“Finding Hidden Foreign Pensions” Based on AI and Big Data Analysis

Securing Foreign Pension Rights via AI & Big Data “Finding Hidden Foreign Pensions”
Proactive Identification: Using AI-based data analysis to preemptively identify and notify potential beneficiaries.
Transforming the Claim Support Process: From a passive approach to a scientific, data-driven identification method.
Impact: Reversed the annual decline, expanding eligibility guidance eightfold from 202 in 2024 to 1,525 in 2025

Innovation Summary

Innovation Overview

Since individuals typically work abroad in their youth but claim pensions after age 65, many potential beneficiaries remain unaware of their eligibility for pension benefits paid decades ago.

Data-driven Transformation: Previously, target identification relied solely on the overseas residence information of existing claimants. We have transformed this into a scientific analysis method, leveraging the vast datasets held by the NPS in this era of digital transformation.

Implementation Details:
- Identification: Established a collaborative framework with the ICT & Big Data Department to analyze and utilize target data based on AI.
- Developed the initial predictive model by applying the Random Forest algorithm and conducting an AUC performance evaluation.

Analysis Workflow:
Utilized 8.5 billion records held by the NPS, including immigration records and benefit payment information. Analyzed the characteristics of current old-age pension beneficiaries who are already receiving foreign pensions. Successfully identified 1,525 potential beneficiaries.

Notification: Providing step-by-step and tailored guidance on “Finding Hidden Foreign Pensions” to the identified 1,525 individuals.

PR: Conducting promotional activities through official NPS channels and overseas Korean organizations.
Press Releases: Selected as a key public service project.
NPS Website: Promoted via rolling banners on the NPS website.
Official Social Media: Featured on the official blog.
Direct Outreach: Conducted information sessions for overseas residents on various occasions, including the 2025 World Korean Community Leaders Convention and on-site briefings.

Innovation Description

What Makes Your Project Innovative?

Transformation of the identification system for potential foreign pension claimants under Social Security Agreements
Passive Approach: Relying on self-reported overseas residence information provided during the old-age pension application process.
Proactive & Scientific Identification: Preemptively identifying potential claimants by leveraging AI-driven analysis of vast internal datasets held by the NPS.

What is the current status of your innovation?

While over 228,000 citizens reported overseas emigration before 2000*, only approximately 6,000 currently receive foreign pensions, highlighting a critical need to identify potential beneficiaries.
*Those who emigrated 25+ years ago and are now reaching pensionable age.

Innovation uses AI and Big Data for scientific analysis to proactively identify and guide potential claimants, simultaneously protecting citizens’ pension rights and advancing national interests.

Innovation Development

Collaborations & Partnerships

Team broke down departmental silos through active internal collaboration with the ICT & Big Data Dept., integrating our administrative expertise with their cutting-edge technology. Their expertise in analyzing vast internal datasets was essential to realize this innovative idea. This synergy enabled a successful transition from a passive, manual process to a proactive, scientific system.

Users, Stakeholders & Beneficiaries

Simultaneous realization of citizens’ rights and national interest by securing unclaimed foreign pension benefits to protect individual financial rights and contribute to the national economy.

Facilitating the long-term inflow of foreign pension payments serves as a stable source of foreign currency revenue, enhancing public trust in the NPS.

Innovation Reflections

Results, Outcomes & Impacts

Protecting Citizens’ Rights: By leveraging AI and big data, we identified potential foreign pension beneficiaries. This proactive approach reversed a downward trend, expanding the number of identified individuals by approximately eightfold!
Performance: Increased from 202 individuals in 2025 to 1,525 in 2025.

Challenges and Failures

Barriers: A stagnant organizational culture that relied solely on self-reported customer information, hindering proactive service delivery.

Overcoming the Barriers:
- Center for International Affairs: Recognized the potential of utilizing NPS internal datasets to identify unclaimed pension rights.
- ICT & Big Data Department: Embraced the shift toward a data-driven administrative culture in the digital transformation era.
- Outcome: Identification of target individuals powered by AI and Big Data analysis.

Conditions for Success

Synergizing specialized expertise through cross-departmental collaboration

Center for International Affairs:
- Providing field-based operational know-how
- Verified the validity of the identified target individuals

Digital Strategy Division:
- Securing expert big data analysts
- Developing an analytical model using diverse techniques

Outcome: This collaboration allowed us to efficiently identify potential foreign pension beneficiaries through scientific data analysis.

Lessons Learned

Innovation and improvement of public administrative services are possible through a shift in thinking during the era of AI and digital transformation.

🇰🇷