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Predictive Analytics for Insurance

Posted. 07.12.2011


How to grow your customer base, prevent fraud and improve profitability.

These are challenging times for the insurance industry. In the wake of the global financial crisis, many insurers are facing change and uncertainty as they seek out the most cost-effective ways to conduct business. Customer expectations are rapidly changing as consumers become more savvy, price sensitive and far less loyal. At the same time, insurers are attempting to reduce expenses through cost transformation, while fiercely battling competitors to win new clients and retain existing ones.

In this volatile market, customer churn and insurance claims losses can quickly overwhelm insurance providers. That’s why insurers are adopting a new way of harnessing their volumes of customer and business information to move ahead. Instead of using this data merely as a historical record of what has happened, they are now analysing it to reliably predict what will happen next. Instead of looking in the rear view mirror, they are turning their focus forward to gain an accurate view of the road ahead.

The science that has made this shift possible is called predictive analytics. Predictive analytics employs advanced analytical algorithms to process historical data and create models that can make predictions about future outcomes. More simply put, it helps insurance providers answer their most critical questions: How are we doing? Why? What should we be doing?

In this white paper, you learn how predictive analytics is being applied across the functional areas that drive success, the benefits it delivers and the IBM technologies that make it possible.

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Smarter Computing - The Next Era of Computing

Smarter Computing - The Next Era of Computing

A short animation on how clients are choosing to design their IT that help will them take advantage of new opportunities, to create new markets, identify trends, delivery more quickly and utilize IT resoureces more effectively - against a flat IT budget.