Case StudyMetlife

Metlife reduces document processing time by 40% by automating data capture from manual documents

Metlife uses Captricity’s READ engine to decipher data from manual documents. The READ engine leverages computer vision to convert hand written material into digital format, processing upto a million documents in an hour. Metlife has been able to automate 42% of documentation capture process. The engine handles exception such as unreadable characters by tagging them for human review.

Context

Metlife is in the middle of automating processing of handwritten documents which still form a major portion of claims processing

The Project

"Captricity’s READ engine decodes hand written forms into digital format using using techniques such as inception, residual networks, and their descendants. The algorithm is trained using more than 10million images. Metlife has deployed the platform to automate the process. Captricity also developed a custom solution to add details about the exception so that reviewers can do the checks faster."

Results

According to Captricity: * Increased straight-through automation by 42% * Reduced processing time per form by over 50% * Reduced the time spent on manual exception handling by 70%

Related Use Cases

Use Case

Recognise unstructured text, e.g. handwriting, in documents to extract information to streamline processes like account creation, loan and insurance origination and documentation

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