Automated Public Policy Application Service for Citizens

Overview

Currently, citizens are required to search for relevant information across multiple government agencies and navigate complex application procedures in order to access public policies. As a result, many eligible individuals fail to receive the support benefits available to them.

This service leverages AI to analyze individual circumstances and automatically recommend relevant public policies tailored to each citizen. In addition, it streamlines and simplifies the application process, thereby improving accessibility to government support and enhancing the overall efficiency of policy delivery.

Project description

The system utilizes AI to analyze individual profiles—including income, age, residential area, and family composition—to recommend optimized public policies. This ensures users do not miss out on benefits for which they are eligible.

By integrating with public data portals and identity verification systems, the platform automatically identifies eligible policies and, with user consent, facilitates the application process. This eliminates complex manual documentation and automates the entire journey, significantly enhancing citizen convenience.

Furthermore, the AI monitors newly introduced policies or updates to existing support programs in real-time. It provides personalized notifications and advance alerts for approaching deadlines, ensuring citizens can apply within the required timeframe.

Key technological features

• Data Linkage and Authentication System: Linking with public data and identity verification systems to support automated applications
• Customized Policy Guidance and Notification Features: Providing users with real-time access to eligible policies and notification capabilities

Expected outcomes

This service enables citizens to more easily apply for public policies they are eligible to receive, while reducing complex administrative procedures to enhance the government's administrative efficiency.

Before and after implementation (AS-IS vs TO-BE)

Launch year: 2024

Attribution

Case study courtesy of the National Information Society Agency, Republic of Korea, Apolitical's Content Partner. Sourced from Use Cases of Public AI Service, Vol.2, https://eng.nia.or.kr/site/nia_eng/ex/bbs/View.do?cbIdx=31975&bcIdx=29182&parentSeq=29182