Auto Insurance
8 Essential Tips to Improve Reporting During Automated Vehicle Inspections

Vehicle inspections are a crucial process for various industries such as motor insurance, fleet management, car leasing/rental, and more.
Thanks to advancements in AI and technology, this process which has traditionally been manually-driven, can be easily automated.
While AI-based vehicle inspection tech can improve the process by overcoming a lot of challenges involved in manual inspections, the quality of the reports is highly dependent on the quality of images/videos being captured during the inspection process.
In this blog, we will talk about 8 essential tips of capturing high-quality images/videos to improve reporting during automated vehicle inspections. Let’s dive in!
Why does image quality matter during automated vehicle inspections?
Capturing high-quality images is very important for an AI model to accurately detect damage on a vehicle during the inspection process. Ensuring that every detail is captured will also result in better quality reports without any false positives/negatives.
If the image is low-quality or captures unwanted information, it could trick the AI model into thinking damage exists when it doesn’t in certain scenarios. Additionally, it will also increase your overall effort since it’ll require you to run the inspection all over again.
To avoid these cases, here are 8 essential tips you can follow to ensure that you capture high-quality images/videos during the inspection process.
1. Make sure that you have enough space to maneuver while documenting the vehicle
Capturing your vehicle from every angle is crucial to ensure there are no blind spots during the inspection process. Tight spaces can be a limiting factor in such situations and hence, it is advisable to move your vehicle to a more open surrounding with more space to move around the vehicle.
2. Make sure the surrounding is properly lit
While choosing a spot for your vehicle, you should also ensure that your surroundings are properly lit.
Capturing images in low-light conditions makes it tricky for the AI model to detect damage, and might result in some damages going unnoticed.
Ensuring good lighting while capturing the vehicle will guarantee a better report as the AI model will be able to capture and report more details that are clearly visible on the vehicle.
3. Make sure to account for micro damages
Micro damages are tiny scratches, dents, and scuffs that are normally not visible (even to the human eye). Identifying these damages is even more challenging using images due to their size.
However, capturing these micro damages is still crucial for generating a fool-proof report. The best way to do so is to either move closer to the damage or use the zoom feature on your camera while capturing these damages.
Capturing these damages clearly will ensure that the same gets reported by the AI model during the inspection process.
4. Avoid Strong Reflections
Vehicles inherently come with a highly reflective surface and can result in false positives/negatives if not accounted for.
For example, the image might capture a reflection of a pole on the car’s surface, and this might trick the AI model into recording that reflection as a damage on the vehicle.
Or it could also happen that the reflection covers a scratch/dent on the vehicle and hence, it goes unnoticed by the AI model.
To avoid such cases, it is necessary to ensure that there are no reflections visible on the vehicle while capturing images/videos during the inspection process.
5. Avoid Shadows
Just like reflections, shadows can also confuse the AI model into reporting false positives/negatives during the inspeciton process.
While most of this problem can be avoided by using proper lighting, there can be cases where the shadows affect the quality of the images and hence the AI model is unable to properly detect the damage on the vehicle.
6. Capture necessary vehicle details
License plate, odometer, VIN number, chassis, and other relevant documents are an important part of the car inspection process. This info helps identify details such as the make, model, and ownership of the vehicle.
The make and model of the vehicle is important to generate repair estimates for the vehicle, while the ownership details are needed as a part of the verification prodess during an insurance claim.
Capturing these details is standard procedure during the vehicle inspection process and missing out on these details will result in an incomplete report.
7. Avoid abrupt interruptions
A common strategy for fraud is to swap the vehicle in sight using different camera tricks, including removing the vehicle from the frame for a brief moment.
These cases are often flagged by the AI model during the inspection process as a case of potential fraud and hence, it is recommended to avoid any interruptions/abrupt movements while recording the vehicle to add credibility to the video/images captured.
Additionally, you should also ensure that the car is visible in every frame while capturing images/videos to ensure that the AI model doesn’t confuse it to be an attempt of fraud/tampering.
8. Always keep the vehicle in focus
Using images/videos where the vehicle is out of focus can be problematic for the AI model.
Blurry images/videos create an additional challenge for the AI model to properly assess the damages on the vehicle and hence, it may end up generating incorrect reports.
How are companies solving this problem?
While today’s AI models are not 100% accurate when it comes to damage detection, there are still some measures being taken to overcome these challenges and enable the AI model to generate a more reliable report during the inspection process.
For instance, Inspektlabs’ damage inspection app comes pre-built with these guiding principles that is used to direct users into properly recording these images and videos. The user receives real-time feedback on the image/video quality with nudges to improve so that they can immediately make corrections and capture the necessary information with absolute precision.
While these guidelines can understandably be a little intimidating for users, following them will ensure that the entire inspection process is completed in less than five minutes and you’ll have a detailed report in your hands within seconds.