While artificial intelligence (AI) adoption in reinsurance will likely remain gradual due to key challenges, it is becoming a major differentiator for companies that successfully incorporate it into underwriting, claims, and operations alongside appropriate governance and risk controls, AM Best highlights in a recent report.
AI has rapidly become one of the most widely discussed topics across the insurance and reinsurance industry.
Even though every major reinsurer is assessing methods to integrate it into its operations, the industry is still in the relatively early stages of implementation, according to AM Best’s report – Global Reinsurance at an Inflection Point: Can Discipline Survive the Temptation of Record Capital?
“Initial investments have largely focused on efficiency gains and cost reduction opportunities. Reinsurers have explored applications ranging from document processing and claims administration to workflow automation and internal knowledge management,” analysts noted. “These projects generally offer clearer return.”
Most recently, focus has broadened to encompass underwriting support and risk analytics.
“Some organisations are exploring how AI tools can enhance exposure analysis, improve portfolio monitoring, identify emerging trends, and support underwriting decision-making. While most reinsurers continue to emphasise human oversight, the potential for AI to augment underwriting processes is becoming increasingly apparent,” AM Best stated.
Although interest in AI continues to expand, “the industry’s adoption curve is likely to remain gradual.”
Reinsurance underwriting relies heavily on professional judgment, established relationships, complex judgment, limited datasets, and significant exposure to low-frequency, high-severity events.
Because of these factors, meaningful benefits from AI may take time to emerge and will likely develop incrementally rather than through immediate transformation.
Moreover, the growing adoption of AI poses several challenges for reinsurers, including model risk and lack of explainability, where the underlying logic and drivers of AI-generated decisions are not always transparent or easily understood, which could result in shortfalls with regulatory compliance.
Additionally, reinsurers must navigate regulatory complexities and address rising governance, bias, talent shortages, uncertain ROI, and vendor dependence.
AM Best concluded: “Nevertheless, AI increasingly appears poised to become a differentiating factor for organisations that successfully integrate technology into underwriting, claims, and operational processes while maintaining appropriate governance and risk controls.”
The post AI adoption in reinsurance likely to remain gradual despite growing enthusiasm: AM Best appeared first on ReinsuranceNe.ws.