AI in Bermuda Insurance, Reinsurance and Financial Services

Bermuda is the world's risk capital, and that makes insurance and reinsurance the centre of gravity for AI in Bermuda. Underwriting, claims, catastrophe modelling, reserving, AML and customer service are all being reshaped, under the eye of a regulator that has published more on AI than any other in the offshore world. This Laurenceo guide brings together what is known about AI in Bermuda's financial services sector, sourced and in one place.

Why AI in Bermuda Finance Matters Globally

The stakes are large. In a September 2025 statement, BMA deputy managing director Gerald Gakundi said Bermuda-based commercial insurers and reinsurers incurred $1.1 trillion in gross claims costs between 2016 and 2024 (Captive.com), and that advanced technologies, including AI, could bring material benefits to (re)insurers. When Bermuda's market changes how it prices and pays risk, the effect reaches cedants and policyholders around the world.

How Widely Is AI Used?

Measure	Finding	Source
Insurers using AI or ML (data for 2021)	Adoption described as "in its infancy" but expected to pick up significantly over five years	BMA survey report, 2022
Property-casualty firms using AI or ML	About 24%	BMA survey, reported by Captive.com
Re/insurance professionals who see AI as the best way to improve underwriting results	57.9% (January 2025)	Bermuda Re+ILS
Employed Bermuda residents using AI for work at least weekly	Nearly six in ten	Narrative Research survey, January 2026 (Bernews)

The BMA's own survey is the most authoritative measure, but it reflects data for 2021. The direction since then is clear from the BMA's 2025 discussion paper and 2026 consultation, which treat AI as mainstream across the sector.

Where AI Is Used

Underwriting. Triage of submissions, extraction of exposure data, pricing support and portfolio steering. Bermuda executives have told Intelligent Insurer that AI will fundamentally change the underwriter's role.
Claims. Document extraction, fraud signals and leakage detection; a Lloyd's Lab cohort with a Bermuda reinsurance focus included a tool that structures and analyses claims files to find leakage (Captive.com).
Catastrophe modelling and forecasting. AI weather models are becoming part of hurricane forecasting. At ILS Bermuda Convergence 2025, Judith Curry of the Climate Forecast Applications Network said her team's AI indices beat the National Hurricane Center's rapid intensification forecasts at 24 and 48 hours, while warning that AI emulators still struggle with intensity (Insurance Business). That is a conference claim about her own indices, not an independent evaluation. The Bermuda Institute of Ocean Sciences has supported the industry's catastrophe research since its Risk Prediction Initiative was formed in 1993 (BIOS).
Parametric and insurtech. AI-driven parametric platforms such as CatX and new insurtechs have used Bermuda as a base.
Compliance and AML. Transaction monitoring, screening and regulatory reporting.
Operations. Drafting, summarisation and internal assistants, which is where most generative AI use starts.

Banking, Investment and Digital Assets

The BMA's guidance applies equally to banks, investment businesses, funds and digital asset businesses. Bermuda's digital asset regime does not restrict AI; Carey Olsen notes that digital asset businesses already use AI models. Premier David Burt has said the Government intends to explore legal clarity for AI agents in financial services, which would matter most for automated trading and payments.

The Risks Supervisors Care About

Model risk: errors in pricing or reserving, and drift as conditions change.
Underwriting and claims errors: listed among the risks respondents worried about in the BMA's 2022 survey.
Explainability: customers and supervisors need to understand material decisions.
Third-party concentration: many firms rely on the same few model vendors.
Data protection: AI that uses personal data must comply with PIPA.
Agentic AI: systems that act, not just advise, need boundaries enforced outside the model.

The Rules That Apply

Every BMA-regulated firm should read The BMA's AI Guidance Note, Explained. In short: the board is accountable for AI risk, each AI use case is assessed for materiality, controls scale with impact, and firms must be able to evidence that controls work.

Laurenceo's View

AI will change Bermuda's market first in the unglamorous places: submissions, claims files and compliance workflows. The firms that win will be the ones that can show a supervisor, a cedant or a rating agency that their AI is controlled, with records rather than reassurances. Laurenceo's research and its Production Control Specification are written for exactly that problem, and Laurenceo Intelligence tracks AI in insurance and reinsurance every day.

Questions and Answers

How is AI used in Bermuda reinsurance?

Mainly in underwriting triage and data extraction, claims handling and leakage detection, catastrophe modelling and forecasting, compliance and internal productivity. Adoption has grown since the BMA's 2022 survey described it as in its infancy.

Does the BMA regulate AI used by insurers?

Yes, through existing insurance regulation. The BMA's proposed Guidance Note explains how governance, risk, conduct, cyber and outsourcing obligations apply when insurers and reinsurers use AI.

Is AI replacing underwriters in Bermuda?

Not replacing, but changing the role. Bermuda executives expect AI to take over data gathering and triage, leaving underwriters to focus on judgement, relationships and complex risks.

Can AI predict hurricanes better than traditional models?

In some respects. AI weather models have shown strong track forecasting and some rapid intensification skill, but intensity forecasting remains harder, and forecasters treat AI as one more tool rather than a replacement.