![]() We believe that disruption will be more radical in personal lines as entire business models (and its underwriting processes) could be uprooted. Arming underwriters and actuaries with such data will enable both improved risk selection and more nuanced product design. This gives much more accurate results for perils such as flood. Risk selection will be much more precise, as drones, satellite imagery and other high-resolution mapping techniques are deployed to better appraise risk down to granular location level. This is due to the inherent complexities and non-homogenous nature of the risk landscape within the commercial realm, where increasingly intricate supply chains and interdependencies are chronically under-appreciated, which was evident during COVID-19 pandemic.ĭisruptions are likely to be gradual. ![]() It is unlikely for models to completely replace expert judgements. Underwriting will continue to become more quantitative and statistical, But the timing and extent of tech driven disruption is not uniform across the general insurance spectrum. We believe that the trends seen to date will continue. Looking ahead: the anticipated timing and extent of disruption ![]() Underwriters also consider emerging factors such as increasing use of telematics (and other ’big data’), and other technologies that will change the insurance market, such as driverless cars. Much time is spend considering the detail of policy wordings and understanding how products compare to competitors. Underwriting is therefore significantly more efficient and the role now marries actuarial, portfolio and product responsibilities. This is caused be availability of large volumes of data and growing prominence of digital distribution channels such as comparison websites, online direct to consumer sales/service and claim journeys. General insurance personal lines of insurance, such as travel and motor, the role of the underwriter has seen the largest disruption. This not only encompasses technical risks, but the commercial realities of the insurance market. These only represent decision-support tools – in many cases underwriters still applied large amounts of judgement into the ‘art’ into the risk selection process, particularly in large, complex risks and special insurance. These techniques include event probability curves, accumulation limits and hazard rating. ![]() Over time, more advanced techniques were adopted. Underwriters were subject matter experts and had to supplement scarce historical data with large amounts of personal intuition and experience. Underwriters have long been essential in traditional insurance contracts, dating back to the 17th century ‘Lloyd’s of London’s’ marine market.
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