Rapid advancement in Artificial Intelligence (AI) technologies over the next decade will allow insurers to capitalise on the capture of vast swathes of digitised data from diverse sources, Finity says.

Gone are the days of the data only being stored in database tables. More and more data organisations are now leveraging “natural language” data: documents, emails, transcribed phone conversations, and photos and videos.

The amount of data stored in the digital universe globally has been estimated at 44 zettabytes – around 40 times the number of stars in the observable universe, or 4.4 followed by 22 zeroes.

“As insurance professionals we know the importance and power of data and this trend isn’t going to slow,” Finity Principal Marcello Negro said. “As you look around at the growing volume and diversity of data you are collecting, how will you use the recent advances in AI technology to solve your clients' problems and grow your business?”

Businesses that thrive will be those insurers to embrace and utilise AI to create new products, streamline processes, lower costs and exceed customer expectations, he says.

Finity’s AI team has developed a software product called The Artificial Immune System (AIS) which can classify insurance data appropriately, identifying issues like insurance fraud, claims leakage, and abnormal customer behaviour.

The rise in three very different types of data – tabular, language and image – pose different challenges to insurers in terms of extracting valuable insights, and Finity says three distinct sub-fields of AI have grown in response.

Predictive modelling: Anomaly detection is an AI sub-field that Finity has been increasingly making use of to help clients with claims fraud detection, trying to find patterns in data and predicting the likelihood of a ‘data point’ – claims, quote, policy, customer etc – being unusual.

Natural language processing: Finity says more and more language data being recorded in insurance in phone calls, chatbot history, emails, and documents of all kinds and techniques to process language data are becoming critical to the insurance toolkit in order to understand vast swathes of text data, to find and utilise patterns to help better understand and respond to customers.

Computer vison: This ‘technology of tomorrow’ covers techniques and approaches for dealing with image data. In insurance, automatic claims assessment for vehicle damage has come a long way in a few years but is still far from perfect, Finity says, and further improvement is likely in the next five years. As more ‘training data’ becomes available, the accuracy of these algorithms will improve.

Many insurers are using machine learning techniques and are making “encouraging strides” regarding the storage and organisation of data.

“We have seen a move away from storing data in legacy systems and into more flexible ‘data warehouses’ that allow for easier extracting, transforming and loading of data for reporting and analytics, instead of trying to work with existing monoliths,” Sydney-based Mr Negro said.