Client centric analytics

By using advanced data analytics including quantitative data analysis, text mining and heat mapping, we are beginning to identify patterns in clients’ claims data and compare them with clients’ industry peers through our vast storehouse of industry claims data. This means we can pinpoint loss drivers, and create powerful benchmark comparisons that are uncovering previously unseen opportunities to help clients reduce risk. .


Using client centric analytics, a detailed analysis of a major retailer’s claims forms revealed correlation between severe falls on flat surfaces with the trolleys used by sales assistants. Based on this, the client overhauled its trolley equipment to reduce accidents. In the hospitality sector, analysis of 5 years of a client’s data showed a risk concentration in the housekeeping department. Text mining uncovered high frequency of injuries around making beds and changing sheets. Armed with this data, the client’s risk management team is shaping future room designs for a safer workspace for housekeepers.