Customer: A national legal support services firm specializing in creditor’s rights and mortgage defaults
Challenge: Categorizing and extracting data from legal documents and notices quickly and efficiently
Solution: Infinia ML used our Intelligent Document Processing platform to develop a suite of machine learning models to extract pertinent document information and reduce the need for manual processing
In order to process incoming requests, employees are manually reviewing over 20,000+ legal documents per month to extract all of the relevant data. The information extracted from these documents ranges from demographic information to details about the type and nature of related court cases. The customer has a team of on-site employees as well as outsourced teams that manually input the collected information into the customer’s databases.
The customer wanted to reduce the number of manual hours required to process documents and the need for employees dedicated to data entry. They also sought to decrease the margin of error related to human processing.
Infinia ML’s IDP Platform configured a processing system that utilizes customized machine learning models to perform an automated review of legal documents. This solution extracts, categorizes, and validates pertinent data from legal documents to populate the customer’s databases and complete vital services for their partners.
A human-in-the-loop component was also incorporated to efficiently review and update invalid or flagged information identified in the documents.
Infinia ML used our IDP platform and document processing expertise to create algorithms that extract and categorize specific data from legal documents, saving the customer thousands of hours of manual processing time and allowing them to reallocate manual resources elsewhere. In addition to significant time and cost savings, the customer was able to improve the overall accuracy of the process and eliminate the need for outsourcing.
This same machine learning technology can be applied to a number of other use cases to automatically find context and relevance in unstructured data:
Infinia ML used machine learning to build our customer an end-to-end document processing solution that can intake, characterize, and accurately parse contracts of interest.
Infinia ML developed machine learning models to extract text data from non-standardized documents.
Infinia ML developed machine learning models to extract text data from non-standardized documents.
Get in touch to discuss how machine learning can help you deliver smarter, faster, more useful services and solutions for your customers.
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