Insurance Claim Automation & Prediction

From claim registration to claim settlement, machine learning is applied in a range of applications. Future claims and the costs connected with them can be predicted using predictive models. Machine learning not only saves insurers millions in claim costs, but also improves customer experience by allowing for faster claim settlement, more effective and systematic probing, and more efficient administration. This allows the insurer to better plan the costs of claims. There are claim document recognition systems that use a cloud-based AI optical character recognition (OCR) service to handle handwritten claims notice papers and reduce the document input load.

Automation Framework

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Figure 1: Insurance Claims Processing & Prediction Framework

The example framework above shows the process of the automated workflow where the system recognizes the data in the documents using the Object Character Recognition (OCR) ML Model, which is trained based on the Business Logic.

The data is then sent through a classification model where the business/operational predictions are made, such as policy premium, claim/sales potential, benefit allocation, etc.

The inferences are reported through the database and Dashboard Visualization, where the relevant stakeholders are able to make business decisions.

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