FERMA Delves into Artificial Intelligence and Risk Management

The Federation of European Risk Management Association (FERMA) recently released a paper titled Artificial Intelligence Applied to Risk Management that explores the implications of artificial intelligence (AI) for risk management.

The paper provides risk managers with a basic understanding of AI and directs them in developing their own strategy for AI implementation with an action guide and a template for creating an AI risk management road map.

With the paper, FERMA said it aimed to perform an initial assessment of the potential value of AI to improve enterprise risk management (ERM), and second, to understand how risk managers can be key actors in highlighting to the organization leadership the opportunities and challenges of AI technologies.

Concerning ERM, FERMA said risk managers will want to consider how AI can be best used in consideration of the following questions.

• How can risk management frameworks integrate AI, especially as a source of new risks across the organizations?
• Can we process more data to mitigate losses?
• How can we use AI in the claims process?
• What processes will we create, and what will be provided by brokers, insurers, and reinsurance companies?

As with every new technology, there are emerging risks and challenges related to AI. Questions on ethics, equality, biases, trustworthiness, and reliability of decisions made or suggested by AI are just some of the topics that need attention. Transparency of algorithms and increasing cyber risks are also questions for the risk manager to address, according to FERMA.

The working group, made up of experts from within and outside the risk management community, expects that corporate risk management will benefit from AI in several areas.

• From its ability to process large amounts of data to the automation of certain repetitive and burdensome risk management steps, AI could allow risk managers to respond faster to new and emerging exposures.
• By acting in real time and with some predictive capabilities, risk management could reach a new level in supporting better decision making for senior management.

The report said that to perform well, AI needs data of a certain quantity and quality. Therefore, the first consideration should be about an organization's strategy for managing its corporate data. As such, solving the data issue and implementing AI in business is a challenging project that impacts many corporate functions, including risk management.