Fraudulent charges are a problem that afflicts insurers around the world. The events associated with fraud generate millions in losses in insurers; this cost has caused companies to reduce their operating costs to maintain profitability. This reduction has led to the diversion of valuable resources that could be used to identify, investigate and prevent irregular activities.
In 2014 Accenture surveyed different insurers in Europe, 7 out of 10 respondents said that their fraudulent claims had increased over a period of three years. So it is a fact that fraud must be prevented and detected before the activities occur.
The challenge for insurers, then, is to improve these detection abilities without negatively affecting the claims process of real and legitimate clients. In this way, Big Data & Analytics are the allies to protect organizations and make sure to provide good experiences to customers.
How to achieve this goal?
- Using business rules that conform to the behavior of your customers. In this way, fraudulent historical claims are compared in various types of insurance of the company, so if a new claim meets those characteristics, an alert is generated that saves money, time and effort.
- Use predictive models to find patterns and trends that can quickly identify fraudsters and improve fraud prevention in the future. The objective is to detect possible frauds quickly, thus reducing the payments made to fraudsters.
- Analyze fraud networks. Advanced tools that are based on data analysis help researchers detect chains of organized actors to make fraudulent charges. In this way, they reveal hidden relationships between the insured and chains of criminals, thus detecting when the activities point to fraud.
Advances in technology are aimed at supporting organizations in overcoming challenges in their business. Insurers can protect their resources with an ally in their processes: data analysis. Contact us and know how we can support your organization.
With information of
IBM Big Data Hub