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Leveraging analytics to counter fraud

Insurance Fraud claims cost the industry tens of billions of dollars annually. Shockingly, about 60% of the fraudulent claims go undetected. Fraud directly impacts the profitability of an insurance company. Insurance companies have put in sophisticated mechanisms to counter fraud, but have not been able to plug in the leak completely. The only way to counter Insurance Fraud is by predicting possible instances of fraud in advance by leveraging the power of analytics.


Fraud continues to be a challenge for the Insurance industry. Even with the current process controls and specialized monitoring at insurance companies, fraud continues to happen. It is largely owing to the changing nature of fraud and the fact that most of the losses are incremental such as over-billing, over stating a loss, etc. The daily level need to meet an agreed service level for an activity such as proposal processing, claim processing or commission payout further raises the requirement to diagnose instances of fraud on the go.


The insurance process generates data at every step from lead identification to underwriting and closure of sale. With these data points, a real time fraud framework that can predict instances of possible fraud can be built. Using behavior analysis and interaction data points, the system can throw severity prompts to tackle fraud.


Aureus' Fraud Analytics solution is built on years of experience in analyzing real time events to calling out suspicious activity all the while ensuring that the false positives are taken into account. Using CRUX, we are able to deliver critical insights to the business user in near real time, by processing structured and unstructured data from scores of data points such as interactions, transactions, relationships, demographics etc. CRUX delivers the capability to analyze and identify fraud before it happens and lets the business user develop models in real time to counter newer types of threats that emerge. CRUX's Fraud Analytics is eight times faster than the current system with an accuracy rate of nearly 90%.

CRUX help in identifying Insurance Fraud in real time or near real time by using a combination of advanced analytics and machine learning. CRUX can identify fraud cases at new business stage, claim stage and also at various policy life stages. CRUX develops a highly accurate risk profile for every customer, which is regularly updated to reflect a customer risk profile.


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