Using Analytics to Reduce Insurance Fraud & Increase Customer Satisfaction
Timothy Powers 270003F3FN email@example.com | 2012-05-09 13:46:48.0 | Tags:  insurance smarter-analytics fraud predictive-analytics decision-management santam claims risk | 2 Comments | 8,196 Visits
The range of fraud and the resourcefulness of fraudsters pose a daunting problem for those charged with its detection and prevention, especially in the insurance industry where fraud accounts for $80 billion of the U.S. insurance industry’s incurred losses and loss adjustment expenses per year. (See infographic)
A big reason for this loss is that data remains segregated in disparate, disconnected systems in most insurance organizations. But with so much pressure on this industry – from streamlining operations to creating a customer-centric enterprise to optimizing risk management – the days of underutilizing data, its most valuable resource, are over.
In the area of claims management, this has never been more evident. Today’s honest consumers want to file a claim, have it processed quickly and receive proper settlement. Customers can easily switch carriers these days and a poor customer service experience through a difficult claims handling process is a big trigger.
A study by Claes Fornell International (CFI) Group, an employee and customer satisfaction consultant, showed that nearly 61 percent of people who have a bad experience with their insurance company’s contact center will consider switching companies, and 26 percent said they will definitely switch companies because of a bad call center experience.
Santam, South Africa's leading short term insurance company, is a great example of a firm that transformed its claims processing methodology in terms of speed and efficiency, but also provided new insight to identify false claims more quickly.
Working with OLRAC-SPSolutions, an IBM Business Partner, Santam built an IBM Smarter Analytics solution that not only saved $2.4 million on fraudulent claims in the first four months, but enabled faster payouts for legitimate claims. (Watch video below)
In fact, the solution delivered a full return on investment and also helped uncover a motor insurance fraud syndicate in less than 30 days after the system went live.
The claims division also developed a new operating model for processing claims, depending on varying risk levels. Using IBM predictive analytics software, Santam can automatically assess if there is any fraud risk associated with incoming claims and allows the insurer to distribute claims to the appropriate processing channel for immediate settlement or further investigation, which optimizes operational efficiency.
With the enhanced claims segmentation, Santam is also able to reduce the number of claims that need to be assessed by mobile operatives visiting the customer or claim site, resulting in further considerable cost savings for the company.
Speed of claims handling is also an important differentiator for the company. Before using predictive analytics, it took at least three days to settle claims. Now, Santam is able to settle legitimate claims within an hour through automated, real-time risk assessment.
For insurers, this isn’t such a bad policy to follow.
For more information:
· Read a more detailed customer success story on Santam
· Read more how IBM Smarter Analytics helps manage fraud, risk and regulatory compliance
· Download the whitepaper, “Insuring the Future of an Industry”
· Watch the Claims Optimization demo