A Review of AI-Enhanced Document Intake Systems Using OCR for Auto and Property Insurance Applications
DOI:
https://doi.org/10.63282/3050-922X.IJERET-V6I4P110Keywords:
Artificial Intelligence (AI), Optical Character Recognition (OCR), Intelligent Document Processing (IDP), Auto Insurance, Property Insurance, Machine Learning (ML)Abstract
The algorithms of AI and the use of Optical Character Recognition (OCR) are redefining the automation of auto and property insurance, meaning that the unstructured and rather complex data can be shuffled around. The article cogitates on the processes of document classification, data extraction, and claims management using AI technologies, i.e., Machine Learning (ML), Natural Language Processing (NLP), and Robotic Process Automation (RPA). These systems improve the accuracy of operations, risk assessment, and fraud identification, and reduce the time spent on manual interaction and paper processing by automating volume and processing analysis. Moreover, AI-assisted OCR models are used to facilitate intelligent decisions, workflow, and insurance process compliance. The other aspect that is discussed in the research is a literature review of comparative OCR and its use in multilingual and handwriting text processing, which has led to the development of document intelligence in insurance. By default, AI-enabled OCR systems represent a significant advancement in automation of smart, data-driven and scalable document management in the insurance industry
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