Artificial Intelligence (AI) and machine learning is a growing topic within both the insurance and reinsurance industry, with more companies using the technology to manage manual, low complexity workflows and dramatically increase operational efficiency.
The technology also allows the ability to predict with greater accuracy losses and the behaviour of customers, with some insurers even stating that it gives them more opportunities to influence behaviour and even prevent claims from happening.
With all this being well, this technology does come with some risks, as Neil Chapman, Senior Director, Insurance Consultancy, Technology & Global Leadership, Pricing, Product, Claims & Underwriting, WTW, addresses in a new report.
Chapman warns that this new way of doing things could potentially go on to create “unfairness and even undermine the risk-pooling model that is fundamental to the industry” and that insurers need to be sensitive to ensure that they develop and use this technology “ethically and manage their customers’ data with watertight controls.”
He highlights that it is crucial to remember that AI does not reason, as algorithms have no ethics because they are just simply algorithms.
He says that instead of asking how ethical a firm’s AI is, “we should be asking how far ethics is taken into account by the people who design the AI, feed it data and put it to use making decisions.”
Furthermore, with machine learning continuing to generate value across the industry, Chapman states that the value of applying a clear ethical framework should be considered as an “essential component to successful adoption and value extraction.”
He highlights that key components in WTW’s own ethical framework, include accountability and fairness – understanding, measuring and the mitigation of bias – of the models and systems in how they operate in practice, as well as understanding how they are built, and technical excellence to ensure models and systems are reliable and safe providing privacy and security by design.
Chapman concludes by noting that there is potential in AI within the industry, but for it to ultimately have the best impact, “it needs to have public trust.”
