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Advanced Analytics in Insurance

Advanced Analytics in Insurance

The big data revolution is transforming the Insurance industry is ways that were unimaginable just a few years ago. Insurers are building better strategies for customer retention, optimizing operations and managing fraud. However, there is still a very long way to go before we can say that Analytics in Insurance has truly arrived!

If insurance agencies had a crystal ball, they would foresee the future and know the nature of each and every risk, and it would also help them structure their policies accordingly. But unfortunately, there is no such crystal ball. Traditionally, a lot of effort was put to derive insights from the unstructured data obtained from the policy holders. Advanced data analytics in insurance, predictive analytics and proper data mining aid insurers in setting up a proper pricing strategy, product innovation, relevant segmentation, and also help in gaining underwriting profitability.

Multi–variate predictive modelling involves careful examination of the historical data, and identification of its patterns helps gather insights that were previously unknown. It also helps in solving specific business problems. Predictive models offer insurance underwriters a statistically sound, purposeful and steady method for enhancing underwriting techniques and thus improving the business bottom line.

If you are losing your customers due to insufficient research and planning, advanced analytics in insurance can help retain and grow your customer base by helping you predict and customize the right offer for the right customer. Better Customer insights also help to increase the persistency of the insurance and thereby increasing portfolio profitability. It also helps you gain operational efficiency and aids you in risk and compliance management.

Big Data enabled Advanced Statistical analytics helps to integrate and model all the structured as well as unstructured customer data from the myriad of scattered sources and develop comprehensive insights into each existing customer. This helps in cross selling and/or up selling marketing campaigns apart from pre-empting the risk of lapsation or cancellation of policies which can lead to profitable portfolio results.

Big Data analytics also helps insurers improve their decision making process. It can generate real time Customer insights with 360 degree profilers and develop insightful scoring, utilizing internal as well as specific external data points. Insurance companies that use advanced analytics are outperforming competitors by wide margins and cruising towards business innovation and profitability.


About Ketan Pandit

Ketan has over 8 years of experience in helping organizations develop messaging for their clients. Having worked in multiple roles across some of the largest global technology firms, Ketan takes care of Marketing, Brand Development, Partnerships and PR for Aureus.

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