Data migration is a major challenge for insurance firms, often leading to cost overruns and delays. According to Gartner, 83% of data migration projects either fail or exceed budgets and timelines. This poses significant risks for insurers, including compliance issues, operational disruptions, and financial losses. However, ChainThat offers a smarter approach. Its insurance-specific policy lifecycle migration framework is designed for agility, reliability, and security.
Built on Azure Data Factory (ADF), the solution minimises disruptions and ensures a seamless transition to modern systems.
Why do insurance data migrations fail?
Migration is often an underestimated aspect of insurance IT modernisation. Forbes highlights that only 36% of migration projects stay within budget, while just 46% are completed on time. For insurance leaders, this raises critical concerns such as data security, compliance, and business continuity.
Key challenges include ensuring migrated policy data remains secure, accurate, and complete.
Managing policy renewals and endorsements post-migration can also be difficult, while regulatory compliance with frameworks like GDPR and IFRS 17 must be addressed.
Seamlessly integrating new policy products while maintaining data integrity is another major concern.
On top of this, minimising business disruption and ensuring smooth operational continuity are critical for success.
A tailored migration framework for insurers
Most legacy insurance systems covering policies, claims, billing, and exposure are built on outdated technology.
Unlike traditional Extract, Transform, Load (ETL) tools, ChainThat’s migration framework, powered by ADF, provides a modern, API-driven alternative.
The solution avoids direct database transfers, ensuring security through an API-first approach.
It simplifies data mapping with minimal coding and automates data cleansing and standardisation, as integrated dashboards provide real-time tracking of errors and performance.
Automated workflows reduce manual intervention, improving efficiency. The system also ensures compliance with key regulatory frameworks, including GDPR, IFRS 17, and CCPA.
Making insurance migration seamless
ChainThat’s agile, AI-augmented approach ensures insurers experience a smooth transition without the risks associated with traditional data migrations.
The framework guarantees immediate system usability post-migration and minimises business downtime while maintaining operational continuity.
Automated validation and data cleansing maintain data integrity, while compliance with key regulations reduces legal risks.
The solution also lowers post-go-live support requirements, leading to greater cost efficiency.
A case study: Successful migration for a US farm mutual insurer
A leading US farm mutual insurer faced significant challenges in migrating policy data to a modern BPA system.
Risks included data loss, downtime, and regulatory hurdles. By leveraging ChainThat’s framework, the insurer achieved a seamless transition while benefiting from reduced operational complexity by avoiding dual system management.
The user experience improved for underwriters and agents, while costs were lowered by eliminating the need for parallel systems.
The insurer also achieved full integration with accounting and regulatory reporting systems, streamlining renewal and endorsement processes with a future-ready system.
The future of insurance data migration
Looking ahead to the rest of 2025 and beyond, ChainThat is set to further enhance its migration framework with AI-driven predictive models.
These innovations will analyse historical and real-time data to anticipate migration challenges, enabling insurers to resolve issues before they impact operations.
For insurance CXOs, ChainThat’s cutting-edge migration solution not only mitigates risk but also turns data migration into a strategic enabler for business growth.
Read the full blog from ChainThat here.
