UTS Advanced Analytics Institute (AAI) is collaborating with ANZ-OnePath, one of Australia’s leading providers of wealth, insurance and advice solutions, to harness advances in machine learning, data science and predictive analytics to do things differently…Machine learning - algorithms that give computers the ability to analyse business processes - and big data are discovering new opportunities and insights for improved processes and better service, and UTS and ANZ-OnePath together are exploring opportunities for artificial intelligence (AI) - an algorithm with human decision-making capability - and data science - the extraction of knowledge and insight from data - to transform the insurance application process.
They are combining their professional expertise in analytics, and in insurance underwriting, to examine ways to significantly reduce processing times, improve quality and offer cover to more Australians. The AAI analytics experts will examine the huge amounts of data that is collected from customer questionnaires to identify ways to reduce a time-consuming manual process which can leave customers waiting weeks for approvals, or even walking away, uninsured, due to frustrating delays.
The traditional underwriting process asks customers up to a 100 possible questions; these are standardised and not personalised or tailored to their particular situations. The underwriter then needs to collate them manually to determine an application – or even seek further specific information, such as medical reports, adding extra stages to the process.
ANZ-OnePath wants to simplify this process, make it easier and more accessible, and improve the customer experience over the whole life cycle of an application for cover.
And artificial intelligence and machine learning can be applied to do just that.
This new partnership has come about in recognition of AAI’s capability in big data, data sciences and data analytics, and its experience in the financial technology sector. This collaboration is the latest by UTS AAi in developing innovative analytics solutions for the financial technology sector.
“We aim to be the leading research group in applying data analytics and AI in FinTech across various wealth sectors such as insurance, superannuation and investment portfolios,” says Associate Professor Guandong Xu, Leader of AAi’s Data Science and Machine Intelligence Lab.
“We have developed a four step methodology for working closely with our partners to build domain knowledge and help them to be more agile and develop quick outcomes.”
This 4D methodology – Discovery, Design, Delivery, Deployment – is used by a team of @20 to understand the business, the challenges it faces, and, on a case by case basis, map specific problems to develop a data-driven concept design.
ANZ-OnePath chief underwriter Peter Tilocca said using a data-driven solution is a clear opportunity to create a more personalised, efficient service with improved quality assurance for customers applying for insurance.
“We began with some key questions:
• Can the questions we ask of applicants be tailored, personalised and reduced?
• Could we use AI and data science to develop an automatic risk engine to quickly and consistently identify if an insurance application is standard, or has an exclusion or loading applied?
• Could we use AI and data science to improve quality assurance processes internally for ANZ-One Path?
“The answer to all is yes and we now see how AI can develop a more reliable application and assessment process and also provide our advisers with a differentiated service that supports them in building trusted relationships with their clients,” he adds.
With ANZ-OnePath, Associate Professor Xu and his team used data science to explore the historical data across the insurance lifecycle process and combined this with AI to develop an Automated Underwriting Risk Engine.
“An intelligent underwriting model will harness machine learning to provide opportunity for insurers to develop more efficient and reliable assessment processes. We will involve client behaviour modelling, text mining and natural language programming, along with social and predictive analytics that can add value in the insurance sector,” he says.
“We discovered that many questions do not provide useful insight to determine if an application should be accepted, have an exclusion, loading or be declined. Data science applied to intelligent underwriting shows that just use 10% of questions asked can achieve the same underwriting outcomes as using all the questions.”
The virtual underwriter will determine if a loading or exclusion needs to be applied and will only processes applications that have been accepted by the customer for underwriter confirmation. It will save time, and saves ANZ-One Path time and increase operational efficiencies and product quality.
The automated system’s quality assurance structure can also evaluate all decisions (Virtual and Human) and generate quality assurance reports for managers to review. The unique advantage of AI is in its adaptive and self-learning capability, absorbing new data and improving over time using aggregated data and external knowledge.
For ANZ-OnePath this is the future of insurance and underwriting….
“We want to be a world leader in AI underwriting, and Australia’s preferred wealth and life insurance company, delivering a more tailored, customised and improved on-line digital experience for a wider base throughout Australia,” says Mr Tilocca.
UTS ANZ stand - G40: Presentations are scheduled daily for 10.45am, 12.15pm and 1.45pm each day for 30-45minutes. 12.15pm to be a demo session.