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How AI can improve Damage Detection in the automotive industry?

Updated: Apr 22


The current situation of the car insurance industry has a huge waste on claims’ leakage.


Claim leakage is the overpay in claim payment due to visual inspection. According to a recent research, claims processing in 2030 remains a primary function of insurance carriers but head count associated with manual claims is reduced by 70-90% compared with 2018 levels. Therefore, the urgency for claim automation is rising in all aspects of insurance.


The recent application of image recognition appears as a disruptive solution in the traditional claim process, which is highly competitive on intelligent data extraction, personalization and fraud detection as the latest trends.



Auto insurance is becoming a lot easier and quicker – with the help of Artificial Intelligence and smartphones.


The United States is one of the world’s largest and fastest-growing auto insurance markets – but until now, the sector has had to rely on traditional ways to renew lapsed policies or make repair claims. Both services have required inspectors to physically look over vehicles and make damage assessments.


In a crowded country like ours, scheduling inspections and getting approvals can keep cars and policyholders off the road for days. A more convenient way was needed. Here is how AI for Damage Detection comes in.


Artificial intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. The main aim of image acquisition is to transform the data from the real world or optical images into the array of numerical data to be manipulated by a "super" computer before processing.




To obtain the estimate of repair costs, the images of the car damage are used, appropriately normalised and aggregated using data mining and NLP (natural language processing) algorithms. A statistical evaluation is subsequently made in relation of the historical costs for repairing similar damage on the same car model. The estimates are then cross-referenced with the results of the damage recognition from photos, relying on a dedicated optimisation algorithm, in order to obtain an overall estimate of the accident repair costs.


How does the application work?


We detect and classify multiple types of damage including dents, scratches, wheels and trim. The inspection algorithms for vehicle inspection are both intelligent and reliable.


The AI algorithm was fed by thousands of damaged vehicle images and their respective estimations and now it is able to detect damage by uploading 8 images of the eight corners of the car by a mobile app taken by the end user (driver)


Nsemble.ai will bring uniformity in the industry instead of having human variation of estimations.




What does damage inspection flow look like?


1-The client uploads clear images of the insured vehicle to the insurance claim processing platform.


2-The platform automatically verifies that images have sufficient quality for running the inspection


3-Notifying the client if the images need to be reuploaded.


4-Run models for vehicle damage inspection that give boxes around damaged areas, detect what part of the vehicle is damaged and what kind of damage it might be like rust, dents, scratches, etc.



What are the benefits of using AI for Damage detection?


- Saves time, effort and money for all parties involved i.e the insurance company, the repair shop, the owner etc.


- Its safe because it allows the appraisals to do their jobs remotely (Covid precautions)


With the whole world undergoing a pandemic, many people are looking to protect themselves by staying at home. AI damage detection allows you to fix your issues without leaving your house.


- Saves time, effort and money for all parties involved i.e the insurance company, the repair shop, the owner etc.

For Insurance companies:


Prevents from fraud (by using pre-inspection), speeds up in times the underwriting process. The solution benefits insurers by transforming the claim value chain. It can speed up time-consuming claim settlements and creates a better customer experience, while increasing efficiency. The possibility to add fraud detection to the model would allow additional checks and verification of the image uploaded with the claim declaration and the repair quotes collected. Furthermore, our AI engine evaluates car damage and estimates the associated repair costs within a few seconds when connected to a repair cost database.The advantages to the customer are clear. They can file claims whenever and wherever is convenient and will receive estimates much faster than before.


Other companies:


Car rental services

Decreases operational costs, brings customers’ satisfaction and higher retention rate.


Car repair services:


Creates a collaborative environment, brings transparency to the repair process and costs.

Easy to use:





LEVERAGE MACHINE LEARNING


Accessible through an intuitive app and platform, N-semble leverages next-generation computer vision and machine learning technology to prevent wasted time and spending while eliminating costly manual assessment errors.





AUTOMATE REPETITIVE WORK


Throughout the insurance industry, the appraisal process is inconsistent and prone to human error. N-semble increases the accuracy of appraisals, saving time, money, and resources for insurance companies.









AVOID ERRORS


By using a manual appraisal process, insurance providers delay the settlement timeline and incur unnecessary expenses every step of the way. N-semble accelerates the entire process while lowering overall| costs.





The future of claims management


Computer vision and, in particular, image classification are fields of study where major breakthroughs were achieved in the last few years. AI damage detection is the breakthrough of the industry. Damage detection represents a revolution in claims management: it speeds up claims processing, reduces the risk of fraud and shortens the time between damage notification and settlement. Above all, it enables insurers to radically improve the customer experience.


Damage detection can radically improve the experience of customers. It just takes a few photos and 20 seconds to receive a detailed assessment of both visible and non-visible vehicle damage.


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