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Predictive analytics discovers insights about the future to drive your business

Everyone knows that nearly 90 percent of all data is unstructured and comes from different sources in different formats. Is your company taking advantage of all of that data?

In recent years, predictive analytics and data mining have been used to identify new opportunities, empower the customer services and prevent problems that could lead to lost business or risks related to the project failures.

Business intelligence uses predictive analytics to foresee future patterns from the data available. Using data from past events, companies are able to evaluate the probability of future events. Predictive analytics is used widely in fields such as insurance, medical and financial services to assign a credit rating to customers. With the help of data mining techniques that make data from past events usable, you can also predict which customers are most likely to renew, leave or purchase related products and services.

Any industry can use predictive analytics to reduce risks, optimize strategy and increase revenue.

The Banking and Insurance sector can widely benefit from this technology. For example, predictive analytics systems can identify which customers are likely to be late in making their payments and help support collection, or to understand when someone is thinking about changing providers and persuade them to stay. For insurance providers, these models can be used to identify risks and thus calculate premiums more accurately. Moreover, predictive analytics makes it possible to detect and reduce fraud activity.

Another sector that can benefit from the advantages of data mining and predictive analytics is life science. The ability to predict an increase or decrease in diseases such as heart disease or diabetes, can be useful for governments or healthcare providers in choosing a specific and more efficient health policy. Moreover, analyzing the clinical story of the patient through new personalized medicine approaches allows a more targeted approach for clinical decision making and long-term treatment. This can be very helpful for the health insurance industry to identify patients who are most at risk of chronic disease and find what interventions are best, or identify patients who are not adhering to prescribed treatments and decide to review their health insurance plan.

Security is another area where predictive analytics models are gaining relevance. The ability to analyze how and what a person writes on social media and accurately predict when someone else signs into your account, can have some implications for securing systems and policing things like pay-walled websites. Governments are now using predictive analytics to empower public services and enhance cybersecurity.

The integration of predictive analytics in business activities are already changing the way companies do business. NOTE.


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