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business process automation

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Improving Efficiency with Intelligent Expense Claims Processing

In the world of modern expense claims processing, the primary challenge has been the labor-intensive and time-consuming nature of the task. Today, organizations are harnessing the power of automated business document processing by integrating OCR, with KUBE 365 leading the way in orchestrating this process. In this article, we explore how expense claims processing is reshaped, with a focus on choosing the right OCR strategy. We’ll discuss two key approaches: training your machine learning models and opting for ready-to-use solutions.

The Challenge of Unstructured Documents

Expense claims often come with a diverse range of receipts and invoices in various formats, making them a challenge for traditional OCR systems. Unstructured data, handwritten notes, non-standard layouts, and low-quality scans pose significant obstacles to an efficient and automated processing workflow.

This unstructured nature of the data can be particularly tedious when relying solely on manual human intervention to read and fill out the necessary information. The complexity of dealing with handwritten content, irregular document layouts, and suboptimal scan quality often results in time-consuming and error-prone data entry tasks.

Training Your Machine Learning OCR Models

To tackle this challenge, organizations can opt for Machine Learning OCR solutions that provide access to train their machine learning models. With KUBE 365’s comprehensive platform, you can enhance processes with the integration of Machine Learning OCR to accurately extract data from various types of uploaded documents. This approach provides flexibility and adaptability, ensuring better results for challenging documents.

Examples of Machine Learning OCR solutions that provide the ability to train and extract data from custom models include:

The Appeal of Black-Box OCR / Pre-built OCR Models

For organizations seeking a more straightforward and quick solution, black-box OCR or pre-built OCR models are available options for integrating with KUBE 365 processes. These ready-to-use solutions come with pre-trained models and require minimal setup. They are an excellent choice for businesses that prioritize ease of implementation and do not require extensive customization.

Examples of Black-Box OCR solutions that can significantly expedite the integration of OCR into your expense claims processing include:

Finding the Right Balance

Finding the optimal approach that harmonizes with your expense claims processing requirements is pivotal. Each organization possesses distinct needs, making it important to tailor your decision according to your specific requirements and priorities, with KUBE 365 providing organizations with the flexibility to accommodate these unique requirements. By deploying a well-suited OCR strategy and leveraging KUBE 365’s workflow orchestration, you can amplify efficiency and guarantee a seamless expense claims processing experience for your team.

Integrating a “human in the loop” at suitable workflow stages can further enhance the accuracy of OCR extraction. By involving human checkers in the process, you can address situations where the OCR may struggle, such as with handwritten or complex receipts. This human oversight ensures data accuracy, thereby minimizing errors and streamlining the overall processing. In conclusion, choosing the right OCR strategy, harnessing the power of KUBE 365, and combining machine & human offers a comprehensive approach to optimizing your expense claims processing, aligning it with your unique business needs.

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