Willis Towers Watson is partnering with data analytics firm, Polecat Intelligence, to develop insurance solutions to increasingly complex and interconnected challenges across life sciences, reputational risk, product recall risk, and D&O using Polecat’s artificial intelligence and machine learning capabilities.
Airmic CEO John Ludlow said the partnership signalled “a new generation” of risk management solutions in the AI field.
“For organisations of all types, there is an increasing recognition by executives and boards of reputation as one of the greatest strategic risks, and solutions like this will be critical to protecting and maintaining intangible asset value,” he explained.
Garret Gaughan, head of global markets P/C hub, Willis Towers Watson, added:
“Information and the way that people access it to develop their perception of an organisation or situation has changed radically, for both the private and public sector. Organisations find themselves in a volatile and dangerous reputational environment. The partnership with Polecat enables Willis Towers Watson to offer Clients real-time insight to public opinion through analysis of social media. By working with a partner able to analyse unstructured data in real time we are able to design and implement risk mitigation mechanisms for our Clients.”
James Lawn, CEO of Polecat, said, “Polecat exists to provide foresight for Corporate Boards and Executive Leadership teams to make better decisions on emerging risks and opportunities. Our partnership with Willis Towers Watson is ground-breaking bringing world-class risk transfer together with market-leading artificial intelligence and machine learning to provide real-time risk insights from the world of unstructured data. Corporate Boards and Executive Leadership teams are looking for insurance and technology that enables them to manage and mitigate their emerging risks that impact their business landscape, the global economy and the world around us. In partnership with Willis Towers Watson and Polecat, we can do this.”
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