Intelligent Document processing (IDP) offers a breakthrough in document data capture for accounts payable, accounts receivable and treasury operations. IDP solutions like GiaDocs can process up to 90% of the documents in global finance and treasury, freeing up resources from mundane tasks to focus more on problem-solving and strategic tasks. Here, we outline four reasons to investigate the leading IDP systems that find and extract data from unstructured and semi-structured documents for your enterprise.
Finance departments have been trying to automate for decades, with varying low levels of success. Of course, to automate accounts payable, accounts receivable, or treasury processes, a company must digitize the process-requisite data. And that has continued to require much time and manual effort, even with advances like OCR.
Now, intelligent document processing (IDP) offers a breakthrough in data capture of the data in documents for accounts payable, accounts receivable and treasury operations. The application of artificial intelligence, machine learning, natural language processing, and deep learning capabilities by leading IDP providers can achieve data capture data not only in structured but unstructured and semi-unstructured documents and feed them into an organization’s system.
There are caveats. Digital transformation presupposes the digitalization of data, and the market is flooded with companies offering IDP solutions. As noted by
researchers at Gartner, not all IDP solutions are alike. For example, some cannot successfully extract data from unstructured documents, which according to a commonly accepted estimate, is where 80% of enterprise data resides. However, top IDP systems that properly deploy artificial intelligence technologies can capture unstructured data.
The financial operations of accounts payable, accounts receivable, and treasury have data locked up in unstructured documents like email, pdfs, and memos and semi-structured documents like invoices and purchase orders. As promised, here are four reasons to investigate the leading IDP systems that find and extract data from unstructured and semi-structured documents for your enterprise.
Time Savings
Manual data capture requires time, on average 10 minutes per document. (It also requires concentration while repeating the same actions again and again.) However, IDP, also known as cognitive data capture, is fast. Compared to proficient data entry personnel, it is exponentially faster. IDP can read and extract data from hundreds of documents in minutes. There’s simply no comparison with human data entry.
Cost
Data-capture costs include the direct cost of employees plus the costs of errors and delays. It will vary by enterprise, but as an example, assume an accounts payable employee’s total cost is $30 per hour. The AP employee can manage six documents per hour if the average document takes ten minutes start-to-finish. That’s a cost of $5 per document review and data capture. Multiply that by the number the staffer must process. Though “your mileage may vary,” all organizations face a considerable cost.
In contrast, IDP can process hundreds of documents in minutes. Further, it operates 24/7/365. With initial instruction followed by automatic machine learning, and given its speed, a sound IDP system significantly reduces the high cost of manual data extraction and input. It also improves data accuracy, saving further costs of error correction, which can be ten times the cost of prevention1.
IDP Handles Up to 90% of Processing
Top IDP solutions can provide straight-through data capture for up to 90 percent of the documents in accounts payable, accounts receivable and treasury processes. That represents a massive reduction in manual effort. As a result, humans can refocus on more captivating and valuable work. And refocusing away from mundane, repetitive but here-to-fore necessary tasks to problem-solving and strategic work improves employee morale.
Discrete Data Digitalization
The fourth reason to investigate IDP for accounts payable, accounts receivable and treasury operations is that digitalization of data is necessary for digital transformation and essential even for existing discrete automation processes. Of course, data capture is vital to any IT automation. But it is also the first step in hyperautomation of whole processes such as procure to pay, order to cash, or record to report that is now possible thanks to AI, analytics, RPA and other technologies.
The Logic of Investigating IDP
Whether an enterprise is planning digital transformation, hyperautomation of specific financial processes, or just a step forward in its automation, there are good reasons to explore IDP. Data capture is the first step in digital transformation at any level, and the cost savings, speed, workload relief, and broad applicability of IDP provide compelling reasons for implementation.
As noted above, not all IDP solutions are created equal. Emagia’s cognitive data capture system GiaDocs is a cloud solution for modern global finance and treasury teams to automate document data extraction and data entry into their financial systems. GiaDocs AI has human-like cognitive skills to read, learn, understand, and extract data from finance documents related to accounts receivable, accounts payable, and treasury services. GiaDocs can read documents in various formats, in multiple languages, date and currency forms, with complex table and spreadsheet data embedded in them.
