The majority of North American life insurers deploying predictive analytics have experienced productivity gains as a result, research from Willis Towers Watson (WLTW) has uncovered.
In a report published last week, WLTW said that over two-thirds of life insurers have reduced underwriting expenses, while three-fifths have boosted their sales and profitability.
Offering faster services, more personalised experiences, easier access to policy details and more mobile-friendly interactions are some of the benefits cited by insurers.
It was also found that the proportion of North American life insurers using data from wearable devices is expected to increase from 5% today to 42% in five years.
"It's no secret that life insurers face financial pressures, and their traditional business model confronts a myriad of challenges," WLTW senior director, Kimberly Steiner, said.
"Our results illustrate a building momentum for future operational investment around predictive analytics due to growing competitive demands and changing customer expectations."
Predictive analytics are likely to be used more widely across pricing, underwriting, claims and mortality risk as insurers increasingly look to boost customer relations.
However, just 13% believe that predictive models are understood by staff outside of their data science and actuarial teams.
Moreover, it was found that many in-house IT facilities are stretched by large volumes of data that require greater processing power to handle the associated analysis.
In response, life insurers are exploring solutions to address this, such as moving to cloud-based environments and Hadoop, which is 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 continued.
"It's imperative for carriers to help stakeholders across their business to understand that enhanced predictive models will shape their competitive future and transform them into more efficient organisations."
