Article | “How Predictive Analytics is Transforming Risk Management” | Strategic Risk

But how can corporates and risk managers make better use of data in risk management?.Huge volumes of data make it challenging for companies to extrapolate value and use predictive analytics to their advantage..According to Airmic, many risk managers are not making the most of the information surge..Many have been using the same information sources and statistical techniques for several years..“Risk managers are being told by senior executives and the board that the company requires better data on their risks..The company requires better insurance data for that,” says Georgina Wainwright, Research and Development Manager at Airmic..“It is a huge challenge for risk managers..They are conscious of the prolific nature of technology and the excessive volume of data being pooled together, which is not being collected effectively.” The data journey So how can data be better collected, or more specifically, how can corporates extract valuable analysis to aid risk decisions?.Data analytics moves through four stages from descriptive, where the data captured describes what’s happened to diagnostic analytics, which provides answers as to why something has happened and begin identifying trends..Predictive analytics is where enough data exists to identify where future losses will occur and when..This helps risk managers to identify red flags or incidents that are likely to culminate in a significant loss or a major insurance claim..“People are wanting to move into the [predictive analytics] stage, where they can predict what’s going to happen and how big or severe [the risk] is going to be,” says Wainwright.. More details

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