Korea Inclusive Finance Agency to Build 'AI Inclusive Finance' Platform... Strengthening Customized Comprehensive Support

Advancing Product Recommendations, Comprehensive Support, and Debt Management
Developing an Alternative Credit Assessment Model
Utilizing Data such as National Tax Service Arrears
Envisioning a 'Business Model' for Savings Banks

The Korea Inclusive Finance Agency is establishing an integrated platform based on generative artificial intelligence (AI) to enhance its work in inclusive finance counseling, screening, and post-management. By leveraging accumulated information on loans, post-management, and counseling, the agency aims to analyze customers' assets and liabilities, thereby strengthening tailored financial support and the connection to employment and welfare services.

Eunkyung Kim, President of the Korea Inclusive Finance Agency and Chairman of the Credit Recovery Committee, is conducting on-site consultations at the Incheon Gyeyang Inclusive Finance Integrated Support Center last April. Provided by the Credit Recovery Committee.

According to the financial sector on June 26, the Korea Inclusive Finance Agency is pursuing the "AI-Based Integrated Platform Establishment Project." This initiative is being carried out using an on-premises approach, installing both hardware and software internally instead of relying on external cloud services. This is interpreted as a measure to utilize generative AI in work while preventing the leakage of sensitive financial information related to loans, guarantees, and post-management of debts.

Analyzing the Finances of Vulnerable Borrowers to Recommend Financial Products and Welfare Programs

The AI platform of the agency is expected to be used for financial counseling and recommending customized comprehensive support. For example, an AI chatbot would analyze the intent and context of customer inquiries to provide information on suitable inclusive finance products, support conditions, and counseling details. It is also reported that the platform will be equipped with a function to automatically generate financial counseling reports containing customized products and consulting content by analyzing the assets, liabilities, and financial transaction patterns of young customers.

AI will also be applied to customized comprehensive support services. The system will collect and link information on various support programs related to finance, employment, and welfare operated by both the public and private sectors, and recommend programs and services suitable for the customer's income, debt, and household situation. The plan is to strengthen comprehensive inclusive finance support that connects both financial and non-financial assistance, moving beyond simple loan product recommendations.

AI will also be introduced into internal screening and post-management work. The AI screening support system will check for missing essential items in the documents submitted to the electronic document management system for subrogation screening. It will also be able to classify cases that can be automatically determined according to set screening standards and those that require further review.

Automatically Reviewing Screening Documents and Selecting Targets for Debt Collection

In debt collection work, a machine learning model will be applied to analyze past customer contact history and data on successful recoveries. The goal is to improve the efficiency of post-management work by identifying borrowers with a high likelihood of debt recovery.

AI will also be utilized in employees' research and report writing work. When staff members inquire about laws, regulations, or work manuals, the internal search platform will present the relevant clauses and supporting documents. Additional functions will be established to draft documents according to the agency's internal templates—such as management evaluation reports, work plans, and press releases—as well as to compare the differences between multiple documents or summarize large volumes of data.

Separately, the agency is also working on developing an alternative credit assessment model for low-credit borrowers using its own data. The plan is to develop a model that can more accurately assess the creditworthiness of low-credit borrowers, supply it to savings banks and other institutions, and develop it into a revenue-generating business. In this process, the agency is reportedly considering sharing data such as tax arrears information from the National Tax Service. The intention is to understand the specifics and background of the arrears, so that borrowers who inevitably fell behind on taxes due to livelihood difficulties are not classified as high-risk borrowers and thereby excluded from access to policy funds.

This content was produced with the assistance of AI translation services.