The use of predictive analytics has grown in selected pockets of the U.S. life insurance industry in recent years. But the latest survey from Willis Towers Watson shows that growing competitive pressures and changing customer expectations, in particular, are raising the stakes and building momentum for future investment.
Life insurers recognize they need to invest in predictive analytics to address earnings and profitability pressures, and the survey suggests those who do will be well positioned to transform the core functions of their business.
The recently released Willis Towers Watson Life Insurance Predictive Analytics Survey found that over two-thirds of life insurers have reduced underwriting expenses through predictive analytics, while 60% have boosted their sales and profitability.
The survey also found that large carriers lead the way in predictive analytics investment, yet midsize and small insurers intend to allocate more budget to the application of data and analysis techniques over the next two years.
Respondents ranked the competitive landscape (78%) and fortifying customer relations (67%) as the top factors driving predictive analytics investment, and they expect to expand the use of it across all their core functions: pricing, underwriting, mortality risk and claim management.
“It’s no secret that life insurers face financial pressures and their traditional business model confronts a myriad of challenges,” said Kimberly Steiner, senior director, Willis Towers Watson. “Many life carriers have been slow to adjust to this reality. However, our survey results illustrate a building momentum for a solution in the form of future operational investment around predictive analytics due, in part, to growing competitive demands and changing customer expectations.”
By deploying predictive analytics, life insurers plan to enhance their customer experience in several ways, such as offering faster service (84%), more personalized experiences (71%), easier access to policy details (64%) and more mobile-friendly interactions (58%).
“Consumers are becoming more digitally dependent by the day, and many, especially Millennials, demand a digital experience,” said Steiner. “It’s really important for life insurers to innovate around data analytics in order to capitalize on improving customer engagement.”
Survey respondents said internal customer data (55%) and customer interactions (55%) are the top data sources they use to improve customer centricity. Interestingly, the use of data from wearables is expected to increase from 5% among life insurers today to 42% in five years.
“More products are incentivizing healthier lifestyles, wellbeing and condition prevention, so it’s understandable that life insurers are among those most interested in wearables,” said Steiner.
But challenges in optimizing predictive analytics do exist. Merely 13% of respondents say their predictive models are understood by those outside the data science and actuarial teams. In addition, many carriers’ in-house IT facilities are stretched by large volumes of data, which require greater processing power to handle associated analysis.
According to the survey, life insurers are exploring solutions to address this, such as moving to cloud-based environments and Hadoop, a framework for managing and using big data.
“The findings demonstrate that while some insurers are making progress with their predictive analytics capabilities, most carriers still have work to do,” Steiner said. “It’s imperative for carriers to help stakeholders across their business—underwriters, claims and customer services teams, and marketers—to understand that enhanced predictive models will shape their competitive future and transform them into more efficient organizations.”
Willis Towers Watson also created a detailed infographic featuring the survey’s key findings, shown below and available for download at this link.
