Consumers Don’t Trust Their Auto Insurers. AI Can Help Fix That

If trust is an essential element in the relationship between consumers and insurance companies, 2024 was an especially bad year for car insurers. According to consumer intelligence firm J.D. Power, trust in insurers fell “dramatically” last year – largely because of a nearly 20% increase in the cost of auto insurance premiums nationwide over 2023, perceived by many clients to be an arbitrary price hike. 

But there is one bright spot for insurers: artificial intelligence. As auto insurers increasingly utilize AI for all aspects of their business – especially claims – they have an opportunity to win back the trust of clients who have lost faith in their business model in recent years. Data shows that a large majority of consumers increasingly trust AI, as long as businesses use it transparently and ethically. And when it comes to insurance claims, AI has great potential to add transparency and efficiency to the claims process, essentially turning clients into partners in the process. AI can help accomplish that in the initial reporting of an incident, the evaluation of damage, and in the the final decision on a claim.

A Growing Role for Consumers in Initial Reporting

In the smartphone era, the first thing many drivers involved in an accident are likely to do is whip out their devices and take photos of the scene. This can actually work to the benefit of both customers and insurers when a dedicated damage-scanning app is used, with an AI assistant guiding drivers on which images to record. This puts power in the hands of the consumers, while ensuring that insurers receive the images they need, including those of the vehicles involved, the surrounding area, weather conditions and other details central to the claim. 

When they provide the images themselves, the customer is more confident that their point of view was recorded, an important element in building and maintaining trust and satisfaction. In many cases when such apps are used, companies will not have to send out an adjuster to examine the scene – a plus for companies, obviously, but also another confidence-builder for clients, who know that their claim will be based on the images they sent, and not on the images taken by an adjuster. In other cases, adjusters, too, can use similar mobile apps to record damages, and these images can also be shared with consumers, creating another route of transparency.

In addition, the use of AI-enabled apps, whether by adjusters or consumers, to record damage brings objectivity, accuracy and efficiency to the process. These apps ensure that images from every part of the car are recorded, not just those areas that appear damaged to the human eye. Such apps can also ensure that each video or photograph is of a certain quality, or direct the user to redo it. This adds to the accuracy and efficiency of recording any damage, making clients feel more confident and ultimately less likely to file time-consuming appeals.    

‍More Objective Analysis and Evaluation 

After capturing images of damage, such apps can then use AI to determine what exactly was damaged, and how much that damage will cost to repair. Using an extensive “damage database” (such as the one we have here at Ravin) insurers can quickly compare their customers’ images of damage to millions of other images of similar vehicles that were in accidents, labeled with data on what parts needed to be repaired or replaced. This can quickly enable insurance companies to determine in an objective manner, how much compensation is due. 

Such systems can also provide reports for customers, detailing the damage, and – based on the comparison to other similar damage in the database – specifying which parts likely need to be repaired or replaced along with the compensation due to cover those costs. This is another way that AI can help improve transparency and clarity with customers, help build trust and guard against errors human adjusters and claims’ processors can make.  

Besides making the process easier and more efficient for clients, such AI-enabled inspection systems can help insurers avoid falling victim to fraud. Insurers can compare images of damage taken after an accident or incident with baseline records for the vehicle, determining if any reported damage was pre-existing or indeed happened during the latest event. The system can also help shed more light on how an accident took place by analyzing the angle of the collision, and other data – all factors in determining whether the claim is legitimate.  

‍Less Friction in Claim Decisions 

With much of the AI-powered examination, investigation, and evaluation process open and transparent, clients are much more likely to accept the insurer’s decision on compensation. This will likely lead to fewer appeals. Moreover, as clients feel more like partners throughout the claims process, they are more likely to stay on as customers. 

Customers are also likely to be very happy with the speed of the AI-assisted claims process. AI systems can come to a very quick decision about how much a client will get in a settlement – often in just a matter of minutes, without the need to send out adjusters to the scene, and undertake the manual research and decision-making that was previously required. Studies show that a speedy claims process, and especially a speedy claims decision, is one of the most important factors in customer satisfaction for insurers.  

Experts agree: For insurance companies, increased transparency leads to greater trust, which results in better growth, as well as increased retention rates. AI provides insurers with an opportunity to improve this trust. When clients see that their insurance companies are striving for transparency and fairness, they will begin to trust them again – and that’s good for everyone.