How insurers can harness the power of analytics

Insurers have an opportunity to identify and act upon new insights within their business to improve loss ratios and boost sales with better customer service

Rebecca Lambert
Rebecca Lambert
By Rebecca Lambert on 02 June 2017
How insurers can harness the power of analytics

This article first appeared in the Spring 2017 issue of The Record.

Data rich but information poor – that’s how many consider the state of the insurance industry at present, and it’s costing both businesses and their customers. Today, the total cost of general insurance fraud in the US is estimated to be more than US$40 billion per year, representing approximately 10% of the industry’s incurred losses. It means that the average US household can expect a rise in premiums of anything between US$400 and US$600.

Fraud isn’t the only issue. Reports suggest that insurers can do more to use the data available to them to tackle others areas of their business too. Accenture’s 2016 report, Harnessing the data exhaust stream: Changing the way the insurance game is played, estimates that insurers can “increase profitability by between 16 and 21 combined ratio points by using analytics to more precisely measure risk, anticipate and prevent losses, and increase sales via more targeted distribution strategies.”

Jonathan Silverman, Microsoft’s director of worldwide insurance industry solutions, concurs. “Analytics and the ability to gain actionable insight from your data sources is key to building good business outcomes and addressing regulatory pressures,” he says. “We are starting to see more demand for claims reporting and analytics related to improving loss ratios in general (property and casualty insurance) carriers and for improving customer intimacy.”

The first area – gaining insights to improve loss ratios – comes down to having the ability to better analyse vast data streams, extending to new unstructured forms of data, such as social media. “For example, when checking a disability claim for a back injury and seeing that the insured is posting photos of him working on his new roofing project on Instagram,” explains Silverman. “Or a new life policy holder who applied as a non-smoker but has been tagged in a photo on Facebook outside a bar having a cigarette.”

In the past, claims processing has been a very manual process, but technology is giving carriers the use of rules-based engines, predictive modelling and cognitive services. “Claims processing solutions based on the Microsoft platform provide end-to-end functionality, covering functions from first notice of loss to settlement and recovery,” Silverman says.

American Family Insurance – one of the largest property and casualty insurers in the US – provides a good case in point. It is using a solution called Insurer Analytics from Microsoft partner 1insurer to perform near real-time analyses, helping it to save money and improve its processes. Insurer Analytics runs on Microsoft SQL Server and takes advantage of its business intelligence capabilities to provide dashboard reporting, real-time analytics and management reporting.

With more information at their fingertips, insurers not only stand to gain valuable new insights into risk factors, but they can serve their customers better too.

“Customer and product analytics solutions enable employees to get the insight they need – helping them to increase profitability, enhance brand perception, and improve customer acquisition, cross-selling and retention,” Silverman explains.

This comes down to giving employees familiar tools they use every day. “With Microsoft-based customer and product analytics solutions, you can capitalise on internal and external data to gain a complete end-to-end view of the customer,” adds Silverman.

Insurers are turning to new technologies like the Cortana Analytics Suite (CAS) – a fully managed big data and advanced analytics suite – to give employees the insights they need.

European property and casualty insurance company If P&C Insurance is doing just that. It has recently completed a pilot project using CAS, with a focus on Azure Machine Learning, to handle different aspects of predictive modelling.

Use cases included predicting churn – seeing the likelihood of whether or not a customer will cancel the policy in a 40-day window surrounding their renewal date – and predicting upsell opportunities – looking into the probability of success of a potential upsell communication. In all areas evaluated, the performance of the CAS solution met or exceeded If P&C’s expectations.

Looking ahead, insurance carriers are beginning to explore how they can use bots to bring more value and efficiency to their processes too. “In combination with Azure Machine Learning, they can be used to gain a 360-degree view of the customer, uncover new insights and improve process efficiencies,” Silverman says. “In all, our end-to-end analytics platform provides insurers with the ability to gain real-time insight into risk exposure, increase loyalty and revenue with customer and product analytics, drive scale, agility and improved economics by transferring workloads to the cloud, all while growing premiums and reducing customer churn.” 

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