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Risk and Financial Modelling in Insurance: Big data and analytics creates artificial intelligence in insurance providers

Cortana Intelligence and Azure Machine Learning are helping insurers unlock data and provide insights beyond areas supported by actuaries.

Data has been an important part of the insurance industry for centuries, but the emergence of big data has brought unprecedented challenges to insurers around the world. Today, insurance companies large and small need to ingest, process, analyse and act on massive amounts of data from heterogeneous sources quickly and cost effectively. As legacy analytics tools fail to provide the necessary capability and agility for new big data workloads, insurers are discovering Cortana Intelligence, a fully managed big data and advanced analytics suite, as an enabler for their new data, analytics and intelligence needs.

For example, If P&C Insurance, a leading property and casualty insurance company serving three million customers in the Nordic region, found that it was able to uncover the value of data more quickly and cost effectively using Cortana Intelligence’s advanced analytics capability. If P&C worked with Microsoft to complete a pilot project on Cortana Intelligence, with a focus on Azure Machine Learning (ML). The main goal was to evaluate how well Cortana Intelligence Suite handles different aspects of predictive modelling as a replacement for If P&C’s on-premises legacy data analytics platform. The success of the pilot led the company to replace its legacy SAS platform with the Cortana Intelligence based solution.

Three use cases were evaluated in the pilot: a churn model was used to predict whether or not a customer would cancel their policy in a 40-day window surrounding their renewal date, while an upsell model predicted the probability of success of a potential upsell communication to a given customer. Data including age, duration of the policy, product composition, payment solution, household data and contact points on phone and web was used for these two models. The third case, an email text analytics project, helps to classify inbound email, such as identifying messages with negative sentiment that may indicate increased risk of customer churn.

The solution met or exceeded If P&C’s expectations in all the use cases that were evaluated. As Cortana Intelligence components are designed to work together, the company was able to use Azure ML web services to quickly integrate the output of predictive analytics into an end-to-end data pipeline. The solution also helped to boost user productivity, enabling much shorter ramp times for data scientists and engineers. In addition, If P&C estimates that it will realize significant cost savings using Cortana Intelligence Suite. Besides Azure ML, the company is also adopting Azure Data Factory, Azure Data Lake, Azure SQL Data Warehouse and Azure HDInsight, and is integrating these with Microsoft Dynamics CRM.

By utilizing Cortana Intelligence, insurers can uncover the value of data quickly and cost-effectively and deliver meaningful visualizations to support focused, insightful information that empowers actuaries to identify and respond quickly to risk. For example, financial modelling can be used to create a vivid, up-to-date view of risk focusing on areas such as customer profitability, customer churn and potential fraudulent activity.

The advanced analytics capabilities of Cortana Intelligence enable constant analysis of the customer base which can be combined with rich visualization to deliver value to insurers in any number of areas relating to risk. Milliman is leading the way in this area, with its Power BI solution that provides data to actuaries in a far more visual, meaningful way than the traditional tabular view.

As the insurance business generates growing volumes of data, risk management will continue to demand increasing amounts of data modelling. With Cortana Intelligence, insurers can enhance the data set they get from their models, generate more insight from that data, and put themselves in a position to make better decisions, transforming their data into business value.

Find out more by downloading Microsoft’s Perspectives on Insurance Risk Modelling


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