Optical Character Recognition (OCR) in 2020: In-depth Guide

Imagine you want to edit a printed document like a book, a magazine article or a printed contract. You need to spend hours to type the document from the beginning and be careful about the mistakes. Or you can use an Optical Character Recognition (OCR) tool to scan the printed document and digitize the whole text.

OCR is a great solution for converting human-to-human communication but falls short when converting more structured documents such as forms that need to be processed by machines.

Human-to-human communication is mostly in the form of free text like the one you are reading now. Such documents are called unstructured data and while they are great for human-to-human communication but they are hard for machines to understand. OCR converts the text in unstructured data into machine readable text so it can be searched and therefore more easily consumed by humans. Read more

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Invoice Capture: Guide to most firm’s first AI purchase in 2020

Invoice capture is a growing area of AI where most companies are making their first purchase of an AI product. This is because invoice capture is an easy to integrate solution with significant benefits.

While digitization helped automate numerous processes, mostly rule based software was used in digitization. Invoice capture software is different. Invoice capture involves both reading the invoice text with Optical Character Recognition (OCR) and understanding its context with machine learning.

We answered all your invoice capture related questions: Read more

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Invoice Processing: First Process to Automate in 2020

Invoice automation (also called automated invoice processing) is a maturing area of automation with limited implementation risks and significant benefits. Invoice automation would free up back office finance/procurement teams to focus on higher value added tasks.

What is invoice automation?

Invoice automation allows straight through processing (no human interaction) most of the time for the entire invoice process. Invoice automation involves

  • monitoring for invoices: Invoices arrive in companies as PDFs, image files and increasingly rarely as hard copy documents.
    • For digital invoices, an RPA bot or a simple email automation tool can flag emails with invoices and forward them for data extraction. Some companies use a dedicated email address for invoices to further simplify invoice monitoring.
    • For hard-copy invoices, companies are switching to using a single address to centralize invoice scanning
    invoice capture: Extracting relevant details (e.g. bank account, ordered item) from the invoice. If software does not have confidence in the results, it is sent to employees for a manual check. evaluating invoice against order records and criteria to ensure that the payment is indeed a valid one. Evaluations include
    • cross-checking invoice against purchase orders
    • cross-checking invoice for duplicity
    • using working capital optimization policies to decide payment time
    • using limits to to decide whether to manually process invoice. Invoices that are abnormally large compared to a suppliers’ usual invoices may need to be manually verified to ensure that wrong payments are not done
    • checking the invoice against VAT rules
    recording invoice-related information in systems. For this, invoices without purchase orders need to be added to a general ledger account and machine learning solutions can be used to match invoices to accounts. making the necessary payment to settle the invoice

    All steps except invoice capture are rule-based processes. However, invoice capture relies on machine learning to extract the data in the invoice. For more, please read our article on invoice capture. Read more

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Fraud Detection: In-Depth Guide [2020 update]

With the increase in digital banking and e-commerce transactions, digital fraud has become a larger threat. There are numerous types of fraud such as account take over and new account fraud and companies are estimated to spend >$20bn annually on fraud detection. Since fraudsters improve their techniques over time and since number of transactions are too numerous to deal with manual controls, companies need to rely on machine learning to build resilient efficient fraud detection systems.

What Is Fraud Detection?

Fraud detection is a major challenge for Read more

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15 Fraud Detection Software: A Complete List [2020 update]

We wrote extensively about fraud detection before. If you believe that your company needs a leading edge fraud detection solution, we list the major fraud detection vendors below.

Fraud Detection Companies Ecosystem

Tech giants

Tech giants like Experian are providing end-to-end fraud detection solutions. They have the advantage of having a large sales force and long term relationship with their customers and they have significant budgets to create competent solutions

AI Startups

Since 2000s startups are tackling various aspects of fraud. The first area of focus was to serve merchants which are easy to sell to as they are smaller e-commerce businesses. Later, with increased commercialization of AI, AI vendors started selling to merchants, acquirers and banks. Read more

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