This article will take you through how these companies can automate several procedures like menu digitization or invoice processing that are traditionally done manually to save time and operational costs. We have all had moments when we suddenly crave a good dessert. Getting that big tub of ice-cream after a long day at work would've been an inconvenience a few years ago. But food delivery apps can get it to you at a lightning fast speed. With companies like DoorDash, DeliveryHero, GrubHub, FoodPanda, Swiggy, Zomato and Uber Eats competing for a greater market share in the food delivery market, adopting technology that aids companies to scale up their operations has become a necessity to stay relevant.
This blog post will take us through how a business which need to ensure customer due diligence (CDD) can automate the KYC (Know Your Customer) processes using deep learning and computer vision based solutions. But before we get started, let's familiarise ourselves with some basic terminology. Customer Due Diligence - CDD involves verifying that your customers are who they say they are and assessing the risks associated with each customer like the possibilities of fraud, money laundering, terrorism financing, etc. This includes verifying your customer's name, address, photograph by analysing bank documents, utility bills, etc. Anti Money Laundering - AML refers to a set of laws, regulations and procedures meant to prevent criminals from disguising illegally obtained assets and funds as legitimate income by safeguarding against trading illegal goods, tax evasion, market manipulation, corruption of public funds, etc. Know Your Business - KYB involves vetting a business trying to establish a relationship with a bank by determining their Ultimate Beneficial Owners (UBO) and enforcing compliance by assessing risks associated with the business. You can learn more about beneficial ownership structures and a risk based approach to counter laundering here.
Find out how data entry automation can help your business optimize workflows. Eliminate bottlenecks created by manual data entry processes. Click below to learn more about Nanonets PDF scraper. Data entry is the process of extracting and entering relevant information in a computerized system or ERP software. This is an essential process in businesses that seek to reorganize data into convenient formats for additional downstream processing.
Receipt digitization addresses the challenge of automatically extracting information from a receipt. In this article, I cover the theory behind receipt digitization and implement an end-to-end pipeline using OpenCV and Tesseract. I also review a few important papers that do Receipt Digitization using Deep Learning. Receipts carry the information needed for trade to occur between companies and much of it is on paper or in semi-structured formats such as PDFs and images of paper/hard copies. In order to manage this information effectively, companies extract and store the relevant information contained in these documents. Traditionally this has been achieved by manually extracting the relevant information and inputting it into a database which is a labor-intensive and expensive process. Receipt digitization addresses the challenge of automatically extracting information from a receipt.
OCR software have been critical to businesses looking to grow quickly by leveraging digital workflows & automated processes. OCR software automate data capture from scanned documents/images and digitize the data in convenient, editable formats that fit into organizational workflows. Scanning & processing documents such as invoices, receipts, and images for valuable data has traditionally been a manual process fraught with errors and delays. OCR software solutions help businesses save time and resources that would otherwise be spent on data entry & manual validation/verification. Modern OCR software are fast, accurate and can handle common document processing constraints such as poorly formatted scans, handwritten documents, low quality images/scans, and blemishes that would have traditionally required extended manual interventions. More and more organizations are automating document processing workflows to go paperless and leverage cloud-based digital solutions that improve bottom lines.