30 seconds for claim submission. Machine learning allows for recognizing damaged vehicle parts, accessing damage, making predictions about what kind of repair is needed, and estimating how much it may cost.
Car damage recognition solution
The Car Damage Recognition system is a set of ML algorithms with an API that utilizes computer vision. Based on deep learning, the algorithms automatically detect a vehicle's body and analyze the extent of the damage. Paralleled machine learning and analytical pipelines speed the analysis process up to seconds to:
Car damage recognition ML algorithms can be retrained based on the customer’s data set and delivered on-premises or as SaaS. This way, the API adapts to the specific business needs and serves as a well-integrated solution to be used in the claims automation process.
The solution speeds up data processing, saving the company’s spendings on human resources, defending form fraud (in 80% and more), and boosting the process of image data analysis in times. The system is used on sight and guides a user on actions to meet photo requirements. Deploying Car Damage Recognition, businesses replace a human-operated time-consuming process of claims proceeding and approval with machine learning algorithms and analytical systems.
An ML system developed by Altoros reduces the time and efforts spent on human inspection and ensures smart decision-making for the following businesses:
Prevents from fraud (in 80% cases), speeds up in times the underwriting process.
Decreases operational costs, brings customers’ satisfaction and higher retention rate.
Creates a collaborative environment, brings transparency to the repair process and costs.
Damian Castelli
Chief Delivery Officer
d.castelli@altoros.com617 841-21214900 Hopyard Rd. Suite 100 Pleasanton, CA 94588
