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Transforming Accounts Receivable Data Capture with IDP

Transforming Accounts Receivable Data Capture with IDP

Intelligent Document Processing (IDP) is a next-generation solution for accounts receivable and other finance processes. IDP replaces manual data entry for accounts receivable processing and, through machine learning, continually improves accuracy and reduces cost. Over time, organizations are seeing up to a 90 percent reduction in costs, 90 percent straight-through processing, with an accuracy of 99 percent.

In accounts receivable, process automation, data analysis and forecasting begin with data capture. Unfortunately, that has long meant a considerable manual effort by accounts receivable staff, retrieving, opening, reading, and keying or copying and pasting information from a massive volume of documents and sources into accounting systems. Manual document processing is time-consuming, error-prone and expensive.

OCR and robotic process automation (RPA), which convert scanned images into text, help. But they only capture characters. They do not “understand” the data and cannot extract, categorize, index and enter the correct data into the right places in systems for further processing.

AI for Accounts Receivable

However, now the application of artificial intelligence allows intelligent document capture. Intelligent document capture, or IDP, is set to revolutionize financial operations and other data-intensive operations across the enterprise.

Intelligent document processing is a next-generation solution for accounts receivable and other finance processes. As Deloitte explains in a report on IDP, it “automates the processing of data contained in documents—understanding what the document is about, what information it contains, extracting that information and sending it to the right place.”

IDP employs machine learning, deep learning, and natural language processing and generation. Solutions that combine these technologies with OCR and RPA allow companies to replace hours of manual work, and reduce errors and cost. IDP provides touchless document processing for remittance advice, checks, lockbox images, and bank statements for accounts receivable. It captures data from PDFs, all kinds of image files and scans, even from the body of emails.

IDP reads, extracts, organizes and indexes data from complex financial documents. It converts information from semi- and unstructured documents into structured data for entry into a company’s ERP or accounting system or into an AI-supported order-to-cash platform.

Accounts Receivable Revolutionized

IDP replaces manual data entry for accounts receivable processing and, through machine learning, continually improves accuracy and reduces cost. Over time, organizations are seeing up to a 90 percent reduction in costs, 90 percent straight-through processing, with an accuracy of 99 percent.

The best IDP systems also support multiple languages and currencies and provide a digital assistant with voice, text, or chat support. They also facilitate integration with proprietary and third-party systems.

The benefits for accounts receivable include:

  • Replacement of time-consuming manual data extraction methods
  • 99% and above accuracy rates
  • Reduction of document processing time by 70%
  • Reduction in lockbox fees
  • Improvement in employee productivity and morale
  • Freeing human resources for higher-value tasks
  • Reduction in AR costs

Companies can access IDP as a stand-alone tool in a per-use model. In addition, some, like Emagia’s Gia Docs AI, also offer cognitive data capture as an integral part of an AI-based accounts receivable/order-to-cash hyperautomation platform.

As a stand-alone tool, Emagia’s Gia Docs AI is available as a cloud-based SaaS application that comes with an AI-as-a-Service model. Gia Docs AI is a multi-tenant cloud solution, accessible from anywhere with a browser. Gia Docs AI establishes connections through secured channel SSL, and because it is a cloud solution on AWS, all AWS security policies apply.

For a demonstration of Gia Docs AI, request a demo.

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