Customized products and services have been proven to bolster customer engagement, and insurers are leveraging advanced analytics to update their portfolios. Product and service personalization helps generate new revenue streams and retain current customers. In fact, 72.1% of insurance executives interviewed for the WIR 2017 said that building individual customer profiles can generate new revenue streams, and 90% said targeted products and services could improve customer engagement.

Are insurers leaving money on the table?

Moreover, the current World Insurance Report (WIR) 2018, found that a substantial number of customers were ready to proactively receive personalized services from their insurers. However, there is a gap between customers’ willingness to accept such offerings and their perception of their insurers’ proactivity. The result? Insurers may not be targeting their offerings through the appropriate channels, but advanced analytics can help to bridge this gap and meet customer expectations.
Today’s consumers spend more and more time on digital platforms, which helps companies leverage their digital footprint to customize products and services. As this involves a massive volume of data, advanced analytics techniques can help insurers with critical insights to accomplish several strategic goals.

Social media, connected devices, and online product inquiries provide insurers with real-time information on customer behavior and preferences. Real-time data can also help insurers with risk identification and prevention, as well as in providing timely feedback to customers.

Future-focused insurers are prioritizing digital, and data and analytics capabilities that align with their strategic priorities, so they can design and implement new business models and evolve to meet ever-increasing customer expectations.

For example, Dutch self-service, internet insurance company InShared uses a data-driven customer-profiling tool that company executives say can decide, with 90% accuracy, the probability of a visitor becoming a customer.[1]

In underwriting and pricing, a data-driven approach can help to create granular, information-rich customer profiles. A competitive advantage in risk selection and pricing is contingent on large volumes of data, and with the exponential growth in structured and unstructured data, advanced analytics tools and methods can help insurers develop more precise pricing for specific risks.

Predict profitability

Furthermore, with advanced analytics, insurers who sell products online can create a dependable customer lifetime value model that can assess the future risk and purchasing behavior of a customer. Such predictions increase the ability to select profitable customer profiles with the most significant chance of reducing loss ratios and improving revenues. It’s no surprise that 42.7% of P&C insurers interviewed for the WIR 2018 said that they had deployed predictive analytics, with 25.3% in the pilot phase.

For instance, London-based Willis Towers Watson, a multinational risk management insurance brokerage, uses predictive analytics software to build complex customer profiles that improve pricing accuracy and quicker decision-making.[2]

The growing popularity of smartphones, IoT, and other digital devices gives insurers access to lifestyle data – such as drivers’ sleeping patterns and customers’ general driving behavior, etc. – for granular-level profiling and customized pricing, which supports the development of new products.

Today’s insurers are shifting focus from risk mitigation to risk prevention. They are seeking solutions to anticipate events and prevent losses, such as improving the health and wellness of customers, perfecting driving behavior, and ensuring home safety by employing connected devices. This shift in focus also paves the way for more customer touchpoints, which generally have been low in the insurance industry.

Getting a leg up on new, emerging risks

For new and emerging risks – that have little or no historical data – the ability to predict future events and take necessary preventive actions is especially useful. Predictive analysis is critical in tackling market changes and the new risks that can emerge from an innovation. Accordingly, 42.7% of P&C insurers surveyed for WIR 2018 said they had deployed emerging risk modeling, while 24% said they were in the testing phase.

In the current technology risk landscape, change monitoring is essential not only for big industry players but small and mid-sized insurers as well.
Advanced analytics can enable insurers to deliver personalized products and services in real-time, which means better customer experiences and happier customers.

What’s more, advanced analytics give P&C insurers an edge when it comes to accurate risk assessment and identification of emerging risks. There is little doubt that advanced analytics empower P&C insurers to become future-ready in a digital world.

[1] Inshared website, https://www.inshared.nl/

[2] Insurance Business Asia, “Willis Tower Watson enhances its predictive modelling software,” Paulo Taruc, October 25, 2017, https://www.insurancebusinessmag.com/asia/news/breaking-news/willis-towers-watson-enhances-its-predictive-modelling-software-82884.aspx