Global Insurer Uses Statutory Pseudonymization to Enable International Data Transfer

Utilizing the data collected from different territories to improve risk modeling, pricing strategy, customer segmentation, and insurance fraud detection

40%
faster time to insight
20%
improvement in risk modeling and pricing strategy
$5 million
saved in potential fines and reputational damages
Case Study Summary
A multinational insurance provider based in the United States, with branches and operations in several European countries, was looking to leverage its vast amounts of insurance customer data for analytics, risk assessment, policy pricing, and fraud detection.
The insurer aimed to use the data collected from different territories. However, they faced challenges related to the cross-border transfer of personal data due to strict data protection laws such as the GDPR and the Schrems II case.
Challenge
The company’s main challenge was to share and process insurance customer data from its European branches and customers in a way that complied with strict data protection regulations. Traditional data protection methods like encryption and data masking did not meet their needs. Encryption left data vulnerable when it was decrypted for processing, and data masking solutions degraded the quality and granularity, making the data less useful for analytics.

Moreover, the company had to manage long and complex approval processes for insurance data processing and sharing, which significantly slowed down their analytics projects and increased the time to insight. The threat of potential data breaches, ransomware attacks, and enforcement actions posed a significant risk.
Solution
The company implemented Anonos’ data protection software, Data Embassy, to overcome these challenges. Data Embassy provided the insurer with technical privacy controls that not only protected data at rest and in transit but also while it was being processed, thus mitigating the risk of data breaches.
Diagram illustrating the process of Statutory Pseudonymization in Anonos's data protection software, Data Embassy, showcasing how it dynamically replaces identifiers in original data for enhanced insurance data privacy while still allowing for critical insights.
The utilized technology was statutory pseudonymization, a combination of de-identification methods, and dynamically changing codes to replace direct and indirect identifiers in the original data. Unlike data masking, which simply deletes sensitive information, statutory pseudonymization allows for authorized re-identification using the associated keys.

This approach ensured that sensitive insurance customer data remained protected while still allowing for critical insights to be derived. The associated keys allowed for authorized re-identification, providing the flexibility needed for different data use cases.
Infographic demonstrating the movement of GDPR-compliant, pseudonymized data from the EU using Anonos's data protection software, Data Embassy, highlighting the preservation of analytical value and the flexibility for different insurance customer data use cases.
Results
Time to insight was reduced by as much as 40% By using Data Embassy, the company was able to expedite its insurance data analytics projects, as well as external and internal review processes, leading to a significant reduction of time to insight.
Risk modeling and pricing strategy improved by as much as 20% With the newfound ability to share and process cross-border data lawfully, the insurer could extend their advanced analytics to their European branches, leading to an improvement in risk modeling and pricing strategy.
$5 million in potential fines saved The enhanced data protection and privacy controls reduced the risk of data breaches and enforcement actions, saving the company an estimated $5 million in potential fines and reputational damages in the first year alone.
Operations expansion and increase in new policies The solution also allowed the company to expand its operations in European markets with confidence, contributing to an increase in new policies issued in these markets within the first year after implementation.
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