Big data analytic can improve insurance claims processing

Insurance is a means of protection against financial loss and a form of risk management used to hedge against uncertain contingencies. Big data analytics can greatly improve the claims processing process in the insurance industry. Here are six ways in which it can be used:

1. Fraud Detection: Big data analytics can improve the detection of fraudulent claims, which account for one in ten insurance claims. Predictive analysis can be used to identify fraud by utilizing a combination of rules, modeling, text mining, database searches, and exception reporting at each stage of the claims cycle.
2. Subrogation Opportunities: Big data analytics can help identify subrogation opportunities that are often missed due to the large volume of data. Text analytics can be used to search through unstructured data to find phrases that indicate a subrogation case, thus maximizing loss recovery and reducing expenses.
3. Settlement Optimization: By analyzing claim histories, big data analytics can optimize the limits for instant payouts, reducing costs and ensuring fairness. Analytics can also provide significant savings on things like rental cars for auto repair claims.
4. Loss Reserve and Forecasting: Big data analytics can more accurately calculate loss reserve and forecast claims, especially in long-tail claims like liability and workers compensation. Analytics can reassess the loss reserve whenever claim data is updated, ensuring that the correct amount of money is on hand to meet future claims.
5. Claim Assignment: Big data analytics can be used to score, prioritize, and assign claims to the most appropriate adjuster based on experience and loss type. In some cases, claims can even be automatically adjudicated and settled.
6. Litigation Propensity: A significant portion of a company’s loss adjustment expense ratio goes to defending disputed claims. Analytics can be used to calculate a litigation propensity score, determining which claims are more likely to result in litigation. These claims can then be assigned to more senior adjusters who are more likely to settle them sooner and for lower amounts.

For more information on how to use big data analytics in the insurance industry, feel free to contact E-SPIN for Big Data monitoring and Big Data Security tools, including vulnerability assessment, continuous activity monitoring, and Big Data application performance monitoring. You may also be interested in other posts.

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The post original create 2017-Nov-13, last rewrite and update 2023-Jan-09.