How Generative AI Revolutionizes IDP

Generative AI Revolutionizes IDP

  What is generative AI?

Generative AI refers to a branch of artificial intelligence and Machine Learning Model that focuses on generating new content, such as text, images, or even entire scenarios, based on patterns and examples found in existing data is based on the idea that AI can learn from existing data and then use that knowledge to generate new data that is similar to the original.

IIDP is intelligent document processing (IDP) technology that deals with automated data extraction from documents. IDP systems use various techniques to extract information from documents, such as optical character recognition (OCR), machine learning, and natural language processing (NLP).

As you and we all know, in the banking and financial sector, they are dealing with a huge volume of documents, where they extract data with accuracy and carefully. Here the combination of Generative AI and IDP has come. The combination of Generative AI and IDP software like Docextractor, use its algorithm, to extract all filled and incomplete data key value from the document and save them into the database.

The combination of generative AI and IDP can be used to automate a wide range of document processing tasks, such as:

  • Extracting data from documents in the banking sector
  • Classifying documents in Insurence Sector
  • Summarizing documents Legal Secore
  • Generating reports in Health Sector
  • Translating documents

The Power of Generative AI

Generative AI works by using deep learning, neural networks, and reinforcement learning. Deep learning is a type of machine learning that allows AI models to learn from large amounts of data. Neural networks are a type of artificial neural network that is inspired by the human brain. Reinforcement learning is a type of machine learning that allows AI models to learn from rewards and punishments.

Imagine you are a bank manager wanting to create a new marketing campaign. You could hire a team of designers and writers to create the campaign, but that would be expensive and time-consuming. Instead, you could use generative AI to create the campaign.

Generative AI would learn from existing marketing campaigns and then generate new content that is similar to the original. This content would be both realistic and creative, and it would be much cheaper and faster to create than traditional marketing campaigns.

Generative AI could also be used to design new products for your bank. For example, you could use generative AI to design a new type of credit card that is more user-friendly and secure.

Generative AI is a powerful tool that can be used to improve the efficiency and effectiveness of businesses. If you are a bank manager, I encourage you to explore the possibilities of generative AI.

Challenges in Traditional IDP Methods

In every bank, as we all  know., if you are a bank manager, you will more know than me. In Year Ending time, or when you are getting a huge amount of Loan and Account Opening applications employees who manually review these applications, but, sad to say, the process is slow and error-prone

That time, you are thinking, How to Automate the whole process. You could use traditional IDP methods to automate the process. However, these methods have several challenges. First, they can be difficult to set up and maintain. Second, they are only sometimes accurate. Third, they can be expensive to implement.

For example, one traditional IDP method is optical character recognition (OCR). OCR is a technology that can be used to convert text from images into machine-readable text. But, in the handwritten text case, it does not give accurate results. 

In this case, You could use generative AI to automate the process. Generative AI is a type of artificial intelligence that can create new content, such as text, images, or audio.  For example, generative AI could be used to generate new loan applications based on existing loan applications. It automatically learns from existing applications and data and gives us predicted and accurate data. This would allow you to automate the process without the challenges of traditional IDP methods.

Benefits of Generative AI in IDP

  • Increased accuracy: Generative AI models can be trained on large datasets of documents, which allows them to learn the patterns and structures of these documents. For example, imagine you are a bank manager and you need to process a large number of loan applications. An experiment shows that With generative AI, a large number of loan applications will be processed accurately and efficiently.
  • Reduced costs: This is the era of artificial Intelligence and Machine learning. Under the Advance LLM, Generative AI reduces manpower and also saves time. Let’s say that you currently have a team of 10 people who are responsible for processing loan applications. With generative AI, you could reduce this team to 5 people, while still maintaining the same level of accuracy and efficiency.
  • Increased customer satisfaction:  With generative AI, the application could be processed and approved within minutes. If a person applies for a loan application in your bank, within just minutes, this AI software, validates the all data of documents and proceeds to further process of approval. This would give the customer a positive experience and make them more likely to do business with your bank in the future.

Case studies showcasing Generative AI’s Impact on IDP

In this digital world, A company has developed a platform that can be used to extract insights from unstructured data. The platform uses Large Language models to understand the structure, style, and meaning of documents, spreadsheets, and images. This means that you can ask the platform questions about any document and it will give you human-level performance. In addition, this AI-based platform allows users to ask questions about any document and receive human-level performance.

Users can automatically process documents through the pre-built apps available on the platform. For example, they can take an existing lease contract and generate an amendment that extends the lease by two years, streamlining content creation.

For example, let’s say you have a lease contract that you need to amend. You could use the platform to ask questions like “What is the original lease term?” or “What are the renewal terms?” The platform would then be able to answer your questions and even generate a new amendment for you.

Though The platform is still under development, it has the potential to revolutionize the way we interact with unstructured data. It could be used to improve document understanding, automate workflows, and generate new content.

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