Reinsurers Face New Challenges

Emerging risks affecting the reinsurance business present opportunities for analytics and predictive modeling.


Reinsurers face multiple headwinds forcing them to come up with creative solutions. Most reinsurers already are investing in business intelligence (BI), data analytics and sophisticated, specialized components (e.g., modeling tools). At the same time, the technology solutions in place at reinsurance companies often lag other areas of the insurance industry. 

The COVID-19 Pandemic and Emerging Risk

COVID-19’s impact on reinsurers has depended in part on their exposure to particular lines of business (e.g., event cancellation). Even so, claims have been lower than anticipated, and reserves and solvency do not present issues. Life reinsurance saw more of an impact from the pandemic than property/casualty did but was still manageable. The overall loss development of the pandemic presents a potential opportunity for modelers. 

At the same time, predicting and managing emerging hazards (e.g., nanotechnology, pandemics, terrorism, cyberattacks, GMOs, e-cigarettes, driverless cars) are creating analytics and modeling challenges for reinsurers. One leading emerging hazard that reinsurers face is climate change and the related increase in natural catastrophes. 

To reduce their exposure to potential capital and earnings volatility, reinsurers should consider the increasing frequency and severity of perils such as floods, storms and wildfires in their pricing. Some reinsurers are already shifting investments away from industries that contribute significantly to CO2 emissions and toward green technologies.

Business Intelligence and Data Are Critical

Pressure from competitors means moving from Excel-based analysis to more sophisticated technologies. Reinsurers are demanding complete and accurate data from primary insurers, focusing on data cleansing, and continuing to use advanced analytical tools to find opportunities to create competitive advantage. 

Once some reinsurers begin investing in data analysis and predictive modeling, the others must follow; otherwise, the latter group will face adverse risk selection and lose market position. Larger reinsurers are investigating AI and machine learning. 

Reinsurers are also exploring new frontiers when it comes to third-party data sources. Some reinsurers are piloting new data aggregation startups that bring together data sources from social media and government records. Others are acting as data aggregators themselves by packaging and providing data and book of business analytics to small and midsized insurer clients.

See also: Excess & Surplus Lines Market Hardens Further

Core Modernization

Reinsurers are investing in core systems to centralize business, streamline workflows and gain better data access to deal with an increase in audits and regulations. Most reinsurers looking at core system replacement are prioritizing integration of core systems with BI and modeling tools, catastrophe modeling and mapping and using broker and third-party data to build risk insights. 

Reinsurers also continue to monitor and engage with emerging technologies, paying most attention to technologies with impact on data and process improvements. Some are exploring robotic process automation to automate routine processes and data movement, freeing resources for value-added work while improving cycle time and consistency. Most of the blockchain consortiums in the insurance industry revolve around reinsurance, though there has yet to be significant impact on how the industry works.

Final Thoughts

Emerging risks affecting the reinsurance business present opportunities for analytics and predictive modeling. Reinsurers should continue to leverage data from primary insurers and other sources to derive insights for primary insurer clients and to optimize their portfolios. 

AI and machine learning have a role to play alongside traditional analytics in optimizing analytics models, placement of business and loss mitigation or prevention on behalf of primary insurers. Reinsurers should also migrate from Excel spreadsheets and workbooks to centralize and improve access to data, achieving a better user experience and easier regulatory compliance. 

To learn more about the latest activity in the reinsurance industry, please read Aite-Novarica Group’s latest report on the topic, Business and Technology Trends, 2022: Reinsurance.

Steven Kaye

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Steven Kaye

Steven Kaye is head of knowledge management at Aite-Novarica Group and lead editor of the firm’s Business and Technology Trends in Insurance series. He has managed a wide range of research projects since joining the firm in 2008.

Previously, Kaye worked for Accenture as an insurance researcher focused on the U.S. life and property/casualty markets. He also served in both knowledge management and research roles at Gemini Consulting (now part of Capgemini) for several of the firm's industry practices.

Kaye holds MILS and B.A. degrees from the University of Michigan.


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