According to Willis Towers Watson, 54% of insurers utilize predictive models to collect data regarding their customers and their businesses. That figure is expected to grow significantly over the next year, as the inherent value of predictive analytics in insurance is showing itself in myriad applications.
Predictive analytics tools can now collect data from a variety of sources – both internal and external – to better understand and predict the behavior of insureds. Property and casualty insurance companies are collecting data from telematics, agent interactions, customer interactions, smart homes, and even social media to better understand and manage their relationships, claims, and underwriting.
Using the plethora of data now available, here are six ways predictive analytics in P&C insurance will change the game in 2019.
Pricing & Risk Selection
This isn’t exactly a new use for predictive analytics in insurance, but pricing and risk selection will see improvement thanks to better data insights in 2019. Given the increased variety and sophistication of data sources, information collected by insurers will be more actionable.
Why do these data sets help predictive analytics improve pricing and risk selection? Because they are largely comprised of firsthand information. Data and feedback collected from social media, smart devices, and interactions between claims specialists and customers is straight from the source. Data that isn’t harvested through outside channels (such as the typical demographic material used in the past, like criminal records, credit history, etc.) is more direct, and can provide valuable insights for P&C insurers.
Identifying Customers at Risk of Cancellation
Predictive analytics in P&C insurance is going to help carriers identify many customers who require unique attention – for example, those likely to cancel or lower coverage. More advanced data insights will help insurers identify customers who may be unhappy with their coverage – or their carrier.
Having this knowledge in hand will put carriers ahead of the game and allow them to reach out and provide personalized attention to alleviate potential issues. Without predictive analytics, insurers could miss credible warning signs and lose valuable time that could be used to remedy any issues.
Identifying Risk of Fraud
P&C insurance companies are always battling various instances of fraud, and oftentimes aren’t as successful as would be ideal. The Coalition of Insurance Fraud estimates that $80 billion is lost annually from fraudulent claims in the United States alone.
Using predictive analytics, carriers can identify and prevent potential fraud before it happens, or to retroactively pursue corrective measures. Many insurers turn to social media for signs of fraudulent behavior, oftentimes using data gathered after a claim is settled to monitor insureds’ online activity for red flags.
Customers are always looking for fast, personalized service. In the P&C insurance industry, that can sometimes present a challenge. But with good predictive analytics systems, carriers will be able to prioritize certain claims to save time, money, and resources – not to mention retaining business and customer satisfaction.
Predictive analytics tools can anticipate an insured’s needs, alleviating their concerns and improving their relationship with their carrier. It can also contribute to tighter management of budgets by employing forecasted data regarding claims, giving insurers a strategic advantage.
Identifying Outlier Claims
Predicative analytics in insurance can help identify claims that unexpectedly become high-cost losses — often referred to as outlier claims. With proper analytics tools, P&C insurers can review previous claims for similarities – and send alerts to claims specialists – automatically. Advanced notice of potential losses or related complications can help insurers cut down on these outlier claims.
Predictive analytics for outlier claims doesn’t have to come into play only after a claim has been filed, either; insurance companies can also use lessons learned from outlier claim data preemptively to create plans for handling similar claims in the future.
Insurance companies are always looking for ways to get ahead of their competitors, and there’s no better way to do that than by staying on top of industry trends. Just as using predictive analytics was once a new trend for carriers, predictive analytics tools themselves can help carriers plan new products, customer experiences, and technology solutions to position themselves at the forefront of emerging possibilities.
Going forward, more and more insurers will use predictive analytics to help forecast events and gain actionable insights into all aspects of their businesses. Doing so provides a competitive advantage that saves time, money, and resources, while helping carriers more effectively plan for a future defined by change. After all, data is only a strategic asset when you can actually put it to work.