to take this kind of exposure to these risks.

In an event where an autonomous vehicle finds out that the current route will experience a high-risk setting, passengers on board can get three options: consider using a different route regardless of how long it will be; hold the journey until all risks are cleared or the passengers choose to pay a certain amount of premium to continue the trip with the increased risks. Ideally, auto insurance premium, in this case, will be built upon the pre-trip fare quote in a similar manner that is comparable to surge pricing. In that case, machine learning will make it possible for insurance companies to change how products are created for autonomous vehicles hence lowering the insurance costs for the day-to-day use of a vehicle. Then, it would be correct to say that vehicle technology decreases insurance rates.

Final Thoughts

Machine learning and AI development are certainly among the major technological breakthroughs of this age. It involves the use of computers to monitor sophisticated information and provide it in ways that can be analyzed and used to make processes and systems efficient. Computers use the information to get its programmed goals. This implies a great step towards making savings and bringing a lot of convenience for consumers. It also translates to reduced costs and increased profits for those in the car insurance industry.

With the enhanced capabilities of computers in handling information a lot quicker than can a person do, a lot can be achieved especially in the vehicle insurance industry. The efficiency of auto insurance company is definitely going to increase the more with continued application of AI in the automotive industry.