Document digitization has become more dominant with the emergence of virtualization, cloud computing, and mobile technologies. This trend is specifically noticeable across the insurance industry that has forever been dominated by the prevalence of paper documents. Insurance organizations have a never-ending chain of documents that flow in and across the organizations via a network of agents, channels, and systems.
Optical character recognition (OCR) deploys technologies to differentiate printed or handwritten text characters that are found in the digital images of physical documents like a scanned paper document. OCR processes examine the text of a document and translate the characters into codes that are further used for data processing. OCR is quite often also understood as text recognition.
Insurance companies exist in an industry that frequently faces changing laws and new processes and face troubles in constantly providing their clients with suitable insurance solutions. It is important to make sure that all the data and documentation are processed accurately. Manual data processing is highly prone to errors or delays, which leaves customers without the coverage they need. The integration of OCR technology can help insurers carry out their tasks efficiently.
Data entry companies deliver OCR solutions and OCR cleanup services that alleviate the quality of the document conversion process. Insurance companies have a storehouse of data that needs consistent processing. The main task of the OCR technology is in industries where data entry takes place in bulk and several printed records are decoded. This is the reason which has made the optical character recognition technology inevitable for the insurance sector. By adoption of OCR and intelligent character recognition, reliable data entry companies provide error-free, on-time data entry services for insurance organizations.
Optical character recognition is a breakthrough technology that has replaced the manual scanning of paper documents. Initially, paper documents were scanned and converted into flattened digital image files. Since this process previously involved human intervention, it was vulnerable to errors and inconsistency. Manual work processes cannot handle the large volume of content, which consequently, delays the workflow. Uncontrollable work delays can affect the customer experience since they need a prompt resolution for all their issues. Delay in claim settling can amplify the customer irritation levels and reduce retention rates and brand reputation. Optical character recognition can help customers to process their documents through a user-friendly format.
OCR enables insurance companies to draw more customers by allowing an organization to do a better job than its opponents when it gets to matching its products and facilities to client needs. For example, several organizations now have online solutions that enable potential clients to upload a copy of their existing policy of insurance. This enables automated analytics tools to evaluate the strategy and then compare it with the company's products to see if better or cheaper protection can be offered to the customer. No manual method can effectively handle the front-end data capture. A good OCR process can automatically transform client documents into precise data that can be automatically analyzed.
Data collection from landing/invoice/ tax receipts/cheques/ order bills-is what OCR does with the mixture of pre-processing image, character identification and word, block and sentence series. But when it gets to gaining context or extracting significance from many of the forms of digital assets, basic OCR alone is not enough. Smart OCR software goes into the image to overcome such difficulties. A software like this helps extract useful data from invoices, records, bills, and paper documents and enables with further assessment and intelligence as required. Custom OCR applications operate in conjunction with smart algorithms to search for particular records like dates, purchase order numbers, document-wide reference IDs. Such competent systems generate more than 90% precise results, enabling thousands of papers to be analyzed in a fraction of minutes.
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The optical character recognition market is on the cusp of the next generation of adoption scenarios that have been enabled with the use of OCR with other technologies. With higher accessibility being provided, the focus of the insurance technology sector is moving towards determining what OCR's next feasible applications might be. This is combined with AI's democratization, along with lower rates of quicker cloud-based computing and storage capacities and the applications are evident. We could see insurance agents and brokers acquiring advanced document comparison tools to evaluate policy documents promptly and record customer queries quicker. Claim examiners could review types of claims and promoting records rapidly to obtain important data needed to create a claim decision. Customers of insurance could potentially match pricing, details of coverage and sub-limitations on complex insurance policies. Over the years to come, the global optical character recognition market is expected to grow at an exponential rate with a CAGR of 13.3%.
