Market Context — Why This Technology, Why Now

Global enterprises face immense pressure to leverage data for competitive advantage while navigating a complex landscape of privacy regulations and cyber threats. The rise of AI and IoT amplifies data sharing needs, making secure, privacy-preserving data matching critical. This technology offers a strategic advantage by enabling compliant and trusted data collaboration, essential for cross-organizational analytics, fraud prevention, and personalized service delivery across diverse sectors.

Key Competitive Advantages
01

Safely identifies common elements without disclosing raw data, utilizing secret sharing technology.

02

Securely protects data even from malicious actors who do not follow the protocol, based on PSI protocols.

03

Demonstrates significant technical superiority with only 3 prior art references, enabling early market share capture.

Market Opportunity
Financial Services
$300M–$400M globally (AI est.)
Privacy-preserving data collaboration is essential for risk assessment, fraud detection, and enhancing customer experience through customer data analysis.
Retail banks Investment firms Insurance providers FinTech solution developers
Healthcare and Pharmaceuticals
$150M–$250M globally (AI est.)
There is a growing need for efficient data sharing and analysis in clinical research, genomic data analysis, and drug discovery processes, while protecting confidential patient information.
Pharmaceutical R&D departments Clinical research organizations Biotech firms Health data analytics platforms
Advertising and Marketing
$200M–$300M globally (AI est.)
This technology contributes to improving the accuracy of privacy-conscious targeted advertising and providing personalized services through customer behavior analysis.
AdTech platforms Marketing analytics providers Consumer data aggregators Digital advertising agencies
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects a robust data matching process, from secret information generation to common element determination, using secret sharing and PSI protocols. Its strong claims, which successfully differentiated from only three prior art references, indicate high technical uniqueness and strong defensibility against future invalidation challenges.

Competitive White Space

This patent primarily covers the core data matching algorithm. Licensees could develop additional IP in areas such as post-matching data analytics, secure multi-party computation beyond PSI, or integration with specific industry-vertical data governance and compliance platforms.

Economic Impact
~$2.0M/year estimated risk reduction and revenue generation per facility (est.).
estimated ROI · USD · AI analysis
ROI Calculation Logic

Implementing this technology could significantly reduce potential costs associated with confidential data breaches, including damages (averaging ~$1.5M/incident (AI est.)), brand damage, and regulatory fines. For example, avoiding one data breach per year could prevent an average loss of ~$1.5M (AI est.). Additionally, secure data collaboration could generate ~$350K (AI est.) in new business revenue annually, leading to an estimated total economic impact of over ~$2.0M (AI est.) per year.

Speed to Market
6× faster than in-house development
The algorithms based on secret sharing and PSI protocols are already established. The components described in the patent specification can be implemented using existing cryptographic and data processing technologies. Compared to greenfield R&D, a significant portion of the technical implementation design is complete, substantially shortening the development period. This could enable licensees to rapidly initiate PoCs and reduce time-to-market by approximately 2.5 years.
Competitive Positioning

X: Data Privacy Level
Y: Data Collaboration Flexibility

Business Models & Applications
📝 Licensing Model
License this technology as a functional module for integration into existing products or services, enhancing privacy protection capabilities for licensees.
☁️ SaaS Data Matching Platform
Offer this technology as a cloud-based service, building a platform where multiple enterprises can securely perform data matching.
🤝 Data Collaboration Solution Provider
Develop and provide customized privacy-preserving data collaboration solutions utilizing this technology for specific industries or enterprises.
Adjacent Application Opportunities
💳 Financial & Insurance
Enhanced Fraud Detection & Credit Scoring
Multiple financial institutions could securely share information on fraud patterns and credit risks without disclosing confidential customer data, enabling the joint development of more accurate detection and scoring systems. This could contribute to curbing financial crime and promoting sound financial transactions.
🏥 Medical & Healthcare
Secure Data Collaboration for Research & Drug Discovery
Hospitals and research institutions could safely match and analyze patient personal information and clinical data while maintaining privacy, accelerating the development of new treatments and drug discovery research. This could significantly enhance research efficiency and outcomes.
📊 Advertising & Marketing
Privacy-Preserving Targeted Advertising
Advertisers and data providers could identify common customer segments without disclosing individual purchasing histories or behavioral data. This could enable more personalized advertising while respecting privacy, maximizing advertising effectiveness by an estimated 15-20%.
Integration Roadmap — Estimated 13-Month Deployment
Phase 1: Requirements Definition & Technical Validation
Duration: 3 months
Detailed analysis of existing systems and data collaboration requirements, defining the scope and protocol design for this technology. Technical suitability is validated through a Proof of Concept (PoC).
Phase 2: System Development & Prototype Construction
Duration: 6 months
Development of this technology's software modules based on defined requirements and integration into existing data processing infrastructure. An initial prototype is built, and functional and performance tests are conducted.
Phase 3: Operational Launch & Feature Expansion
Duration: 4 months
Deployment to production and commencement of operations, monitoring stability and performance in actual data collaboration. Features are expanded and optimized based on usage, aiming for continuous value creation.
Technical Feasibility
This technology's process, from secret information generation to common element extraction, is clearly defined as software modules. These modules can be implemented using existing data processing infrastructures and standard cryptographic libraries, requiring no significant hardware investment or infrastructure overhaul. The components described in the patent specification can be realized with general-purpose technologies, offering high compatibility with existing IT environments and enabling relatively rapid system integration for licensees.
Success Scenario
Upon adopting this technology, licensees could securely conduct joint analysis with partners while keeping highly confidential customer data private. This could accelerate the discovery of new customer segments and the development of more personalized services, potentially increasing annual sales by over 10%. Furthermore, reducing data privacy infringement risks is estimated to contribute to enhanced brand value.
Patent Record
APPLICATION NO.
JP2022-010444
REGISTRATION NO.
7759269
FILING DATE
2022/01/26
GRANT DATE
2025/10/15
EXPIRATION DATE
2042/01/26
PATENT HOLDER
日本放送協会
Examination History
2024-12-09
Request for Examination
2025-09-16
Decision to Grant