Pamela Beesly

Artificial intelligence-powered insurance claims analytics software would speed up the entire workflow with fewer errors and greater accuracy. Insurance claims processing considers the services rendered by the providers, checks the necessity or validity of those services, and cross-references them with the health plans of the patient. If everything seems to be in order, the claims are accepted and the provider reimbursed. But if there is a slight discrepancy, the claim might be denied or rejected.

This workflow can be programmed by a claims data analyst using an AI-powered insurance claims analytics solution and run to check the claims. The solution would establish certain benchmarks and compare the claims and health plans to look for things that deviate from established benchmarks. Instances of claims information that do deviate are flagged down and sent to teams of professionals that process it manually. The bigger an insurance company gets, the greater the volume of claim data it might need to handle. In light of this, if there is a solution to automate the processing of health care claims data, it is bound to speed up the entire workflow around insurance claims analytics.

Claims that are disputed need to be defended and later settled. If there are lawyers involved, then the settlement could really get bigger. In other words, disputed claims go on to increase the expense of an insurance company, since they take more time and resources to deal with. Additionally, the nature of processing insurance claims puts pressure on the companies to settle the claims faster and move on. There is greater transparency when the process is fast-tracked. But this leads to the possibility of overpayment.


Source: https://www.osplabs.com/insurance-claim-analytics/