Insurance companies around the world are encountering unprecedented change as a result of regulation, the evolution of markets and technology, and competitive pressures. The key asset affected by all of these is data – the regulators need it, the market generates it, and technology solutions open up new ways of dealing with it and interpreting it. Clearly, a strong data management strategy is crucial to an organization trying to respond to these issues. Such a strategy has to address more than just gaining operational efficiencies; it must also help organizations extend the business value of data and systems by making it relevant, accessible and actionable, and strengthen and support the decision-making process.
While new regulations have created an explosion in the amount of data and in-depth record keeping insurers must manage, it has also created a wealth of new information from which they can derive greater strategic business value. In a low-interest, low-growth environment, insurers know the best way to drive their businesses forward is to increase their focus on new, more competitive and profitable offerings for their customers, leveraging technological innovation and new markets while reducing their reliance on dwindling organic growth and investment returns.
Regulation is often seen as a burden on the business, but this is not a fair picture. In fact, an October 2015 survey of global insurance professionals, conducted by Insurance Risk and sponsored by FIS, revealed that more than 80 percent of participants believe data produced to satisfy regulations can be useful for the business as well. However, there are many concerns about the data being collected, specifically:
While these challenges resonate throughout the insurance industry, they are also opportunities to affect positive change. With the help of the right technology firms can establish a collaborative culture, and help it grow. By developing a flexible and innovative data management strategy, firms can respond quickly to inevitable changes in information requirements as well as to changes in the sources and types data they can access. They can ensure that data is of high quality, is consistent across the enterprise, and is disseminated to the people that need it, when they need it..
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