How to Catch Fraud Before You Pay the Claim

Posted on

January 2nd, 2018


aiInsurers catch most instances of fraud after they already paid for the claim. However, it is harder to get money back from a fraudulent claim than it is to prevent fraud in the first place. This was not always the case. With the rise of powerful analytics, insurers can use the data to make predictive models. These models can trigger an investigation into a claim if it contains markers of previous cases of fraud. This will allow insurers to stop fraud before paying the claim.

How Data Models Work

Data analytics are not new, but insurers had not been able to use them to their full potential until now. Statistical modeling and machine learning were not readily available in the past, but the technology has made significant strides in recent years. For example, an insurance agent could always survey claims data and try to draw conclusions. However, this method would prove too slow and too prone to error to be reliable.
With machine learning, the insurance agent presents the machine with sets of data (in this instance, true claims and fraudulent ones). The machine then learns over time how to develop insights into these sets of information. The machine can then use this knowledge and apply it to new claims. Through this method, the machine can interpret with reliable accuracy if a claim is high risk of being fraudulent.

Catching Fraud During FNOL

It is best to identify fraud during or right after first notice of loss (FNOL). This is because each step after FNOL is investigative or communicative. It is easier to look for fraud at the outset of the claim than to go back after the fact and try to find the relevant information.
Internal and external data are both relevant for fraud detection. Internal data, the information insurance agents collect, can provide common fraud statistics. However, external data is just as important for statistical modeling. This includes information such as regional demographics or weather conditions during the time of the loss. All of this data combined creates one premier set of data to use for predictive modeling.
Fraud is not the cost of doing business—at least not anymore. Fraud detection and prevention will always be a crucial element to claims management, but, with new technology, insurers can simplify and expedite the process. They can even identify fraud before they pay the claim. To learn more about claims management and fraud prevention, contact the experts at Actec.