BI’s Article search uses Boolean search capabilities. If you are not familiar with these principles, here are some quick tips.
To search specifically for more than one word, put the search term in quotation marks. For example, “workers compensation”. This will limit your search to that combination of words.
To search for a combination of terms, use quotations and the & symbol. For example, “hurricane” & “loss”.
BERLIN — Artificial intelligence will create new liabilities for organizations, but it can also be harnessed as a risk management tool, a panel of experts said.
By processing high volumes of data, risk managers can get a better grasp of the risks they face, spend less time on repetitive tasks and use connected devices to enhance their risk management processes, they said.
Companies are already implementing AI, and risk managers should ensure they are aware of the risks and liabilities that the technology creates, said Philippe Cotelle, head of insurance and risk management at Airbus Defence & Space, a division of Airbus SE in Toulouse, France.
He was speaking during a session of the Federation of European Risk Management Associations’ biennial forum in Berlin on Monday.
Risk managers should make sure they are “going to capture what is within AI both in terms of risks and in terms of opportunity, and it becomes a tool for the risk manager,” Mr. Cotelle said.
AI can be used to enhance processing of structured and unstructured data, said Jens-Daniel Florian, head of digital strategy and transformation for the Continental Europe operations of Marsh LLC in Dusseldorf, Germany.
Structured data includes information found in risk management databases and spreadsheets, while unstructured data includes images, text files and emails, usually not processed by risk managers, he said.
AI can be used to look for patterns in large amounts of data and to determine the value of critical assets, among other things, Mr. Florian said.
In addition, the technology can be used to analyze claims data and draw conclusions about whether underwriting or risk management models are working effectively, he said.
“Preventing claims is the main task that we all want to go for, and it’s the greatest benefit we can achieve for our companies,” Mr. Florian said.
AI can also be used to increase efficiency and manage complexity, Mr. Florian said.
“The greatest benefit will be that we can manage complexity in a different way. It will help us to manage large data sets that we don’t have today but will have in the future,” he said. “It will allow us to do correlations of different risks that we are not able to perform as human beings, or don’t want to invest the time or money to do so.”
The technology will also enable risk managers to make more informed, faster decisions, Mr. Florian said.
Much of the data that is used in developing AI technology is obtained through the “internet of things” devices that are being used to improve operational efficiencies in numerous industries, said Hélène Stanway, digital leader for Axa XL, a division of Axa SA, in London.
“We are seeing too much of the operation focus and not enough of the risk focus. The data is there already, you just need to think about how to leverage that data to think about risk,” she said.
For example, when goods are transported around the world, “you ship and pray. You hope they are going to get to the other side in the condition in which they started,” Ms. Stanway said.
Sensors can be installed with the cargo to measure temperature, humidity, light and shock levels, she said, which provides risk managers and insurers with data on what happens to sensitive cargo as it is transported.
AI can then be used to aggregate the data and determine, for example, what happens to the cargo from a seasonal perspective or when it is handled by an individual logistics provider, she said.
Axa XL installed the sensors in the shipping containers of a transportation policyholder and reduced its loss ratio to 80% from 180%, Ms. Stanway said.
“We used the data, we used the human experience from our risk managers, and said that actually you just need to change the way that you are packaging these goods,” she said.
Although AI has the potential to transform risk management, the technology won’t replace risk managers, said Bénédicte Huot de Luze, CEO of AI Risk Services in Paris.
“When you use AI, it is only to replace a practice with no added value, it is only something repetitive with a high volume and done without expertise,” she said.
AI is complementary to traditional risk management, Ms. Huot de Luze said.
Artificial intelligence and machine learning technologies are increasingly being deployed by companies to reduce risk, with a broad swath of industries from financial services and transportation to energy and technology applying the tools to detect fraud, manage cyber threats and predict disruptions.