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Key takeaways from the blog
Insurance Claim Processing is an effort-intensive process. With many touchpoints, including receiving the first notice/claim intimation, creating a case folder, receiving the documents in order, reviewing them, adjudication, settlement, explanation of benefits/remittance advice, and reimbursement, it is a tedious workflow. Of these multiple sub-processes, only a few have been brought under the scope of automation, for example, first notice and explanation of benefits. However, the majority of the points follow regular manual processing. As a result, the entire Claim Processing cycle takes a long time for fulfillment. Claims Adjudication is one such human-dependent and lengthy manual process. Automation improves processing efficiency and cycle time. With each Claim running into a few megabytes to gigabytes and consisting of unstructured data in various formats, AI/ML-powered automation, which extracts the required data and processes it further, is a must-have.
First intimation and explanation of benefits (EoB) are the two prominent insurance claim processes already in the ambit of automation. These two processes leverage Intelligent Automation to a particular extent to accelerate Claim Processing. First intimation uses a digital platform accessible on any device, anytime, anywhere. EoB automation parses data from multiple sources and organizes it in a standard format for payment processing/reimbursement and archival/referencing.
Claim Adjudication is the process of receiving the Claim documents from the insured entity/person, assessing the Claim, comparing it with the terms and conditions in the Service Level Agreement (SLA), and manually deciding whether to honor the Claim and in what proportion. The process generates multiple calculations and analysis documents at various levels. At the end of the Claim Adjudication process, all the final calculations are noted along with reasons in the Explanation of Benefits (EoB) or Remittance Advice. This advice is crucial for keeping track of why the payment was made or withheld, along with the specific reason and endorsement of the adjudicators/reviewers.
Claims Adjudication/Processing includes checks at different levels. Intelligent Document Processing and Intelligent Automation parses the unstructured data received in the format of handwritten documents and the video/pictures and ingests and integrates it with the downstream processing systems. Pre-trained AI/ML Claim Adjudication Models capture the tacit knowledge of the adjudicators/decision-makers to build the recommendation Claim Adjudication engines that enable seamless Claim Processing/Management. These AI/ML models sieve through the hundreds and thousands of claims received almost daily. With the built-in jargon and their synonyms related to the different insurance categories, the engine processes the Claim Adjudication and reduces the turnaround time from days to minutes. The models get stronger by handling higher volumes and through each exception handling.
AI/ML Claim Adjudication models improve the experience of both the adjudicators and the customers/insured. Automated Claim Adjudication can be used for both low and high-cost insured entities/items. It results in significant improvement of the overall Insurance Claim Processing. The insurance providers can pass on the savings accrued in the operational costs to the customers through reduced premiums or bonuses.
Pre-trained AI/ML models automate the tedious and lengthy Claim Adjudication. The models handle vast amounts of claims and produce more accurate results with time and higher volumes processed. The models get stronger and more intelligent with each exception handling. They eliminate fraud from the entire value cycle even while speeding up the Claim Processing.