Document Analysis & Process Automation with Data Science

What about it?

Any business process that revolves around manual work, varied data sources and disconnected systems, gets trapped in a cycle where more people are dealing to do with manual troubles. It involves a high manual cost of labour, data entry errors which can impact the company’s processing times, compliance, customer retort and ultimately the reputation of the company.

Automation is a process of making a system or process operate automatically with minimal or no human intervention. Automation of such manual data entry processes with ‘Document Process Automation’ powered by the smartness and intelligence of Machine Learning and Data Science will not only eliminate data entry errors, but delivery an intelligent, accurate data that reduces processing time at a fraction of the cost. Thus, the employees can focus from mere data entry to enhancing better customer experience.

As per Forrester’s study, by 2021, we will have around four million robots (automated processes) doing office, administration, sales, and other related tasks.


Take for example on-boarding a new customer. As per a study done by Forrester, it takes about 2 to 12 weeks for client on-boarding process. Manual processes result in errors, such as missing signatures and empty data fields on paper forms. These Not-in-Good-Order (NIGO) documents are time consuming and expensive to correct, but firms have no choice — they have to be fixed. And fixing them is 3–4 times the cost of an error-free digital process, simply because of all the extra time and effort involved in going back to the customer for re-works. This process can greatly be reduced by eliminating the manual filling of forms followed by manual data entry into systems by smart automation like scanning important documents, analysing the information and getting relevant data directly into the systems.

Or it could be identity verification of customers. Instead of manually filling in lots of identity information, data can be extracted from identity documents and used appropriately and efficiently.

And the applications are endless.


As shown above, the process is quite straight forward. It involves scanning the input documents through OCR techniques, then extracting useful and relevant information through various cognitive analytic methods using machine learning techniques, natural language processing (NLP), and finally converting the extracted data into a format that is used in the organization.



The future lies in innovation and continuous business process improvements. Data Science and Artificial intelligence is the way forward. The earlier an organization realizes the importance of its adoption, the higher chances of it leading its competition. Elimination of manual tasks and creating more space for new possibilities through research and innovation gives an organization more credibility towards customers.

To know about the solutions that we have developed for Document Analysis & Process Automation using Data Science, get in touch with us.

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