Automated Car Damage Detection With AI for Remote Assessment and Improved Claims Processing

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The world of insurance is highly regulated, which often leads to delays in processing an insurance claim. Talking about claims for car damages, the process is further delayed as it includes human intervention for damage inspections. With AI, car damage detection and remote assessments are automated and the manual intervention is drastically reduced.

McKinsey already estimates that AI investments in the insurance industry can lead to a potential annual value of up to $1.1 trillion.

Legacy systems and outdated technologies do not help insurance service providers automate and offer a better experience to their customers. However, modern-day technologies like Artificial Intelligence (AI) and Machine Learning (ML) are here to turn the tide.

This article looks at how you can leverage AI-based solutions such as automated car damage detection models to improve the assessment process and ensure faster disbursal of claims.

How Does a Vehicle Insurance Claim Work?

When vehicles face accidents, owners need to inform the insurance company and police immediately. It helps them in getting maximum benefits from the insurance. If the insurance providers identify that the claim is genuine, they reimburse the amount after due inspection. Here’s how the process works:

Informing the Insurance Provider

The vehicle owner needs to inform the insurance provider about the accident. The timeline for conveying the information is usually seven working days, post which the claim settlement period will likely get lapsed. The insurance claim involves adding documents like registration certificate, driving license, insurance policy, and FIR copy.

Lodging an FIR

Informing the police and filing an FIR is critical, whether it is an accident, theft, fire, or other damage. In case of minor dents or scratches, an FIR is not necessary. The police will ascertain the claims about the accident by visiting the spot. They will also record essential details related to the driver and vehicle.

Submitting the Documents to the Insurance Provider

When you get done with filing the FIR, you can proceed towards insurance claim settlement. Make sure you have a set of photographs that capture the scene of the accident. You can also snap photos of the damages from all sides. You will then have to provide all the documents and supporting proof to back your claim.

Setting Up a Manual Inspection for Damage Detection

When you file the insurance claim with your insurance provider, you can ask them to assign a surveyor for the inspection process. A representative from the insurance company will assess the damages and help you find garages for repairs. The insurance provider will tow the vehicle so that there are no further damages. You can expect the assessment process to get completed within a day or two after claim intimation.

Getting the Repairs Done

Vehicle owners can get the car repaired and begin the insurance claim settlement process, which happens in two ways. If they opt for a cashless claim, there is no need to meet the repairing cost. The insurance company recommends the network garages in such cases. Vehicle owners only need to pay for deductibles.

If they opt for a reimbursement claim, they will have to bear all the repair charges. Vehicle owners can then submit the receipts and other documents to the insurance provider. The company will reimburse the amount except deductibles.

Now, don’t you think this process is a lot and time-consuming? What if some part of this process could be automated?

The highest time-consuming activity would be the manual inspection of the damaged vehicle.

Can We Automate Vehicle Damage Detection?

The rise of AI has been phenomenal in various fields, and the BFSI sector is no different. AI systems can analyze accident images to identify repair costs on a real-time basis. Insurance companies can experience better productivity by implementing AI in insurance claims processing and managing manual time for important tasks. AI accelerates the claims process and helps insurance companies experience better productivity.

Furthermore, in situations like a pandemic where social distancing norms are necessary, surveyors can perform their duties remotely. It not only helps save costs but also leads to savings in time. Automating routine processes like manual damage inspection of cars can overcome inconsistencies that can prove to be costly errors. Document capture technologies also help in handling large volumes of documents at once.

How AI Can Help in Automated Vehicle Damage Assessment?

Gramener helped a car insurance firm automate the car damage Assessment process to accelerate insurance claim settlements. This was a classic computer vision application that helped the client detect car damages remotely and comply with social distancing norms.

The company wanted to analyze damage from multiple angles and not depend on the physical visit by an agent to save costs and time. Our Android app classifies live images from a camera.

We trained models, converted them to TensorFlow lite, and added them to the app. The classification model uses an advanced edge deployment mechanism that eliminates the need for human interference for identifying damage estimates for cars. With an inference time of two seconds, the model achieves a 97% accuracy.

Challenges to Build Automated Car Damage Detection Models

Like with creating a model for any purpose, there are challenges related to creating automated car damage detection and assessment models. Let us take a look at them in detail.

Getting Appropriate Datasets

You need to have sufficient data of images to train machine learning models. It is also better to have a varied set of photos to classify them. It might be a challenge as it is tough to find a public database with images of damaged vehicles.

Pre-Processing Images

Pre-processing helps in speeding up the process and getting better results. It includes editing images to make them usable. When done correctly, pre-processing also helps in making dark and blurred photos suitable for use. You can have a better database of images to work with.

Building Car Damage Assessment Models

Creation and training of models take time because it takes time to detect vehicles and distinguish their exteriors appropriately. You may need more input data and improved algorithms to get better accuracy. So, the process likely extends for weeks and months.

Optimizing Costs and Performance

The model needs to be reliable as insurance companies deal with hundreds and thousands of claims processing. Vehicle owners should also get damage estimation instantly. At the same time, the costs need to be controlled because the processing of images itself can cost thousands of dollars. If there are delays, it will only end up costing more time and money.

Maintaining Privacy

It is critical to maintaining the privacy of car owners during the processing of images. If photos contain license and number plates of vehicles, it is easy to identify the owners of those vehicles. It can be a violation of privacy and breach the GDPR standards.

Benefits of Automated Car Damage Detection

Here are some advantages of the automated damage detection process.

Saves Time of Inspection

Insurance companies do not have to send a surveyor to check the condition of the damaged vehicle. The AI-enabled system helps them assess the damage even remotely. When the vehicle owner sends the photos, they can run them through the system and specify the repair costs.

Saves Cost on Claims Processing

Automated claims processing helps in speeding up the process. AI-enabled tools and claim analytics help handle a large volume of requests. Besides reduced spending of resources on these tasks, insurance companies can experience better productivity.

Conclusion

Using AI in car insurance to assess damages and identify repair costs can significantly speed up the claims process. Insurance businesses can shorten the processing and reduce the steps for customers to get their payment. Besides improving the productivity of agents, insurance providers can improve customer satisfaction levels.

Gramener is already helping insurance companies worldwide leverage automation to get the best benefits of AI for improved revenue. Contact us for custom built low code data and AI solutions for your business challenges and check out computer vision solutions built for our clients, including Fortune 500 companies. Book a free demo right now.