Automate Claims Processing

Notebook

Accelerating Insurance Claim Process with Machine Learning

Predicting the category of a claim early in the process using: Random Forests, Support Vector Machines, MLP Neural Networks and K- Nearest Neighbor Learning

Automated claims processing at Xactware with machine learning on AWS

Automating Property Claims processing via Item Classification and Matching. Used NLP through a multi-class classifier built on text features, and a multimodal branched deep neural network acting as a ranker for refining item matches

Paper (30 minutes)

Automating Car Insurance Claims using Deep Learning Techniques

An automated AI system that has different components to tackle each of the tasks performed during the claim process using an end-to-end pipeline for the user to upload images, visualize the predictions, and also get the estimate of the cost of repair.

Article + Github Repo

Automating claims adjudication workflows using Amazon Textract and Amazon Comprehend Medical

Python application to automate the extraction and validation of healthcare claim documents using Amazon Textract and Amazon Comprehend Medical.

Ensemble Machine Learning Project - Allstate Insurance Claims Severity Prediction

Predict what kind of claims an insurance company will get. This is implemented in python using ensemble machine learning algorithms.

Github Repo

Insurance Claims Severity Prediction

Using a dataset from Kaggle; provided by AllState (a US-based insurance company); this notebook tries to predict the severity of claims using different machine learning techniques - so as to enhance the claims processing speed