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October 15th, 2020
How AI OCR for Financial Spreading Strengthens Risk Management

From government to banks and financial institutions, hardbound documentation and financial reports on paper continue to be the backbone of their services. However, today businesses are now beginning to realize the importance of digitized documents. Computer technology’s growth, combined with AI, has quickly outdated previous innovations and made new advancements. The transformative power of technologies like OCR — image processing, extracting data, layout, and handwriting recognition to create digital records combined with AI are rapidly setting a benchmark for credit assessment and strengthening risk management. In this article, we explore the entire gamut of AI OCR for Financial Spreading Strengthening Risk Management.

The Three Dimensions of How AI OCR works for financial spreading

The ability to reinvent your business through an integrated approach of AI-based services with OCR (Optical Recognition Technology) enables traditional solutions of paper claims, documentation, and financial records translated, for financial spreading. Financial spreading lays the foundation for such activities.

Artificial Intelligence makes your business smarter at every touchpoint, which means aiding strategic decisions with the help of faster and more efficient risk assessment. Especially for financial firms and banking services, reviewing and assessing financial data is paramount for an individual’s credit risk, the legality of documents for business, seamlessly handling complex accounts of conglomerates, and international firms, amongst others.

Today, AI OCR services are opening new possibilities for global businesses to automate, digitize, and optimize information for digital scanning, processing, analysis, and verification helping the business.

i) Identify and extract information and texts from unstructured documents, images, and formats.

ii) Convert invoices, bills, financial reports for digital record keeping

iii) Create documents with large records and files into editable and searchable formats.

iv) Allow systems to recognize, translate and analyze information in multiple languages

In the current era of limited time and quality efficiency, traditional solutions of handwritten paperwork involve human errors, high operational costs, and inaccurate analysis. Let’s take a look at the three dimensions of how AI OCR systems are considered superior.

Today, AI OCR services are opening new possibilities for global businesses to automate, digitize, and optimize information for digital scanning, processing, analysis, and verification.

  • Dimension 1 – Installation
    • Achieving a hundred-precision and capturing financial information is the most accurate manner involves building machine learning libraries and algorithms that make AI OCR for financial spreading faster and more efficient.
    • Using an OCR software run by Google, a business can build a technology that can be ready from scanned text and images. This enables the digitized document for character classification, layout analysis, and segmentation. The software used for this purpose incorporates a complex neural network that extends the reach of OCR to understand and read texts, columns, images, and even layouts that make them readable by your systems.
  • Dimension 2 – Processing of images
    • The 2nd dimension to working with AI OCR involves sourcing an open-source machine and deep learning library like OpenCV that can preprocess input images and improve automation performance. The library is a database of different techniques like color space management, text transformation, and smoothing to convert and automate significant parts of the model with over ninety percent accuracy.
  • Dimension 3 – Data extraction using trained models
    • Once the model starts functioning, the AI OCR system can extract information from structured as well as unstructured documents and images (in all popular formats like jpg, png, gif, tiff, etc.) to store data, make it readable, accessible, editable, and searchable. Furthermore, you can create layouts from the original document in the digitized version to create exact copies.

Importance of AI OCR for Financial Spreading

Let’s understand that OCR is not a new technique for creating digitized financial reports and documents. The relatively more modern combination of OCR with AI-solutions is what makes it a game-changer. Earlier OCR systems used to rely on conventional templates from physical documents that it could extract information from. The process involved a lot of ‘head work’ – extracting information from unstructured sources and a lot of ‘handwork’ – entering data from one application to the other. So, the process involved a lot of human intervention, and the cost and time of performing this activity for every new document made it unfeasible.

With AI-powered OCR services, individuals, businesses, and large corporations can extract and store sensitive information on the cloud and perform a host of intelligent and machine learning processes that can extract insights from such documents and reports, therefore strengthening risk management. Let’s take a look at the various importance of AI OCR for Financial Spreading Strengthening Risk Management.

  • Business processes data intelligence.
    • Cloud-based AI OCR takes standard OCR techniques to a whole new level of sophistication by combining machine learning and intelligent data processing systems (IDP) with intelligent data capture (IDC). Using natural language processing, computer vision technologies, and machine learning tools, any financial institution or business can get business process expertise faster without any human having to play a role in the whole process.
  • Strengthens Risk Management.
    • Combining AI OCR with machine learning systems, you can transform complex credit risk processes that currently depend on unstructured data and slow-moving human analysis. This single tool enables credit risk assessment teams to extract information and aggregate data to better understand at-risk accounts and parties while improving the quality of credit making decisions and developing customized inventions and financial solutions for clients. Offer superior customer experience from start to finish and decisions that take minutes and not weeks.
  • Minimize human intervention and reduce operational costs
    • Traditional OCR systems relied heavily on human resources to define rules and templates, leading to an increase in operational costs, delayed processes, and erroneous results. Today, AI OCR systems are far better in data entry and information extraction that provide high accuracy and save time and money.

Conclusion — Transforming Financial Risk Management through AI OCR

Banks and financial institutions that adopt AI OCR for documentation intelligence find themselves ahead of the curve. The combined ability to expertly manage complex accounts for conglomerates and multinationals, gain market/financial insights to better prepare for a future, create editable and searchable databases for documents, deploy machine learning solutions that demonstrate an impact, and transform the ability automate tedious tasks like data entry and spreading financial analysis is not found anywhere else. The ease, speed, and simplicity with which AI OCR strengthens financial spreading and accelerates credit risk management processes while offering analytics capabilities is truly a game-changing product.

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