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OCR + IDP For Data Reconciliation

OCR + IDP For Data Reconciliation 

IDP (Intelligent Document Processing)

IDP is an innovation that compiles several technologies related to Optical Character Recognition, Machine Learning, Natural Language Processing, and computer vision. Using these technologies, IDP aims to solve one of the biggest challenges in our digital era: migrate, transform and digitize paper documents into usable and reliable data.

The cornerstone of IDP is OCR, this technology is capable of extracting the data from images and paper documents. OCR has more than 10 years of existence, and it has been improving and improving throughout the years, adding more languages, characters and fonts. Not only these aspects but also the algorithms used have been evolving and machine learning and deep learning have played an important role to achieve high levels of accuracy.

However, OCR stand alone solutions can not longer shine in the market as the specifications and business requirements look for aspects like:

IDP Scope and key elements

The ultimate goal of IDP is reaching data usability, in order to do this there is a requirement to boost and cleanse the input to maximize OCR performance and accuracy. The IDP Basic model contemplates Preprocessing, Data extraction and Post processing.

AppMan ocr

AppMan OCR is boosted by preprocessing and post processing to achieve the highest accuracy rates in Thai language for structured and unstructured documents. This technology has been acknowledged as the TICTA Award winner of Business Service, The Other Solution recognized at Thailand ICT Awards 2020. Due to its capabilities to read and ingest text from a paper document for a variety of business processes such as mobile onboarding, identity verification KYC, tab banking and more.

IDP for Document Reconciliation

Document reconciliation is a business process which involves mapping of various types of data into matched categories.

This process usually involves company CRM and key databases that are used for daily operations, but the input usually requires human interaction to capture, validate, update and compare details from various data sources from the company.

With IDP you can trim the human data capturing and even optimize the validation and update of information. This process usually involves several data and can be applied to several industries, one example is for financial institutions like banks for

WHAT ARE THE GAINS OF COMBINING OCR WITH IDP?

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