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How to extract data from payslips using OCR?

Nanonets

In this article, we will understand this document that has become an integral part of our monthly work ritual.  Payslips are crucial for both parties, serving as a payment receipt and a record of financial transactions. Form 26AS (in India) fraud checks record-keeping Looking to extract or parse data from payslips and W2 forms ?

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Bank Statement Analysis: A Complete Guide

Nanonets

Key aspects of bank statement analysis Transaction categorization: Classify entries as deposits, withdrawals, transfers, payments, etc. Expense analysis: Review outgoing payments such as vendor payments , payroll, and operational costs. Revenue tracking: Monitor income sources, including customer payments and interest income.

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Automated order processing: Boost efficiency

Nanonets

AI and ML analyze this data to recognize patterns, learn from previous actions, and make intelligent choices like directing orders to the right approver or identifying potential fraud. The system's automated workflows and integrations unite different platforms, allowing data to move effortlessly through each order processing stage.

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What is Lease Abstraction? Overview and Techniques

Nanonets

Rent: The base rent amount the tenant must pay, along with the payment schedule (e.g., Additional Rent: Any extra payments the tenant must make, such as property taxes, utilities, or common area maintenance fees. Coding Proficiency: Requires coding proficiency for API access, maintenance and debugging. monthly, quarterly).

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How to Automate Insurance Claims Processing

Nanonets

  With automation, insurers can automate repetitive tasks such as manual data entry and document verification, speed up claim processing to increase efficiency and accuracy and minimize errors and fraud. This reduces the likelihood of fraudulent claims being approved, enhancing the integrity of the process.

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The Top 3 OCR Kofax Alternatives

Nanonets

This can reduce processing time by up to 90% and save on costs by up to 50%  Natural Language Processing (NLP): Nanonets employs NLP algorithms to comprehend the context of the extracted data, making it capable of understanding complex and context-dependent information, leading to improved accuracy in data extraction.