Fraudulent claims hit the companies with humongous losses every year across the globe. In the U.S. alone, the costs are as high as $80 billion per year.
Such big numbers compel the insurance companies to stand against these frauds and bring in robust mechanisms to identify, combat, and forecast such frauds.
Data Analytics is one such savior to the insurance companies which is upon saving them from huge losses, by analyzing the previous scenarios which identify the frauds and forecasts the futuristic risks.
Here are mentioned some of the ways through which Analytics is saving the insurance sector from many of such frauds.
Digging in the Data
The data collected from various areas are the mines for investigating fraudulent activities. The application of Analytics over these data can bring out remarkable results and also can assist in predicting futuristic mishaps. The forecasts can prevent huge losses and strengthens the relationship between insurers and customers.
Suspicion Score
There exist some opportunistic claimants who try to exaggerate the claims, and are categorized under cultural fraud.
A step towards preventing and forecasting these frauds would be the application of Analytics in assigning Suspicion Score to a particular claim. The question that arises here is what is the basis of scoring such claims?
The process is quite easy and involves excavating past fraud records and applying Analytics over these data sets. Analytics can compare the fraud-related data from the past to justify the truth value of the present claim. Based on the obtained likelihood for the present claim to be an actual fraud, it is given a score, which is known as Suspicion Score.
Continuous Assessment
Continuous assessment and regular checking are necessary to detect fraud at an early stage and reduce the losses. Predictive Data Analytics should be regularly utilized to obtain a pattern for insurance fraud. The claims should be regularly assessed to decide the correct truth value. Analytics is a tool, the usage of which can be modified, and also can be automated to minimize manual repetitive tasks which (manual tasks) increase the probability of mistakes and missing out important points.
The continuous rescoring model which updates the Suspicion Score for a particular claim after every regular interval helps decide the actual likelihood that the fraud has occurred. Also, the fraud pattern obtained from regular assessment, helps the insurers to stay cautious against such future frauds and assists in their successful prevention.
Revised Approaches
Like the insurers, with time, are advancing towards adapting more powerful tools and shields against frauds, so are doing the criminals. The criminals are also advancing their cross tools and so, frauds are still prevalent.
The insures need to ensure that the tools and approaches towards dealing with the frauds and identifying such frauds are continuously getting up-to-date. Predictive analysis should be utilized to chalk out newer fraud patterns regularly so that the upcoming powerful frauds are identified early and accurately.
During the economic downfalls, a greater number of policyholders may come over with creative and powerful claims. Thus, the insurers should always keep the claims section and staff aware of the current market scenario so that frauds could be minimized to the maximum extent.