How Data Clean Rooms Can Power Business Model Reinvention for Telecom Companies

Introduction

Telecom companies are at a crossroads. Traditional revenue streams, such as voice and SMS, continue to decline, while data services are becoming increasingly commoditized. At the same time, telecom operators sit on a goldmine of data—customer behavior, network usage, and fraud patterns—that, if leveraged effectively, could open up entirely new revenue opportunities. However, regulatory constraints and privacy concerns have made it difficult for telecoms to fully capitalize on their data assets.

Enter data clean rooms (DCRs)—a privacy-enhancing technology that allows telecom companies to unlock the power of their data securely and compliantly. By enabling privacy-preserving collaboration with external partners, DCRs can help telecom operators reinvent their business models in ways that drive new revenue streams and competitive advantages.

Understanding Data Clean Rooms

A data clean room is a secure, controlled environment where multiple parties can collaborate on data analysis without exposing raw datasets. These platforms use privacy-enhancing technologies (PETs) such as encryption, differential privacy, and secure multi-party computation to ensure that sensitive data remains protected while still enabling valuable insights.

For telecom operators, this means they can share insights with banks, advertisers, insurers, and other ecosystem partners without violating data protection regulations like GDPR. The result? New revenue-generating collaborations that were previously impossible due to privacy concerns.

Business Model Reinvention Through Data Clean Rooms

1. Enhancing Fraud Prevention and Cybersecurity Services

Telecom fraud, such as SIM swapping, call forwarding fraud, and ATO (Account Takeover), remains a major challenge. By leveraging a data clean room, telecoms can securely collaborate with banks, fintechs, and cybersecurity firms to detect and prevent fraud in real-time.

• Use Case: A telecom operator partners with a bank to detect SIM swap fraud. By allowing the bank to query anonymized telecom data in a clean room, they can verify if a customer’s SIM card was recently swapped before approving a high-value transaction.

• Revenue Opportunity: Monetize fraud detection services by offering real-time risk scores to financial institutions.

  
  

2. Transforming Advertising and Customer Insights

With increasing restrictions on third-party cookies and traditional digital tracking methods, advertisers are struggling to target audiences effectively. Telecom operators, with their first-party data on user behavior, can become key players in privacy-preserving advertising.

• Use Case: A telecom company collaborates with advertisers to provide insights into audience segments without exposing individual user data. Using a data clean room, advertisers can measure campaign effectiveness while maintaining user privacy.

• Revenue Opportunity: Telecoms can offer privacy-compliant audience segmentation services to advertisers, creating a new revenue stream in digital marketing.

  
  

3. Optimizing Smart City and IoT Monetization

Telecom networks power IoT devices and smart city infrastructure, generating vast amounts of data. However, sharing this data with governments, enterprises, and urban planners is often restricted due to privacy concerns. Data clean rooms solve this by enabling secure, privacy-compliant data collaboration.

• Use Case: A telecom operator partners with a city government to analyze mobility patterns while ensuring individual identities remain anonymous. This data helps optimize public transportation routes and reduce congestion.

• Revenue Opportunity: Telecoms can provide insights-as-a-service to municipalities, logistics companies, and urban planners.

  
  

4. Enhancing Credit Risk Modeling for Financial Services

Many individuals lack traditional credit histories, making it difficult for banks to assess their creditworthiness. Telecom data—such as mobile payment behavior, prepaid top-ups, and usage patterns—can serve as an alternative data source for credit risk modeling.

• Use Case: A telecom company collaborates with a bank to enhance credit scoring models. Using a data clean room, the bank can securely analyze telecom usage data to improve lending decisions without accessing personally identifiable information (PII).

• Revenue Opportunity: Monetize anonymized insights for credit risk assessment while ensuring compliance with data protection laws.

  
  

5. Boosting Roaming and Inter-Carrier Collaboration

International roaming agreements between telecom operators involve complex data-sharing processes that must comply with multiple regulations. Data clean rooms streamline this by allowing operators to securely share aggregated insights on roaming patterns without exposing raw customer data.

• Use Case: Two telecom operators from different countries collaborate in a clean room to optimize roaming pricing and network usage without violating data privacy laws.

• Revenue Opportunity: Improve operational efficiencies and negotiate better inter-carrier agreements.

  
  

Conclusion

Telecom companies are uniquely positioned to leverage data clean rooms to unlock new revenue streams and reinvent their business models. By enabling privacy-preserving collaboration with ecosystem partners, telecoms can expand their value proposition beyond connectivity and into areas like fraud prevention, digital advertising, IoT analytics, and financial services.

As data privacy regulations continue to tighten, adopting data clean rooms isn’t just a competitive advantage—it’s a necessity for telecom operators looking to future-proof their businesses. The time to act is now.

Are you a telecom operator looking to explore data clean rooms for business growth? Let’s discuss how privacy-enhancing technologies can help you unlock new opportunities.