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IAG is using artificial intelligence to predict whether a motor vehicle is a total loss after a car accident, improving customer experience by reducing insurance claims processing times from over three weeks to just a few days.

This means that customers of IAG brands, which include NRMA Insurance, SGIC and SGIO, involved in a motor total loss accident will get a claims outcome faster and back on the road in a new car sooner.

The technology, which combines artificial intelligence with business process automation, has helped IAG achieve up to a two and a half week reduction in claims times for customers when their car has been written off in an accident, by removing the need for a vehicle to be towed to a repairer prior to being assessed as a total loss.

IAG Director of Analytics Hannah Sakai said predictive total loss, which was developed in-house, was created to help reduce the emotional impact of a car accident by providing customers with more clarity and certainty sooner in the claims experience.

“A car accident can be a traumatic and challenging time for our customers, so we turned to artificial intelligence to help improve this experience.

“Our predictive total loss solution leverages machine learning to detect a potential total loss with more than 90% accuracy, using information provided by the customer when they make a claim on the phone with a consultant or online.

“The customer is notified of the potential total loss outcome via text message the following day, providing transparency upfront on the process and providing answers to commonly asked questions. We’ve seen a significant uplift in customer advocacy as measured through total loss customer experience surveys.

“The predictive total loss model is one of many AI applications being developed by data scientists in IAG’s AI Centre of Excellence.  Using an internal team allows us to leverage our unique business knowledge to tailor the experience to our customers”, Sakai said.

Application of AI ethics framework

Prior to deployment, Predictive Total Loss was evaluated using IAG’s established AI ethics framework and the Australian Government’s voluntary AI ethics principles to identify potential issues or risks prior to go-live, including:

  • Human, social and environmental wellbeing: making sure the objective of the project was to benefit IAG’s customers, with no other conflicting objectives, and clearly documenting this to assist with ongoing monitoring.
  • Reliability and safety: experimentation to verify that customers had a positive experience and setting conservative thresholds for modelling to help reduce the likelihood of wrongly predicted total losses.
  • Fairness: Careful consideration of the potential benefits and harms of the system, including the distribution of benefits and harms across the population. 

The IAG AI Centre of Excellence plans to refine the model using customer photos of the vehicle damage and extending the methodology to predict motor claim liability to help automatically validate claims at the time of customer lodgement. 

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