Loan Screening for 20s 'Thin Filer' to Be Entrusted to AI

Increase in 20s Young Borrowers Requires Loan Screening
Young Adults Starting Careers Face Low Credit Scores Under Current System
Financial Sector Introduces AI Systems for Credit Evaluation
Measured by Mobile Payment Records, Student Loan Repayment Rates, and Tax Payments

[Asia Economy Reporter Shim Nayoung] 'Thin filers' refers to bank customers with minimal financial transactions and thus thin related documents. Typical examples include college students or young professionals who have no credit card usage history in the past two years or no loan records in the past three years, making credit evaluation difficult. These individuals are likely to receive low ratings under the current credit rating evaluation methods of commercial banks. The financial sector is developing a system that entrusts loan screening for such borrowers to artificial intelligence (AI).

On the 3rd, a report titled "Utilization of Artificial Intelligence in the Financial Industry and Policy Tasks" (Seo Jeongho, Vice President of the Korea Institute of Finance) revealed that among eight domestic banks (KB Kookmin, Shinhan, Hana, Woori, three regional banks, and one internet bank), AI utilization was highest in the fields of credit evaluation and loan screening. In particular, as loan demand increases among people in their early to mid-20s investing in stocks and Bitcoin, introducing AI-based credit evaluation models targeting thin filers is a representative example. Data such as thin filers' mobile phone payment records, student loan repayment rates, and tax payment histories are used by AI to derive credit ratings.

The report stated, "In the personal loan sector, it was difficult to obtain loans using existing statistical evaluation models," and added, "While AI cannot directly prove correlations with repayment rates or default rates, it can assess the significance of these relationships." It also noted, "AI can be used in interest rate approval and detailed limit adjustments, and the financial sector believes that accuracy and discrimination power have improved," and "To actively utilize AI, collecting more data to analyze repayment ability is a task for the financial sector."

Beyond the thin filer cases, AI utilization has become an alternative in the personal loan sector. The U.S. investment bank Citigroup monitors customers' social network service (SNS) data to use as supplementary information for credit rating decisions. Domestically, Shinhan Bank is preparing models that analyze the likelihood of loan delinquency using AI with credit-related data and can assess the credit of small business owners.

AI utilization in the corporate loan sector remains minimal. The report stated, "Some banks collect all external data, including qualitative indicators such as news articles, in addition to corporate-related indicators like financial statements, to evaluate companies," but added, "AI-based models for corporate clients are still in the early stages and are not directly used for credit evaluation but serve as reference materials for loan officers' judgments."

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