The client is a leading independent insurance adjusting firm in the USA, known for outstanding claim services, which includes General Daily P&C, Large and Complex Loss, Catastrophe, and much more. They are committed to providing superior and highly engaging customer service.
The Client had a Property Claims Estimation System that generated Claim Loss Reports containing damage estimates for the insurance carriers. Due to incorrect data provided by surveyors and human errors, these reports lacked accuracy related to identification of house roof material type (Hip, Gable, and Shed) and type of roof shingles. This resulted in multiple quality checks of the loss report before submitting it to the insurance carrier.
There are multitude of factors involved in evaluation, such as the owner’s data, inspection requests, and other inputs regarding the property. Applying AI can streamline data management process while systematically automating mundane tasks and lowering down redundancies. This results in unprecedented amount of efficiency at each level and creates an error-free claims process. Thus, the client sought Damco’s help in aligning operations, while helping them save cost and time.
challenges
Inaccurate loss estimation reports
Human-errors in claims estimation data
Mundane & redundant operations
Unstructured data from multiple sources
The client engaged with Damco Solutions to break the problem statement into smaller components. The team provided an AI roadmap to tackle the current situation.
Use of advanced tools & technologies to perform claims related activities
Tools like OCR, ML, and technologies like Pytorch and Fast AI were used in the implementation process. Moreover, the team developed and trained advanced neural network AI model for image processing to perform activities related to claim damages present in houses like: Shingle verification (3-Tab or Laminated), Gauge photo identification (Metal, Shingle, or Pitch), Roof type identification (Gable or Hip).
Damco’s system integration with the client’s existing software
The solution delivered by Damco highlighted mistakes present in loss estimates. This helped the client match the identified roof material with those present in claim loss report matrices. Furthermore, images were fetched for training to submit claims loss report via Damco’s system integrated with client’s existing software to provide end-to-end solutions. Correct estimate suggestions were generated to ensure accurate loss reports, which were directed to the insurance carriers.
Through Damco’s unique approach, the client witnessed the powerful potential of AI-assisted processes. The client’s team now has a concrete validation on improving other aspects of their overall function through an AI-assisted approach. They have a clear model for transition and a roadmap for scalability. Few of the other benefits delivered were:
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