Automating Insurance Claims Processing and Updating to MongoDB Database

Maheswara Reddy Basireddy

Abstract: The insurance sector has tremendous hurdles in managing an ever-increasing number of claims and related documentation in today's fast-paced business climate. Conventional manual insurance claim handling procedures are frequently labor-intensive, prone to mistakes, and time-consuming, which leads to inefficiencies and possibly unhappy customers. By integrating contemporary technology into automated claims processing, processes may be greatly streamlined, data management effectiveness can be increased, and overall operational performance can be eventually improved. This study investigates the use of the Python programming language and a number of supporting modules to automate the processing of insurance claims and integrate a MongoDB database. The main goal is to efficiently collect and handle insurance claim data by utilising state-of-the-art technology including optical character recognition (OCR) and strong data processing capabilities. The suggested approach attempts to offer a reliable and effective system for storing and retrieving insurance claim data by utilising the powers of MongoDB, a versatile and scalable NoSQL database, and its Python driver (PyMongo).

Keywords: Insurance claims processing, automation, MongoDB, NoSQL database, PyMongo

How to Cite?: Maheswara Reddy Basireddy, "Automating Insurance Claims Processing and Updating to MongoDB Database", Volume 12 Issue 8, August 2023, International Journal of Science and Research (IJSR), Pages: 2532-2536, https://www.ijsr.net/getabstract.php?paperid=SR24506175358, DOI: https://dx.doi.org/10.21275/SR24506175358