Artificial Intelligence Can Greatly Optimize Insurance Claims Analytics

Analyzing insurance claims is an integral part of the American healthcare industry. Insurance payers offer a wide range of coverage for people who are part of a broad array of health plans. Whenever they receive a claim from a provider, they need to process the claim to know if the medical services rendered are covered in the corresponding health plan. This is perhaps the most important part of an insurance company’s operations and it’s where solutions for insurance claims analytics play a big role.

Artificial intelligence might be one of the biggest tools for payers to boost the efficiency of their claims processing activities. Claims assessment is nothing but data analytics, and artificial intelligence has demonstrated impressive capabilities of processing large quantities of information and churning out valuable insights that help the bottom lines of companies. Many industries from shipping, to e-commerce, social media, and wealth management have leveraged the power of artificial intelligence to detect patterns from large quantities of information.

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. 

Artificial intelligence-powered solutions for data analytics in insurance have the power to prevent overpayment and help minimize disputed claims. By assessing historic information according to providers and patients, it is possible to identify patterns and insights about the claims. As a result, such insurance claims analytics software can highlight which claims are more likely to be disputed, or which ones might take longer to process. This insight helps the business side of things at insurance companies maximize their productivity and derive more from existing resources.