The Wikipedia definition of information extraction is “the task of automatically extracting structured information from unstructured and/or semi-structured machine-readable documents and other electronically represented sources.” Although the presence of information extraction can be dated back to the late 1970s, it is of greater significance in the present times. This is because of the growing availability of information in unstructured form. This unstructured information lacks semantic metadata, and by transforming it to be made accessible for machine processing, businesses can gain access to important information. Artificial intelligence has transformed several spheres of business, and similarly, it has streamlined the process of information extraction. In this blogpost, we will be discussing AI-driven information extraction and how it can transform your business.

Information Extraction Made Easy Using AI

In the present world, humans have access to a wide range of information. As the amount of information keeps growing, so does its complexity and the difficulty in managing them. Businesses built on customer and employee data need to devise ways to efficiently extract and manage this information. Although the growing availability of information is vigorous, the good news is that the pace of technological advancements is keeping up with the growth of information. The growth of deep learning approaches and OCR technologies is paving the way for wider adoption of automated solutions for information extraction. Some of the benefits of leveraging AI for data extraction and verification include:

  • Increased efficiency
  • Greater speed
  • Reduced human error

Using artificial intelligence, businesses can unlock inaccessible information stored in paper or other analog formats. This information can prove to be of significant value and can be used for business growth. Now, let us take a closer look at the three different industries that could benefit from AI-powered information extraction and verification.

  • Insurance: The insurance industry can benefit highly from the extraction of information from their huge repositories of paper. An example of this could be in underwriting, wherein decisions about premium and coverage are based on claims history, historical patterns, and other factors. ML algorithms can streamline underwriting by identifying patterns in digitized documents. Also, intelligent optical character recognition aids in decoding information and documents. In the case of claims processing, image recognition can help in analyzing the photos captured by claims adjusters and classify them according to their type. Thereby through AI, insurance providers can effectively assess their applicants’ risk and make more informed decisions.
  • Banking: As with the insurance industry, the banking industry possesses several records on assets and customers. Although compiling this information is laborious and expensive, it is a necessary task as well. In banking, information extraction can be done by combining AI with optical character recognition (OCR) technology. Through this, records that were previously stored on paper can be digitized to extract useful information. Also, machine learning algorithms can be used to interpret this information and make decisions. AI can also help in identifying information like social security numbers from unstructured data. Another benefit of AI is that it helps in retrieving information from multiple data silos and can also compensate for any errors such as spelling mistakes.
  • Oil and Gas: The oil and gas industry has several assets located in different remote locations. AI plays a vital role in this industry by automating the process of going through several paper documents to look for seismic records and geological maps to find prospective drilling locations. By digitizing this data for natural language query, businesses can make faster decisions. Also, predictive analytics can be used to find new drilling sites.

The process of extracting information from unstructured data and verifying the same could be a herculean task if businesses do not digitize the process. Leveraging AI and new technologies like natural language processing (NLP), machine learning, and intelligent document recognition, businesses can gather and maintain data in an organized manner. Information extraction can be employed in various other areas, other than the ones discussed above, such as media monitoring, healthcare records management, and pharma research. Irrespective of the industry that your business belongs to, leveraging AI-driven information extraction could prove to be a gamechanger in the way data is extracted and verified and can help transform your business.

Latest posts by Vidya Ramakrishnan (see all)