The insurance industry strives a lot to win the trust of their customers. Imagine a scenario where the right ones are not rewarded and the wrong ones are rewarded. This leads to chaos or loss of faith in a system.
Now the question is ‘what breaches the trust utmost’? In any business, it is the money that matters in return for the investment that the customer paid for a service or product. When it comes to insurance, customers expect a reward for the premium they paid. During risks/accidents/deaths they expect the reward from the insurer during the claims process. Because of this reason, claims processing is the most crucial stage for the insurers. It should be seen in the context that, not all those who claim are not genuine ones, but at the same time the genuine claims need to be rewarded. It is at this stage fraud analytics powered insurance processes comes to the aid of insurers.
Why is it Important to Detect Fraud?
According to FBI, about $45 billion is lost every year in insurance fraud. Handling claims is not a simple process. On the other, it is the most complex process in the insurance processes. Complexities include frequent file transfers, gathering adequate information, sieving misinformation from the right ones, etc. All these contribute to the complexities for the insurers. If the insurance carrier is unable to identify whether the claims are genuine or fraud, it is a foregone conclusion that the insurance carrier will undergo huge loss leading to a chain of losses to other sectors linked with it.
Today, customers are looking at quick and quality services. Customers may not like a scenario where more time is required to conduct background checks. Even if the insurers use the best communication to soothe their feeling, customers leaving a sad note or unimpressed, can send wrong feedback on the social media. To avoid all such instances, the answer lies in fraud analytics. Technically speaking with the help of analytics insurance carriers need to integrate data sourced from claims notes, telematics data, social media, OFAC (Office of Foreign Assets Control), weather data etc., inspectors can develop pattern recognition algorithms to speed up the claims process. While developing the algorithms, reliable high-quality data is identified and correctly integrated with all the meta-data labels. The process includes analyzing, filtering and segmenting by a computer-based system that analyses various risks.
Ultimately the bottom line is to provide nearly automatic clearance for simple, straightforward cases, and immediate expert attention on the complicated or suspected claims. Analytics also helps in streamlining the internal processes. This will result in saving the valuable time of the customers. If there is a possibility to reduce the waiting period of the customers with fraud analytics, they will hail this as a big success in the service area.
Thanks to analytics, today insurance executives are empowered to make informed decisions for strategizing, carving new niche markets, as well as building loyal customers. Fraud analytics is promising for insurance carriers as it has the capability to respond to the evolving insurance industry.
According to Coalition Against Insurance Fraud anti-fraud alliance, speaking for customers, fraud accounts for 5-10 percent of claims costs for insurers in U.S. and Canada. Nearly one-third of insurers (32 percent) agree fraud constitute to 20 percent of claims costs.
To Pursue Path to Profit Power Insurance Processes with Fraud Analytics
For insurance carriers, the main issue is to raise profits amidst tough competition. The facts and figures above mentioned states fraud constitute 20% of claim costs. Take the example of P&C industry to understand the impact of the loss. The insurance Information Institute says that the profit of P&C insurance industry income analysis, from 2010-2014 is $55.5 billion. If 20% can be added as profits through fraud analytics, it will immensely help the industry to contribute to the GDP of the nation benefitting all stakeholders. Therefore insurance carriers who are pursuing to install trust in their customers must power insurance processes with fraud analytics.