Insurance

Powering innovative solutions in insurance with the highest quality training data to accelerate ML pipelines.

Use cases

Claims management

Automate claim registration and document validation with effective detection models built upon clear data and accurate labeling.

Fraud detection

Enable AI-powered models to identify incremental fraud patterns, such as fake images or invalid documents.

Virtual inspections

Develop computer vision assistants to examine and assess buildings, houses, apartments according to your insurance metrics.

Damage assessment

Annotate damaged vehicles, buildings, and other insurance items to let computers locate the damage, evaluate the extent of repair work, and the amount of reimbursement to the client.

Roof underwriting

Using quality annotations of aerial images, build a smart AI model to estimate and validate the age, condition, and characteristics of a roof.

Risk prediction

Collect historical data and let your model alert in case of calculating a high probability of hazardous events such as wildfire or floods.

Top 6 use-cases of computer vision in insurance

With the advancements in computer vision, it’s obvious that the future is built upon machine learning. Computer vision is actively changing various industries, insurance being one of them. As the ultimate data annotation platform, we looked into the applications of computer vision in the insurance businesses and discussed some of the most popular use-cases.

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SuperAnnotate for insurance

Machine learning completely remodels the insurance industry and provides tools to automate lengthy paperwork, minimize claims leakage and even detect risky or fraudulent events. Annotation quality is especially critical when it comes to insurance.

Training this kind of large, complex model requires a robust data annotation workflow with quality management measures and smooth iteration cycles. SuperAnnotate is designed to feed quality data into AI models and get them into production up to 5x faster.

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