The insurance industry is well aware of the transformative power of big data and predictive analytics.
What do we mean by big data? Quite simply, a mass of information held digitally that is so large it is difficult to analyse, search and process. In terms of predictive analytics, it’s the application of advanced mathematics to these large data sets whilst using new technologies to improve forecasting capabilities. The issue of big data and predictive analytics has impacted on most industries, especially the insurance sector. In fact, insurance is probably the biggest industry to be able to benefit from big data and analytics, presenting insurers with a massive opportunity to improve processes and ensure adherence to the growing regulatory challenges.
Unlocking key information through data analytics can provide competitive advantage, uncovering unknown correlations and hidden patterns. In turn, premiums can be more accurately correlated to risks, something particularly relevant now given the 2016 arrival of the Solvency II directive (a risk-based system, meaning that capital requirements are aligned with the underlying risks of the company).
So what’s the biggie with big data? Well, big data provides the opportunity for insurers to develop new insights and ultimately improve business processes. Combined with predictive analytics, insurers can place themselves on the cutting edge of insurance technology and address pertinent business issues, quickly. Predictive analytics can undoubtedly drive better performance and insurance companies are beginning to recognise the value and benefits of applying technology to this critical area of their business. Essentially, seeking competitive advantage through competitive knowledge.
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