This paper builds on Part I: The Potential of Automation and AI in Insurance, which introduces the concept of platforms of intelligence and analyses automation potential across core insurance functions.

In Part II of the joint benchmark study, Synpulse and additiv focus on one of the most automation-ready areas of insurance: claims. Building on the concept of platforms of intelligence introduced in Part I, the study shows how insurers can modernise claims operations incrementally and with low risk, without replacing legacy core systems. 

The benchmark analysis demonstrates that insurers can automate up to 70% of straightforward claims and reduce claims service costs by up to 31%. High-impact use cases include FNOL and triage, reserving, and settlement, where AI-driven workflows and orchestration deliver rapid time to value. 

Beyond cost efficiency, the study highlights the strategic impact on customer experience and revenue. Faster resolution, fewer errors and more transparent communication directly improve satisfaction, retention and renewal rates while freeing claims experts to focus on complex and sensitive cases. 

The key takeaway: claims transformation does not require a ‘big bang’ IT programme. With modular platforms of intelligence, insurers can start small, deliver measurable results within months, and build a scalable foundation for continuous innovation.

This paper builds on Part I: The Potential of Automation and AI in Insurance, which introduces the concept of platforms of intelligence and analyses automation potential across core insurance functions.

In Part II of the joint benchmark study, Synpulse and additiv focus on one of the most automation-ready areas of insurance: claims. Building on the concept of platforms of intelligence introduced in Part I, the study shows how insurers can modernise claims operations incrementally and with low risk, without replacing legacy core systems. 

The benchmark analysis demonstrates that insurers can automate up to 70% of straightforward claims and reduce claims service costs by up to 31%. High-impact use cases include FNOL and triage, reserving, and settlement, where AI-driven workflows and orchestration deliver rapid time to value. 

Beyond cost efficiency, the study highlights the strategic impact on customer experience and revenue. Faster resolution, fewer errors and more transparent communication directly improve satisfaction, retention and renewal rates while freeing claims experts to focus on complex and sensitive cases. 

The key takeaway: claims transformation does not require a ‘big bang’ IT programme. With modular platforms of intelligence, insurers can start small, deliver measurable results within months, and build a scalable foundation for continuous innovation.