Context

Document Processing

Every organization has to process documents. This task can be complex and tedious – but it doesn’t have to be with Symphona. By using Symphona’s automation and AI tools to optimize document processing, your organization can streamline these repetitive processes and save time and resources.

Specifically, Symphona can help optimize in the following areas: 

Documents With Unstructured Data 

Processing unstructured data in documents can be a significant challenge due to the lack of predefined format. The absence of standardized representation makes it challenging to extract and use the information in a structured manner. 

Two solutions to this are leveraging natural language processing (NLP) techniques to extract relevant information from the text and utilizing Optical Character Recognition (OCR) to convert the document into a machine-readable format.  On their own, each has issues with time and accuracy. However, by utilizing both alongside Symphona tools, organizations can make sense of vast amounts of unstructured data.

Familiarizing With Rules, Policies, and Regulations

Processing documents can be a complex task – especially when dealing with different types of internal and external rules, policies, and regulations. Managing this complex net requires document processors to have a comprehensive understanding of these rules. 

Organizations must recognize these challenges and utilize tools like Symphona that can ensure their policy document processing meets the necessary standards. By doing so, they can streamline their operations, minimize errors, and deliver high-quality services to their customers.

Reviewing and Extracting Key Information

Document processing can be a complex and challenging task, primarily due to the difficulty of extracting essential information. Many business documents can be lengthy and filled with technical jargon, requiring a keen eye to identify the most critical pieces of information. Additionally, capturing all relevant details accurately is vital in situations where minor inaccuracies can have a negative impact on items like revenue, cost, customer experience, etc.

Keeping track of document changes and updates can also be challenging, as information evolves over time. As a result, document processing requires a thorough and meticulous approach, which can be time-consuming. However, with the help of an experienced team, these challenges can be overcome. 

By leveraging Symphona, it is possible to ensure that all necessary information is accurately captured and processed, leading to more efficient and effective operations.

Solution

How Symphona Helps

By using Symphona Flow, Converse and Resolve, document processing can be much easier for your organization. For best results, organizations should ensure their unstructured data is extracted.

Flow and Converse’s NLP and OCR technology can help companies overcome some of the difficulties associated with unstructured data. In particular, Converse can analyze free-text documents such as policyholder correspondence. It also automatically extracts data from customer documents such as policy applications and claims forms. OCR can scan customer documents and convert them into digital formats that computer systems can process. This attribute saves time and effort that would otherwise be spent on manual data entry. Companies can extract key information from unstructured data sources by using these technologies, making it easier to process and manage. In turn, this boosts operational efficiency and helps reduce costs.

Reviewing and Extracting Key Information

It can become cumbersome for employees to continually input important information as it involves a lot of time and tedious work. However, the procedure can be simplified through a seamless process involving repetitive manual activity using OCR, NLP, and AI technologies.

NLP, OCR, and AI are extremely beneficial in document processing. NLP helps identify key information and concepts in a document, while OCR extracts that information for further analysis. AI then provides insights and recommendations based on the extracted data.

Each of these technologies has its strengths and weaknesses, but they can provide a powerful tool for processing documents. NLP is effective at understanding the meaning of the text, while OCR is better at quickly extracting large amounts of data. AI then analyzes what data to find patterns and trends that would be difficult to spot.

By using all three technologies together, companies can significantly improve their efficiency in document processing. NLP speeds up review times by identifying relevant information more quickly, while OCR and AI can automate the extraction and analysis of that information. These attributes save companies time and money while also boosting the accuracy of their document processing.