Praedicat, a risk analytics company for casualty insurers and global industrial firms, has announced the appointment of Grant Dewar as Vice President (VP), Global Industrials.
Grant’s previous roles include four years as Chief Operating Officer (COO) for the EMEA Insurance Group at FIS, where he was responsible for driving growth in sales, revenues and operational profit margins.
He also managed large multi-cultural insurance and financial services teams, before which he spent three years at Willis Towers Watson as an SVP, Sales Europe.
In his new role, Dewar will be based in London and report to Praedicat’s Vice President and Head of Sales, Charles Clarke.
His focus will be on bringing Praedicat’s products and expertise to the industrials market on a global basis, working with organisations that manufacture and distribute products such as chemicals, pharmaceuticals and Consumer Packaged Goods (CPG).
This sector is a key market for Praedicat as it represents the start point of the value chain for product risks, from production through to risk management and the purchase of insurance.
“We are delighted that Grant has agreed to join Praedicat, where his extensive knowledge of the insurance sector and his experience in delivering global business transformation will support our efforts to drive growth in the business,” said Clarke. “Praedicat will benefit from his expertise in developing C-level client and partner relationships.”
Grant also commented: “This is an exciting opportunity to join a dynamic company at the forefront of predictive modelling and risk management for industrial clients.”
“Praedicat is helping industrials across all areas of their business, not just with their product stewardship requirements,” he continued.
“Environmental health, sustainability, due diligence on potential acquisitions, risk management, as well as safeguarding their own employees, are all areas that concern this sector, to which Praedicat has responded by developing exceptional products.”
Praedicat uses a combination of Natural Language Processing and Machine Learning to read the global corpus of peer-reviewed scientific literature, currently around 31 million scientific papers.
Its algorithms look for evidence of a causal link between a product or chemical, and a harm, for example asbestos and mesothelioma.
Praedicat then mines scientific papers, and extracts metadata to develop a computational weight of evidence assessment and then builds a probabilistic casualty catastrophe model for latent liability risks.