A new report by the Bermuda Monetary Authority (BMA) has concluded that use of artificial intelligence and machine learning technologies in the Bermuda re/insurance market is still currently in its infancy, but is set to pick up significantly over the next five years.
Machine learning, which focuses on the use of data and algorithms to imitate the way that humans learn, is an important component of the growing field of data science and is increasingly being utilized by re/insurers to improve the speed, accuracy and capabilities of digital processes.
A survey of Bermuda insurers conducted by the BMA found that, overall, 38% of firms that responded are using AI or ML systems to some degree.
And for property and casualty (P&C) insurers, the percentage was just 23.7%, showing the extent to which uptake of these technologies remains at an early phase.
But among the 62% of respondents that do not use AI/ML technologies, the BMA reported that 23% indicated that they plan to adopt AI/ML in the next five years or less.
This time scale should allow the Authority and the Bermuda insurance market sufficient time to develop a creditable and fit-for-purpose AI/ML framework, analysts noted.
Accordingly, the top challenges and obstacles preventing the adoption and usage of AI/ML systems include these systems not being critical to current business offerings, a lack of skills and expertise to implement these technologies, and limited budget .
When asked about the areas of concern insurers have when considering adopting AI/ML systems, the top responses were explainability, auditability, modelling challenges, system security, transparency and consistency of outputs.
“The acceleration of digitalisation in the financial services sector has brought about new ways and means to improve insurance companies’ operations, including the use of AI/ML systems,” the BMA concluded.
“The BMA recognises that AI/ML systems create opportunities, including discovering additional risks and perils leading to new insurance products, a more streamlined insurance life cycle brought about by increased interconnectedness and new ways to underwrite traditional lines,” it continued.
“Alternatively, AI/ML systems carry an increased risk profile, particularly in cybersecurity, data privacy and legal and compliance uncertainty, not to mention ethical considerations and the risks of unintended outcomes.”
