Insurance companies that don’t embrace the use of intelligent “learning” computer algorithms to speed up their claims process will be left behind, says a leading industry analysis firm.
KPMG’s latest overview of the Australian industry has identified “machine learning” as a game-changer for the industry.
Machine learning refers to a set of algorithms that predict current or future outcomes based on historical data. It is already in use by banks to identify irregular transaction activity.
“The big question is why insurers have been so slow to start collaborating with machines,” KPMG states.
“A shift from human resources to to automation should deliver significant cost savings.
“KPMG has worked with a global insurer to develop an algorithm focused on efficient claims processing. The time to process claims was reduced from months to minutes – and the machines were not just faster, they were also more accurate and reliable than the traditional human-led approach.”
Identifying machine learning as one of the key risks and opportunities facing the sector, KPMG says the technology could give early-adopting insurers a competitive edge, if customers are willing to pay a premium for a product that guarantees frictionless claims experiences.
Overall, KPMG’s analysis of the Australian insurance sector found challenging conditions, with competitive pressures increasing even as gross written premium stays flat at $32 billion.
Thanks in large part to catastrophes such as Cyclone Marcia, storms and hailstorms in Sydney and south-east Queensland, and the South Australian bushfires, profit took a major hit, dropping from $4.8 billion last year to $3.7 billion.
“While some insurers have been able to grow their books via merger or acquisition activity, organic growth in the industry has proved difficult to attain,” KPMG states.
“Nevertheless, there may be opportunities on the horizon for insurers to introduce new products or distribution channels.”
To read the full report, click here.