Peter Tilocca

ANZ OnePath has rebuilt its underwriting system to launch a simpler, more intuitive experience for customers applying for OneCare insurance.

Developed in partnership with the University of Technology Sydney’s (UTS) Advanced
Analytics Institute, OnePath’s new underwriting system has taken ten years of OnePath data and used Artificial Intelligence (AI), data science and data analytics to bring the future to underwriting.

The result is a more streamlined personal statement that takes less time to complete
provides customers with more certainty and brings a new era of plain speaking to insurance.

Users can now disclose medical information in a manner that is more aligned to the way
they think about their health, raising relevant questions along the way.

Key features of the new underwriting system:

• Up to 30% faster completion time of personal statements
• Higher straight-through processing and acceptance rates, adding momentum to the 52.9% acceptance rate for clients under age-50 on all lump sum benefits
• An expected 2,300 per annum reduction in the underwriting referral triggers
• The addition of 3,000 medical conditions, reducing the need to enter free-from text in the ‘any other’ category which added delay and uncertainty to the process.
• 1,000 medical aliases such as ‘tennis elbow’ to describe medical conditions more aligned to everyday language.
• Improved tele-interviewing and client URL experiences
• Ability to search for conditions and to jump to different areas of the personal statement to easily adapt with client’s conversation.

ANZ’s Chief of Underwriting Peter Tilocca, said: “ANZ OnePath has taken underwriting innovation in a new direction, taking its own data and harnessing new tools such as AI and data analytics to make insurance a more intuitive and engaging experience.”

UTS Advanced Analytics Institute Professor, Dr Guandong Xu confirmed the power and value of using AI to transform underwriting.

“Using AI to simulate people’s decision making process, we have shown how AI has used big data, natural language processing and predictive modelling, to revolutionise a huge process such as underwriting.”

In September, the underwriting system won the Best Industry Application of Data Analytics and the Best Industry Application of Artificial Intelligence at the Data and AI Innovation Awards held in Sydney.

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ANZ addresses “cumbersome” underwriting process for tradies.

ANZ has built a predictive underwriting capability to make the insurance underwriting process faster, accurate and easier for tradespeople.

Based on a successful pilot program in Victoria, licensed tradespeople such as plumbers, carpenters, electricians and builders aged between 20 and 40 years of age can now access an underwriting program that uses big data and artificial intelligence to identify factors common to this group.

Working with the University of Technology, Sydney Advanced Analytics Institute, data from 10 years of OneCare underwriting and claims decisions were analysed to achieve the accurate three-dimensional market segment profile.

According to ANZ Wealth chief underwriter Peter Tilocca, this is tremendous step forward for the insurance industry which has been locked into the same underwriting process for the past two decades.

“The underwriting process today is at best described as cumbersome, and in a world where the consumer now expects instant gratification, an underwriting time frame average of 20 to 30 days will no longer be acceptable.”

“By working backwards from the claims history and seeking out commonalities in this data set, we have been able to reduce underwriting personal statements while maintaining the integrity of our insurance portfolio,” Mr Tilocca said.

In practice, this has seen the number of medical questions in the underwriting process for the full OneCare product suite reduced to eight. It is anticipated this will have a positive effect on the completion rate of insurance applications.

“Currently 20 per cent of life insurance applications are not completed due to a requirement for more data or incomplete information provided,” Mr Tilocca said. “This has a detrimental effect not only on Australia’s underinsurance problem, but also on the customer experience and the perception of insurers.”

This breakthrough in predictive underwriting complements the launch of Pre-Assessment Wizard which helps advisers with loadings and exclusions for pre-existing medical conditions in real-time. Bringing these two initiatives together will further streamline the underwriting process.

“We’re excited about the opportunities big data and artificial intelligence are bringing to the underwriting process, giving advisers and their customers a better experience,” Mr Tilocca said. “We will continue to look for other opportunities to transform the underwriting process.”

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