“Virtually any ‘digital trail’ left by consumers can be tracked, and the extracted data can potentially be used for contract underwriting,” Dr Bednarz said. “Artificial intelligence and machine learning tools allow valuable inferences to be drawn regarding risk prediction from this data.”
“The inferences that can be drawn from the data are very broad and many of us would find them uncomfortable,” Dr Bednarz said. “Models, such as machine learning algorithms, have been shown to (correctly!) guess a person’s sexual orientation from pictures of their face, or possible depression from their posts on Twitter. Think of everything that can be discovered about us from our grocery history alone: our diet, our household size, maybe even our health status or social background. It becomes even more extensive and perhaps more specific if we think about the information revealed by our social media posts, our photos, our likes or our membership in various groups.
Dr Bednarz also points to his additional research, conducted with Professor Kimberlee Weatherall, of the University of Sydney Law School, indicating that insurers’ access to data is becoming even easier with the new Consumer Data Right (CDR) , which already obliges banks to share consumer banking data, at their request, with another bank or another application, for example to access a new service or a new offer (possibly also insurance ). It is proposed to extend the CDR to the insurance and pensions sectors in the near future.
While consumer data rights are being heralded as empowering consumers to access new services and offers, and giving people choice, convenience and control over their data, Dr. Bednarz says that “in the handy, however, it could mean that insurance companies don’t even need to monitor you online to find out how much money you’re spending (and on what). They might just ask you to share your bank details through the CDR.