The evolution of predictive analytics in insurance

However, integrating predictive analytics with business processes is not an entirely straightforward process. Prior to any modelling activities, data science teams, business teams and IT teams have to understand fully the business needs and related technology needed to deploy the models into their core systems. Otherwise, problems will arise when insurers move to operationalize their analytics and the expected business value is often never realised. Moreover, even artificial intelligence deep-learning techniques – that is, artificially intelligent systems capable of learning unsupervised by looking at unstructured data – may struggle to understand patterns they have never seen before. Depending on the insurer's needs, and the nature of the data they are using (structured or unstructured) variable amounts of data are required to create models.