Authored by Hélène Stanway, Digital Leader at AXA XL
Data has always been a key tool for risk managers – and for their broker and underwriter partners too. We are entering now a new era for data, which could prove a game-changer for the risk management profession.
The Industrial Internet of Things, whereby interconnected sensors and devices are used to enhance manufacturing processes, is transforming the way companies work, resulting in enhanced efficiencies and also providing them with stacks of powerful data.
And the ability to harness that data, to analyse it and unlock its potential will transform the way risk managers are able to perform their jobs.
At the Federation of European Risk Management Associations’ forum in Berlin in November, I am taking part in a panel that will explore how Artificial Intelligence (AI) and data will change the practice of risk management.
I’m looking forward to hearing views from my fellow panellists and the wider room; this is a topic that we at AXA XL are excited by, and we are taking part in several proofs of concept that we believe could give powerful data insights to help risk managers, risk engineers and underwriters to improve the way risk is understood, managed and transferred.
AI and data
Artificial intelligence is becoming part of day-to-day commercial life. There are now about 1,600 AI start-ups in Europe, according to recent research.
And there are many ways in which AI is not just helping businesses to work more effectively but also to begin to manage their risks in a different way.
A concrete example is our partnership with Parsyl Inc., a supply-chain platform that helps shippers, their clients, and insurers to understand the quality of the conditions that sensitive or perishable goods are kept in.
Sensors placed alongside cargo provide insights into the context of goods throughout the supply chain. The data that these sensors provide about variables such as temperature, light, humidity and movement, enables our risk engineers to make practical risk management recommendations to avoid losses or to minimise their impact.
It is the combination of data mining, that would be practically impossible for a human to achieve, with human powers of analysis and understanding that make innovations like this such game-changers for risk management.
It is possible to imagine how this could evolve to make those goods that are currently tricky to insure much more insurable.
Take vaccines, for example. Currently, when vaccines are in transit, it is possible to insure them – up to a certain point. So sensitive are vaccines to changes in conditions, and so important is it that they not be tampered with in any way, underwriters need absolute clarity of information about how the vaccines are stored throughout their journey.
There are currently some geographies where information is, at best, patchy that it becomes difficult for underwriters to gain assurance about the quality of the vaccine when it reaches the intended recipient.
We are working on a proof of concept to try to find a solution to this problem.
Sophisticated sensors, data analysis and mining and risk engineering expertise could give risk managers and their insurers a much better understanding about what happens to vaccines as they are transported.
Not only does this have the very human benefit of getting more vaccines to those that need them, it also will reduce losses and make insuring vaccines along the entire length of their supply chain a much more viable – and affordable – proposition.
There are many other ways in which we believe that AI will empower risk managers and equip them with more usable, meaningful data.
Take for example, property risks. The use of advanced technology should enable insurance companies to provide 24/7 risk engineering and loss prevention services to customers.
Another proof of concept that we have been involved in is to test placing a “black box” in highly fire-sensitive areas of a customer’s premises.
This black box pulls data to populate a risk dashboard which gives constant updates mean that maintenance can be performed as and when it becomes apparent that it is needed – drastically reducing the risk of loss and, as ancillary benefits, increasing the longevity of the company’s assets.
Another area in which data analytics and AI will help risk managers is in industires where workers have stringent safety requirements – for example if they work at height or carry dangerous or heavy materials.
Wearable technology can feed back information -much like the black box mentioned earlier – to alert risk engineers and risk managers if there is potential hazard, and to enable a worker to correct their movement or posture before something serious occurs.
For these innovations to make a real difference, however, there may need to be a cultural shift.
Risk managers will need to tread carefully to ensure, for example, that workers appreciate that it is their safety that is being monitored rather than their movements or productivity.
The human touch
There are many ways in which AI and data are impacting all of our lives. But it is important to remember that they will never replace some human skills. Rather, we humans need to harness the power of these new technologies to be able to do our jobs better.
A human cannot analyse data at the same rate that some technologies can. But a human can understand the importance of that data, the nuances of that output and the lessons it is telling us.
Risk managers have a hugely important role to play in companies of all types. These new technologies will, I believe, help them to push the profession of risk management into a new era.