Infrrd AI Enabled Intelligent Document Processing for Complex Documents

Old school ways of conducting financial transactions are gradually bidding adieu. Automation, AI, and data analytical tools are taking over to ease the workflow. Everyone in the market wants to move ahead to enhance customer experience, deliver value, and obtain market share. So boarding the train of digital transformation has become the first choice for most companies. Now the question is what does it signify for the present and future of this industry? Adapt and adopt, these are the key terms for most companies who are walking in pace with the technological revolution. Finance being the people first sector is shifting its focus to make their customers’ personal lives better and easier. Businesses are prioritizing greater agility and higher quality for their overall process improvements. Some of the changes they are going through are: Making investments on technology which can support or expand their operating models, thereby making their processes responsive, effective, and digita

WHAT IS OCR? Data entry can often turn tedious and inaccurate if done manually. But, you can avoid this cumbersome process with an automated optical character recognition software. What OCR does is, it uses machine learning to scan each character on a page individually. It allows the documents to upload as text documents instead of images. We could scan easily and promptly any kind of printed document, be it receipts, invoices, contracts, utility bills and much more with this solution. HOW IS INFRRD’S OCR DIFFERENT FROM TRADITIONAL OCR? Our  OCR solution  is different in two ways: We don’t use templates but NLP for recognizing entities in a document. This helps us identify business names, bank details, amounts, prices etc. irrespective of where they occur in the document. Read more  here  on why templates are a bad idea. We use Machine Learning to fix what traditional OCR’s cannot figure out, by building an automatic context around the document. Watch  this video  to understand

Data analysis without data preparation it is a myth. Unless we feed the right data in a proper format, Machine Learning algorithms won’t be able to solve our problem. If we give one wrong input then we end up where we started. So it’s very important to understand what data preparation is and how one can do it. Data, in its original form, may have a lot of missing pieces or disarrangement. Through data processing, one can modify this raw information from a specific database to a format which is understandable and learnable by the machine. Mentioned below are the ways that, we at Infrrd , employ in preparing our data. 1. Data selection: It is necessary first to identify the type of data we are going to be working with. One has to keep in mind whether the available data will be able to address an existing problem or not. We keep certain factors in consideration before selecting the data: Data should not be of low quality: Low-quality input= low-quality output. Dataset is not err