Computer vision based AI models are on the brink of transforming every sector of the economy. This technology promises to automate a wide range of processes and services, creating significant cost and time efficiencies. Insurance is one of the industries best placed to reap the benefits of computer vision AI. Automated systems could revolutionize the way in which assets and claims are assessed. However, as with all computer vision use cases, the success of insurance AI projects is dependent on reliable access to high quality training images and video. Companies that choose to create and annotate training data in-house can be faced with a daunting challenge. Increasingly industry leaders are choosing to outsource annotation to experienced service providers, like Keymakr.
This blog will examine the promising potential of AI for the insurance industry and show how data annotation can support further development.
Insurance assessments, both of asset values and insurance claims, require a significant amount of time and expertise to be carried out by humans. Manually assessing the value of a property requires a human to travel to a location and view the property in its entirety. AI has the capacity to partially automate, and greatly accelerate, this process. Specific use cases for this technology include:
- Using satellite imagery to assess property insurance: AI models can use image data to accurately calculate the area of a particular property. They can also identify what material the building is constructed from, its proximity to trees or water, and a variety of other factors that influence the properties risk profile.
- Assessing and processing insurance claims: Computer vision systems can view images of, for example, a car accident and rapidly produce damage estimates. This instant claims processing will dramatically streamline the operations of large insurance providers and help to reduce errors.
Powered by annotation
In order for this technology to fully realise its potential insurance AI developers need to feed their machine learning algorithms with accurate and varied data. These systems will be required to identify and analyse objects and scenarios in endlessly complex real world environments. Creating training datasets that reflect this complexity can be overwhelming for many companies, causing lead researchers to lose focus on their core goals. Turning to professional annotation services can offer a number of specific advantages to insurance AI innovators:
- Data collection and creation: In order to create reliably functioning AI systems companies need access to varied data. However, the right data can be difficult to find in open source archives or via web scraping. Professional annotation services have access to proprietary data harvesting tools and can even create bespoke datasets with in-house studios.
- Annotation tools: Precision in image annotation is vital for the performance of end models. Outsourcing to specialized providers allows companies to gain access to proprietary annotation platforms. These tools ensure that a variety of annotation techniques are carried out accurately. In-built project management systems can also ensure that labeling work is completed efficiently.
- Managed teams: Professional annotation services, like Keymakr, leverage their teams of annotators to ensure quality datasets. Annotation work can be overseen by experienced managers removing this burden from AI companies. Centrally located teams of operators are also able to respond quickly to changing data demands and troubleshooting.
Annotation services for Insurance AI
Keymakr is a leading provider of quality annotation services. By combining cutting edge annotation tools with experienced annotation teams Keymakr is able to guarantee training data that enhances AI projects.