P&C insurers must unlock big data to capitalise on predictive models

Two-thirds of US property/casualty insurers currently use predictive models for underwriting and risk selection, an increase of over 10 percentage points compared to last year, according to a survey by Willis Towers Watson

Results from the company’s 2016 Predictive Modeling Survey found that big data, notably from vehicle telematics and the Internet of Things (IoT), are opening up many new potential opportunities for carriers.

While personal lines carriers continue to take the lead on predictive modeling, more commercial lines intend to build their capabilities within the next two years, e.g., claim triage (15 percent use predictive models now vs. 66 percent expected to in two years); fraud potential (14 percent vs. 55 percent); litigation potential (10 percent vs. 50 percent) and case reserving (8 percent vs. 48 percent).

“The survey findings suggest that these could become increasingly important areas for performance differentiation, building on what many commercial lines carriers believe models have already helped achieve,” said JJ Ihrke, senior consultant and actuary, Willis Towers Watson.

In order to sustain predictive model use, insurers must unlock the value of data, according to the survey’s findings. Insurers say over the next two years big data will help them with pricing, underwriting and risk selection (92 percent), better management decisions (84 percent), and loss control and claim management (76 percent).

“This is contingent upon investments insurers are willing to make, as the degree to which carriers characterize themselves as data-driven has significant bearing on how aggressive they are in employing analytics,” said Ihrke.

For the top-growing big data sources that insurers are already embracing, they believe internal claim information (41 percent) and internal customer information (27 percent) are the most useful.

Big data, from vehicle telematics and the IoT, are opening up many new potential avenues for improvement, as personal auto carriers expect to get much more driving data from connected cars (100 percent), apps (75 percent) and telecoms (63 percent) in the next five years.

“Unlocking the value of data — both emerging data sources and information that can frequently be tied up in a web of company legacy systems — represents the most likely near-term source of enhanced pricing accuracy, product differentiation and business outperformance opportunities for both personal and commercial lines carriers,” said Ihrke.

Insurers will need to solve internal roadblocks to fully expose data’s potential. Respondents say people are the biggest challenge to generating business value from data, as insurance companies often lack employees with the right training and skills (51 percent). Other concerns include capturing the right data (37 percent), cost considerations and funding (35 percent) and data quality and reliability (33 percent). To address these challenges, insurers plan to upskill existing employees (60 percent), hire more employees with the right skills (51 percent), ask third parties to advise (46 percent) and outsource (21 percent).

“We’re nearing the point where market momentum will accelerate, as value-building big data, and diverse and growing analytics techniques take hold. Insurers that want greater control over their destinies will marry flexible IT frameworks and partner with the analytics techniques and skills necessary to effectively harvest data,” said Ihrke.

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