How Can Big Data Be Used In Insurance Claims Analytics?
MD: Big data helps the analysis of large amounts of structured and unstructured data. Let us see how health care providers and insurers can use big data in insurance claims analytics.
Big data is the technology that facilitates the analysis of large amounts of structured and unstructured data. Healthcare providers and insurers can use big data to devise models. Machine learning algorithms can be developed to train insurance claims analytics machines to evolve as per changing dynamics of data. The use of big data can be used to simplify insurance claims processes and streamline workflows.
4 Ways How Big Data Can Help In Insurance Claims Analytics
Big data can be helpful in insurance claims analytics in several ways. Listed below are some of them.
1. Insurance claims analytics can use big data to speed up claims processing
Big data in insurance claims analytics has helped insurers find anomalies and inconsistencies in insurance claims data. Large amounts of data for insurance analytics help determine the accuracy of the finding instead of finding anomalies based on a limited data set.
Companies can use historical data and match claims against this data to derive unique analytical results. For example, one of the analytical data points from this activity is finding insurance adjusters to work on insurance claims. The credential and experience of the insurance adjuster often determine the time for the insurance claim to be resolved.
2. Reduce fraud
The FBI came up with a statistic that is revealing and horrifying. FBI estimates that health insurance payers spend an enormous amount annually on insurance fraud. This startling estimation suggests that existing insurance claims analytics solutions are getting it wrong, or the fraudsters are becoming smarter.
Many insurance claims analytics software vendors use big data in insurance claim analytics to identify fraud early. Complex and adaptive predictive analysis is used for this, and it helps detect even the most innocuous and trivial of manipulations. It is possible to identify suspicious activity and spot potential offenders.
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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.
