Introduction to Automobile Insurance Claim Processing with Amazon Bedrock recipe
Introduction to Automobile Insurance Claim Processing with Amazon Bedrock recipe
The Automobile Insurance Claim Processing with Amazon Bedrock recipe is based on
REST and SOAP APIs. Use the recipe to evaluate a claim request, assess the vehicle
damage, and estimate the insurance payout based on the uploaded images.
The recipe facilitates the entry of necessary details into the incident claim
form, allowing you to upload up to five images with a total size limit of 5
MB. It is recommended to upload photos of the damaged vehical from all sides
for the Large Language Model (LLM) to work better.
Upon submission, the process generates a claim ID and initiates vehicle
verification by validating the provided information against the dataset.
After successful validation, the process retrieves a sample price list and
part details corresponding to the selected vehicle.
The process then checks the image format before proceeding with damage
recognition using the specified LLM. This model assesses the extent of
damage, categorizing it as either simple or complex. LLM recognizes damage
only from the list of supported parts. If the damaged parts are not in the
list, LLM returns the damage level as complex.
For simple damage levels, the LLM provides a list of damaged parts, and the
process calculates an approximate payout.
For complex damage levels, the application undergoes further review to determine
the list of damaged parts based on the uploaded images. An email containing
the images and claim information is sent to the reviewer.
After the reviewer's assessment, the process calculates the approximate payout
and sends an email to the specified recipient with the payout details.