Technology can faciliate enhanced risk management. Sensors to detect EOW can be nstalled in areas susceptible to water damage and send an alert of excess moisture and water before it becomes a major issue. Some commercial properties also make use of ‘occupancy sensors’ which are used to activate lighting within a building when occupancy is detected. This can help in deterring or alerting of intruders, in turn reducing the risk of theft, fire and vandalism. 

Condition monitoring sensors are also being used for real-time monitoring of the health and performance of industrial equipment. These compact wireless sensors work by collecting data on metrics such as vibration and temperature to help predict machine failure. Through use of AI the data is analysed and used to present an overview of performance and any degradation over time. 

AI and machine learning are touted to play a growing role in managing risk. One example is the area of lone working where individuals may be working at height or in physically challenging circumstances. Food processing firm Alpro has successfully used machine learning to detect falls so that surveyors can ensure that any accident is reported if they are injured while working alone.²

Traditionally insurance has been associated with compensation. However, insurers and brokers are increasingly embracing a role as proactive risk managers, equipping their customers with information to help reduce risk in the first place. Whilst the nature of risk will continually evolve, the basic principles of risk management remain fairly constant.

These include having effective measures and plans in place for risk identification, analysis and control. This, combined with a robust business continuity plan and the right insurance cover, can provide peace of mind that an incident should not bring business entirely to a halt.