DocuHall - Automotive

Overview

WNS-Vuram DocuHall-Automotive, powered by Appian low-code capabilities, helps enterprises gain meaningful insights by extracting any type of unstructured or semi-structured document from any variety of documents with better accuracy, speed, and intuitive experience.

Here are some challenges/problems that solution solves:

1. Every organization regardless of its size and industry is reliant on data. However, 80% of the data that any organization has is unstructured. Currently, enterprises collect the documents from their customers and extract the information manually.
2. Thus, manual processing may take a lot of time and effort and may be prone to errors. Legacy technologies may help with data extraction but the quality may be poor.
3. Specially to the automotive industry, the documents related to vehicles are multiple, and also the data on the documents are a lot unstructured. The organizations dealing with the automotive industry find it difficult to collect all documents and manually verify it.
4. Our DocuHall solution comes with out of box DOvC AI capabilities to extract key details from vehicle documents like licenses, certificates and based on the business rules bring it up to the queue of users to verify and process it.

Key Features & Functionality

1. The solution will be integrated with the customer's existing process.
2. The customer's customers send various types of documents to avail themselves of the services. The customer would use this solution to classify and extract the information from those documents automatically to send to downstream or process it further to provide the right service to their customers and draw insights from the data.
3. Configure business rules - Set the threshold accuracy for different document types to route it as a task to review the extract based on accuracy.
4. Out of the box AI model is trained to handle document types like licenses, vehicle certificates, with workflows and business rules configuration.

Benefits & Business Impact

• Reduce the time taken to extract information.
• Improve the accuracy of data extraction.
• Improve the STP rate of each document/customer case.
• Cost savings for customers in processing documents.
• Time saved in searching for document information.
• Reduce manual errors in processing data.
• Reduce non-compliance issues.
• Scale and productivity - the number of customer requests/documents being processed.
• Increase in customer revenue/customer conversion.
• Employee satisfaction and customers' satisfaction.