Journal article in Insurance Review
How does digitalisation reshape the architecture of insurance markets? Why is innovation in this sector primarily driven by processes rather than products? And what do artificial intelligence, big data, and on-demand models mean for the future of insurance as we know it?
These questions are at the heart of our latest publication, Digital Transformation and Innovation in the Insurance Sector: Processes, Technologies, and Challenges, co-authored with Prof. Adam Śliwiński and Dr. Renata Pajewska-Kwaśny, and published in Insurance Review (2/2025).
The article offers a comprehensive overview of how technological change – including AI, machine learning, and telematics – is transforming core insurance functions such as underwriting, pricing, distribution, and claims management. Drawing on the conceptual framework of Barras’s reverse innovation cycle, we argue that the insurance sector exemplifies a distinct pattern of service innovation: process improvements come first, while truly disruptive product innovations remain relatively rare and often marginal.
We explore not only the mechanics of transformation but also its implications: the rise of usage-based and on-demand insurance models, the increasing reliance on predictive analytics and automation, and the complex ethical, regulatory, and operational challenges that insurers must now face. We also ask: what barriers still slow adoption, particularly for smaller insurers? And what does the future hold for customer trust, AI explainability, and the evolving role of regulators?
This article may be of interest to readers working on the intersection of insurance, technology, and innovation economics – and to all those seeking to understand how deeply digital transformation is reshaping even the most traditional sectors of finance.
Abstract
The digital transformation of the insurance sector improves risk assessment, pricing, distribution, and claims management. Key technologies driving these changes include artificial intelligence (AI), machine learning (ML), big data analytics, and automation. These advancements primarily drive process innovation, aligning with Barras’s reverse innovation cycle rather than traditional product innovation.
The authors show that key technologies such as telematics, the Internet of Things, predictive analytics, and robotic process automation streamline operations and improve customer experience. However, challenges remain in ensuring AI transparency and interpretability. While digital transformation is still in its early stages, its continued development will shape the industry’s efficiency, competitiveness, and regulatory landscape.
Keywords:
Digitalisation of insurance, process innovations, AI in insurance, Barras’s reverse innovation cycle, big data in insurance
JEL Classification:
G22, G52, D58
Credits
| Authors | Adam Śliwiński, Łukasz Kuryłowicz, Renata Pajewska-Kwaśny |
| Date | 2025 |
| Pages | 93-116 |
| Type | Journal article |
| ISSN | 0137-7264 |
| DOI | 10.33995/wu2025.2.6 |
| How to cite | Sliwinski A., Kurylowicz L., Pajewska-Kwasny R. (2025). Digital Transformation and Innovation in the Insurance Sector: Processes, Technologies, and Challenges. Insurance Review, 2/2025, pp. 93-116. |
Full text
Full text is available at ResearchGate